TDS Exsum-EN 03.Content Final 20180404 · 2018-05-15 · 2-1 2.1 Review transportation and traffic...

Executive Summary Report Travel Demand Freight Movement Survey

For National Transport Planning

Content-1

Content

CHAPTER 1

INTRODUCTION

Page

1-1

1.1 Reasons and Background 1-1

1.2 Object 1-1

1.3 Scope of study 1-2

1.4 Study Framework 1-3

CHAPTER 2

THE STUDY GATHERS THE RESULTS OF STUDIES AND THE IMPLEMENTATION OF VARIOUS PROJECTS ASSOCIATED

2-1

2.1 Review transportation and traffic policies and related projects 2-1 2.2 Gathering the Traffic and Transportation in Bangkok and Metropolitan Area 2-3 2.3 Gathering the Traffic and Transportation Data 2-4

Chapter 3 Analyzing Travel Needs in Bangkok and Its Vicinity 3-1 3.1 Survey Demand Survey (Travel Demand Survey) 3-1 3.2 Survey and Analysis of Trip Selection 3-8

Chapter 4 Commodity Flow Adjustment of Country 4-1 4.1 Conceptual for Commodity Flow Analysis and Updating Data 4-1 4.2 Results of Commodity Flow Survey 4-2

4.3 Commodity Flow Analyzing 4-4

CHAPTER 5 DEVELOPING A BANGKOK MODEL AND METROPOLITAN AND APPLIED 5-1 5.1 A study of transport and traffic modeling in Bangkok and its vicinity 5-1

5.2 Improvement of study area and sub-area (TAZ) 5-4 5.3 Economic and Social Update 5-5 5.4 Improvement of transport network 5-10 5.5 Improved Trip Generation Model 5-10

5.6 Improved Trip Distribution Model 5-13



Content-2

Content (Cont.)

Page

5.7 Model Split Model Improvement 5-14 5.8 Improving Trip Assignment Model 5-15 5.9 Model Calibration 5-16

Chapter 6 National Model (NAM) and Application 6-1 6.1 Developing and Improving of National Model (NAM) 6-1 6.2 Travel Survey for National Model (NAM) 6-4 6.3 Model Analysis and Prediction 6-5

Chapter 7 DEPTH DATABASE OF TRAVEL BEHAVIORS (ACTIVITY-BASED) 7-1 7.1 The development of Activity-Based Travel Demand Model. 7-1 7.2 Traffic surveys and live interviews 7-2

7.3 Model development 7-6

Chapter 8 Geographic Information System Revision and Management Information 8-1 8.1 Design, develop, improve, transport and service networks in an integrated

manner. Geographic Information System (GIS) 8-1 8.2 Preparation of Executive Information System (EIS) 8-4

CHAPTER 9 PUBLIC CONSULTATIONS, TECHNICAL TRAINING AND PROJECT PUBLIC

RELATIONS 9-1

9.1 Summary of 1st Public Consultation 9-1

9.2 Public Consultation with Model Users (Government Agencies)

9-2

9.3 Focus Group Meeting 9-3

9.4 Meeting with Academics for Model Development Suggestions

9-4

9.5 Summary of 2nd Public Consultation Development Suggestions

9-6

9.6 Technical Workshop and Technology Transfer

9-7

9.7 Project Public Relations 9-11



Content-3

Table of Contents

หน า

Table 4-1 Top 50 Commodities by Transport Weight 4-6

Table 4-2 Average Transportation 4-8

Table 5-1 Development and Improvement of the Ebum Model to Date 5-2

Table 5-2 Economics and social update lists 5-5 Table 5-3 Economic and Social Data Forecasts 5-9 Table 5-4 Trip Rate for Each Objective of the Trip 5-11 Table 5-5 Travel Attractiveness 5-13 Table 5-6 Calculation of passenger volume 5-16 Table 5-7 Calculation of average traffic volume in Expressway system 5-17 Table 5-8 number of passengers using public transport 5-19 Table 7-1 Midblock Count Survey 7-2 Table 7-2 Result of the anticipation from Activity-Based Model in Amphoe

Mueang, Nonthaburi Province 7-7

Table 7-3 Result from eBum in Amphoe Mueang, Nonthaburi Province 7-8 Table 5.9-3 Calculation of Traffic over the Chao Phraya River 5-18 Table 5.9-4 Travel Volume in the Year 2017 5-19 Table 5.9-5 Travel Form in the Year 2017 5-19 Table 5.9-6 Travel Form in the Year 2017 5-19 Table 9–1 Technical Workshop and Technology Transfer 9-8 Table 9-2 PR Media / Tools Used in Meetings 9-13



Content-4

Figure of Contents

หน า

Figure 5-1 Overview of the Ebum Model 5-1 Figure 5-2 Model Structure of the Project Selection Model 5-15 Figure 7-1 Travel Pattern (Monday- Friday) 7-4 Figure 7-2 Travel Pattern (weekend) 7-5 Figure 7-3 Travel Demand in 2017 7-6 Figure 7-4 Travel Demand in 2042 7-7 Figure 8-1 GIS Design and Development Guideline Chart 8-1 Figure 8-2 GIS MODEL OF THE PROJECT 8-4 Figure 9-1 Atmosphere of 1st Public Consultation 9-1 Figure 9-2 Atmosphere of Public Consultation with Five Government Agencies 9-3 Figure 9-3 Atmosphere of Focus Group Meeting 9-4 Figure 9.4 Atmosphere of Meeting with Academics for Model Development Suggestions 9-5 Academics Name List 9-5 Figure 9-5 Atmosphere of 2nd Public Consultation 9-7 Figure 9.1-1 Atmosphere of Technical Workshop and Technology Transfer 9-9 Figure 9.6–2 Atmosphere of Technical Workshop and Technology Transfer 9-10 Figure 9.6–3 Atmosphere of Technical Workshop and Technology Transfer 9-11 (4 Additional Courses) 9-11 Figure 9-7 Project’s Social Network (Facebook) 9-12 Figure 9-8 Project’s Website 9-12 Figure 9-9 Project PR Leaflets of 1st Public Consultation 9-13 Figure 9-10 Supporting Documents of 1st Public Consultation 9-14 Figure 9-11 Exhibition and Information Boards of 1st Public Consultation 9-15 Figure 9-12 Video Presentation of 1st Public Consultation 9-15 Figure 9-13 Project PR Leaflets of Focus Group Meeting 9-16 Figure 9-14 Supporting Documents of Focus Group Meeting 9-17 Figure 9-15 Exhibition Boards of Focus Group Meetings 9-17 Figure 9-16 Project PR Leaflets of 2nd Public Consultation 9-18 Figure 9-17 Supporting Documents of 2nd Public Consultation 9-19 Figure 9-18 Exhibition and Information Boards of 2nd Public Consultation 9-19



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1. Introduction

1.1 Reasons and Background

On December 1, 2015, the Cabinet acknowledged the Action Plan in National Strategy 20 years frame, to accelerate the investment in infrastructure and logistic system in the country (topic 2.5), which relevant with 2017 fiscal year. The acknowledge itself intend to elevate the Global Competitiveness Index: GCI rate of Thailand in terms of increasing the Logistic Performance Index: LPI.

National Economic and Social Development plan chapter 12, (2017-2121) specify the development plan to promote middle class income to higher class, by accelerate the investment on national infrastructure such as public transit to be able to connect the domestic business throughout and the international business. In addition, the investment plan also goes toward the growth of trading.

As the strategy stated above, assigned by the National Economic and Social Development Board, Traffic Policy and Planning (OTP), which act under the Ministry of Transport is response in developing the plan and recommendation to the relevant authorities. The direction will be given paying attention to the estimation of travel demand and transportation demand, creating and developing public transit system along with traffic condition, developing the database of shipping goods, where is the dominant in beneficial of modeling. The modeling and database themselves will be a key tool for the relevant country projects that compatible with Thailand modern economic situation.

1.2 Objective

1) Perform Study Travel Demand Survey and Household Interview Survey of Behavior in order to use the information to benefit the calibration of transport and traffic mathematical models. Up to date information will leveling up the accuracy and efficiency of the model, to be consistent with the behavior changes and style. The result after all will be used in planning and decision making to solve transportation and traffic problems.

2) To set up the in-depth database on travel behavior of the population in the pilot areas in Bangkok and its vicinity, using in the analysis of traffic and transportation conditions at the activity based level.



1-2

3) Study, survey, storage, information, transportation and traffic information system on quantity and cost of goods, 180 products to be updated to be available in the geo database. This will be used and beneficial to the analysis of the freight proportion of the country that reflecting the various modes of transportation linked to the area

4) Study, analyze and prepare management information for planning and decision making in transportation and traffic.

1.3 Scope of study

The study area consists of 4 parts.

Part 1: Collect information and the results and the implementation plan of the associated projects.

1) Study, collecting data and perform the literature review on related traffic and transportation projects.

2) Collecting general information and perform literature review on following model; National Model: NAM and extended Bangkok Urban Area Model: eBUM.

3) Study and perform literature review on the national travel behavior in Bangkok area and its vicinity following with the household surveying.

4) Study and perform literature review on the previous freight survey such as the origin and destination information of 180 goods.

Part 2: Survey and analysis of travel demand and improving freight movements for appropriate transportation planning of the country.

1) Suggestion in the concept of performing travel demand survey in order to develop the traffic and transportation of Bangkok and its vicinity by specify the random sample of at least 15,000 samples.

2) Suggestion to develop the concept of completeness in database of the moving goods and traffic in the national level.

3) Survey and analyze the travel demand then identify the travel pattern of Bangkok and its vicinity.

4) Survey and analyze the travel demand better the freight system to benefit the transportation system of the country.



1-3

5) Design and develop the transportation system and services in Geographic Information System: GIS

6) Design and develop transportation and traffic model in national level and Bangkok and its vicinity by the area development and infrastructure development should be consider.

7) Analyze and develop the travel demand model for the based year and future year by describe by detail about the sources and analysis method.

Part 3: Development and applied the application of transport and traffic models.

1) Set up the detailed database of travel behavior of the pilot area in Bangkok and its vicinity in order to perform transportation and traffic analysis on activities based level.

2) Set up geo database in management level for making decision about transportation and traffic system. Publication on the system which Office of Transport and Traffic Policy and Planning owned is required.

3) Presentation of transportation model is required at least 5 topics.

4) Specify the development plan for the transportation model to every level of OTP and concept of the guideline in attention to survey the travel information and freight information.

5) Rectify the quality and keep the user licenses up to date for Cube software.

Part 4: The seminar arrangement and academic training session.

The study framework of travel demand survey and rectify freight system database to plan out the transportation system of country, is programmed to compatible with the figure below.

Figure 1-1: Study framework and methodology.

1.4 Study Framework

Study Demand Survey (Travel Demand Survey) and Improve Product Movement For the transportation planning of the country. The consultant has framed the approach and the study plan to be consistent with the scope of the operation and the duration. The plan can be summarized as planned. The framework for conducting the study is based on the nature of the relationship and the link as shown in Figure 1.4-1



1-4

Figure 1.4-1 Link diagram and sequence of operations

O-D / Mode ChoiceHome interview Survey

Traffic Survey

eBUM Development

Logistics O-DSurvey

Traffic Survey

NAM DevelopmentGIS Design &Develop

MISActivity Based Data

National Transport Survey Plan

Seminar & Training

eBUM Application NAM Application

Policy and Information Review

Software Maintenance

The workpart 4

The workpart 2

The workpart 1

The workpart 3



2-1

2. The study, collecting information, the study of results and its process of associated projects.

2.1 Review of transportation and traffic policies and related projects

Linkages of policies and development strategies related to transportation and logistics. As shown in Figure 2.1-1

Figure 2.1-1 Overview of policies and development plans of various agencies

Corporate Strategy

Ministry of Transport

National Strategy 20 years(2017- 036)

Strategy Strategic aspects to building a competitiveness.

The Twelfth National Economic and Social Development Plan( 017- 021)

Strategy 7 : Strategic aspects to development of infrastructure logistics and communication.

Office of the National Economics and Social Development Board

Strategic Plan for Logistics Development of Thailand No.3

017- 021

Eastern Economic Corridor Development) Draft Development Strategies for Thailand’s Transport System for 20 Years 2017- 036

Strategic Plan, Ministry of Transport (2017-2021)

Draft Strategic Plan of the Ministry of Transport to Support the Development of Logistics in the Country No.3 017- 021

Strategic Development of Thailand’s Transport Infrastructure( 015- 022)

Principles of Transport and Traffic Development Plan( 011- 020)

Action Plan, Ministry of Transport ( 017- 021)

Department of Rural Roads

Strategic Plan, Department of Land Transport ( 016- 020)

Strategic Plan, Department of Rural Roads 017- 020

Department of Highways

Strategic Plan, Department of Highways ( 017- 021)

The Urgent Policy of the Department of Highways aims to Achieve Strategic Success for Development of Thai Transport Infrastructure 8 years ( 015- 022)

Department of Land Transport

Other Programs of Expressway Authority of Thailand, Department of Land Transport, Bangkok Mass Transit Authority, Marine Department, Port Authority of ThailandState Railway of Thailand and Mass Rapid Transit Authority of Thailand



2-2

A review of the results of the study and the implementation of associated projects.

1) Review of transportation, traffic policies and related projects. Compilation and review of this study consisted of policy, strategy, development plan, economic and social and transportation and transportation, etc., to be used as the basis for the study of the project, consisting of group 1: policy and strategy, development plan and report. Economic and social studies and transport and transportation. Group 2: Economic and social groups and group 3: Transport and Transportation Planning Group

2) Collect information related to transportation and traffic in Bangkok and its vicinity.

Collecting Information of public transportation usage, project plan a n d Project Plan Home Interview Survey (HIS) from related organizations includes the Office of Transport and Traffic Policy and Planning Bangkok, Department of Highways, Department of Highways Expressway Authority of Thailand Harbor Department and Chao Phraya Express Boat, Bangkok Mass Transit System Public Company Limited (BTS), Mass Rapid Transit Authority of Thailand Bangkok ,Mass Transit Authority National Statistical Office Department of Public Works and Town Planning.

3) Collect basic information related to transportation and traffic at the national level. In this section, the consultants separate the work into two parts. The first part is the review of previous information of transportation and traffic. The second part is to study the plans and relevant projects in the past. For example, multimodal transport systems development and continuous management of logistics systems, Development of communication c o n n e c t between Thailand and neighbor countries. High-speed rail travel b e h a v i o r study t h a t c o m p a t i b l e w i t h study of the master plan, for the development of rail and high speed rail systems. Feasibility study and design study of dual rail projects across the country.



2-3

4) Study and review the related cargo survey results. Perform literature review through the database development projects and models for

integrating transport and traffic development, also multimodal transport and logistics

(TDML) onwards.

2.2 Collect basic information of Traffic and Transportation in Bangkok and Metropolitan Area

Modern and Future Transport Network

Number of current transport network

Future traffic network

Expressway 210.4 Km.

New addition 176.7 km (in 5 years year years years) Roads / Bridges

(Only on main line) 4,700 Km.

New construction 293.3 km (in 7 years) Extends 789.0 km (in 20 years)

Electric system 5 Lines Distance 107.8 Km. New addition 8 lines 426.92 km (in 8 years) Source: Consultant

Traffic information in Bangkok Metropolitan area

Traffic volume / user volume

expressway Annual average of 7 routes in 2016. - 653.51 million vehicles per year, representing 1.82 million vehicles per day.

Roads / Bridges Bridge over the Chao Phraya River with a total of 21 bridges - Early morning rush hour (7: 00-9: 00): 123,337 vehicles per hour

- Cold rush 155.555 cars per hour (16: 00-19: 00)

Electric system In the year 2017, 371 million people per year. - Metro dark green and light green 252.73 million people / year, average 0.76 million

people per day.

- 107.54 million blue-line metro / year average 0.33 million per day - Suvarnabhumi Airport Rail Link connects 22.52 million passengers a year,

averaging 0.06 million people per day.

- Purple Line 11.63 million people / year 0.04 million people per day



2-4


Bus* By 2015, there were 15,492 passenger cars, with a total of 1,452 million passengers a year, or

4.05 million passengers per day. Passenger boat Boat riders in the year 2016 (express boat along the Chao Phraya River with the passenger

boat Canal Saen Saeb) - The number of passengers is 64.52 million per year and is approximately 0.18 million per

day. Ferry crossing in 2016 - The number of passengers is 37.88 million people / year and the average rate is about

0.10 million people per day

Source: Consultant, PAT, MRTA, SRT, BMA, BMTA, MD and DOH

Average travel speed in Bangkok and its vicinity from Central Business Area through Ratchada Ring Road The speed of about 14.00 km. / hr. and the average speed of Ratchada outer ring to the outer ring. The speed is about 22.96 km. / hr.

2.3 Gathering the Traffic and Transportation Data

Modern and Future Transport Network

Number of current transport network

Future traffic network

Intercity highway network 141 km. 6,612.6 km.

Train 4,041 km. Add the tram route 4,692 km. 2,517 km of high speed trains

Source: Consultant

Traffic Information Network

Travel / Transport Format


Road Average daily traffic volume (AADT) of 217,588 million vehicles per day Road freight volume is 482,000 tons per year.

Bus Service By 2019, the number of passengers was 375 million. 25 million trips a year.

Train In 2016, there are 33 million passengers per year. 2,000 buses a month. Three-way bus service per month 11,000 tons of cargo per year



2-5

Travel / Transport Format


Waterway In 2015, the domestic water transport volume is 50,000 tons per year. 51,000 tons per year

In the year 2559, the volume of containers entering and leaving Bangkok (inbound) 855,575 TEU Bangkok - 603,246 TEU Volume of container through to and from Laem Chabang Port (inbound) 2,055,722 TEU Volume of container through-out Laem Chabang Port (outbound) 3,632,097 TEU Container volume through Songkhla port (inbound) 29,031 TEU Volume of container through Songkhla Pier (outbound) 77,639 TEU

Air By 2015, the number of passengers at all airports is 142,502 thousand. Total cargo volume was 1,465,610 tons.

Source: Consultant, DOH, DLT, SRT, MD, DOA, CAAT.

This study examines the content of model improvement and development, including the development of a national model (NAM) since the development of the Urban Transport Database and Model (UTDM) in 1995, after that, the project continued to develop in various stages.



3-1

3. Analyzing Travel Needs in Bangkok and Its Vicinity

Travel Demand Survey 3.1

Travel demand survey is required to perform in a household level. The Household Travel Survey (HTS) surveyed 18,833 households, or about 0.3 percent of households in the area. Quota sampling was used to randomly interview for one-day travel information during the period from May 15th to October 31st, 2017, mainly using the method of interviewing at home (Personal Interviews) and through the phone as an option for those who are inconvenient. The details of the interview in the household include: household information, personal information, purpose of travel, origin point - destination point travel Information. 2,582 Furthermore, alternative modes choices were selected in addition to the survey.

Table 3-1 Number of survey samples from previous studies and number of samples in the TDS project

Description UTDM (1995)

TDMC II (2003)

TDML II (2009)

TDL II (2013)

(TDS)

Covered area (province) 6 6 6 8 8

Number of households 2,856,000 2,830,000 4,906,000 5,643,000 5,643,000

Number of HTS samples (Household) 7,879 19,899 3,018 4,614 18,833

Number of mode choice sample - - 2,000 - 2,582

HTS ratio/household ratio (%) 0.28 0.70 0.06 0.08 0.30

Source: Consultant

3.1.1 Survey Results

The survey found that the majority of urban population (CBD) is live in outer tring of urban areas (18.4%), Urban (50.8%), Suburban (30.8) with 52% of woman and 48% of male. The average age is 34 years, average household size of 2.57 persons per household. When categorize the size of households in each area found that the inner Bangkok area (CBD) has an average household size of 2.64 people per household. Urban Bangkok has an average household size of 2.62 persons per household and suburban area with an average household size of 2.43 persons per household. The average income in a month is 37,000 baht per household with the average personal income is 17,300 baht per month.



3-2

Household vehicles ownership is about only 29.4 percent, only 22.6 percent with no vehicles ownership. The average vehicle ownership rate is 0.98 units per household while the average motorcycle ownership is 0.77 units per household.

2.1% >60 2.3%

8.3% 50-60 6.0%

19.5% 40-50 15.0%

33.2% 30-40 31.2%

28.1% 20-30 35.4%

7.7% 10-20 8.9%

1.0% 0-10 1.3%

อาย

CBD18.4%

SUBURBAN30.8%

URBAN50.8%

Student16.1%

Work out74.6%

Work at home7.1%

No job2.2%



3-3

The vehicle ownership characteristic found to have an obvious relationship with income.

High income group tends to have high occupancy rates. The classification of vehicles by area showed that all areas covered most of the cars and obviously seen that the inner space of urban has motorcycle ownership rate significantly less than the outerpart area.

1 2 3 4 4

17.71%

34.86%

25.23%

19.84%

2.36%

0VEH22.6%

MC22.0%

MULTI26.0%

PC29.4%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0

1-5,000

5,000 – 10,000

10,001 – 20,000

20,001 – 30,000

30,001 – 40,000

40,001 – 50,001

50,001 – 60,000

60,001 – 70,000

70,001 – 80,000

80,001 – 100,000

100,000

0VEH MC PC MULTI

30%

24%

18%

11%

21%

27%

35%

30%

26%24% 24%

30%

CBD URBAN SUBURBAN0VEH MC PC MULTI



3-4

Travel characteristic Average travel time is 1.97 people - daily

/ daily. People communting each day to work (HBW) is about 63.1%, for education (HBE) is about 12.1%, and 8.0% for those who do not travel. The survey found that some of who do not travel to or from home (NHB) does not willingly to provide the information to the team causes significantly lower in results.

Type of Travel HBW HBE HBO NHB Total

CBD 1.35 0.28 0.28 0.18 2.09 Urban 1.28 0.26 0.26 0.16 1.96

Suburban 1.27 0.25 0.25 0.15 1.92

Note: HBW is Home-Based Work

HBE is Home-Based Education

HBO is Home-Based Other

NHB is Non-Home-Based

CBD is Central business district

Travel characteristic of the samples in the most study areas is travel by private vehicle with the highest rate among all, which 39.9% following by motorcycle with 23.8%. In addition, the indept detail of the study of each area shows an interesting point of how modes vary attractively through the area.

Travel by motorcycle is less popular in cenral business area of Bangkok (CBD) than in the outer part of urban area and suburban area with 14% versus 22% and 35%. While, using pubic transit is the most attractive mode of travel to the users especially bus in the inner part of Bangkok and the using rates is decreasing accordingly to the distance from the center part.

Traveled8.0%

Work63.1%

Study12.1%

Private errand11.5%

Work errand2.7%

Transfer2.5%



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The average travel distance is 12.6 kilometers among three highest major modes which are bus (20.9 kilometers), school bus/pick up service (15.6 kilometers) and personal vehicle (15.5 kilometers).

The average travel time is 32 minutes, with the three maximum travel times of 3 types following van with 50 minutes, for bus is 43 minutes and school bus/pick up service is 41 minutes.

The average speed of travel is 22.9 kilometers per hour. The top three travel modes are personal cars with 26.5 kilometers per hour, taxi with 25.4 kilometers per hour and van with 25.0 kilometers per hour.

Private car (PC), 39.9%

Motorcycle (MC), 23.8%

Public car, 23.8%

School bus, 2.1%Taxi/MC Taxi, 4.6%

Walk/Bike, 5.7%Other, 0.3%

MRT/BTS 1.2%

BUS 18.1%

Air bus 1.8%

Van Taxi 2.7%

40%

14%

33%

1%6%

6%

0%

CBD

-

43%

22% 25%

2%4%

4%

0%

URBAN

-

33%

35%

15%

4%

4%

9%

0%

SUBURBAN

-



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The average travel expense is 28 baht per trip. The maximum cost of taxi is dominant with 112 baht per person, personal vehicle is 61 baht per trip (excluding the price of the car itself) and lastly 42 baht per trip for the mass transit such as skytrain and underground train.

Distance Time

Spped Expenses

The origin - destination information of the survey samples.

24 groups were categorized for the easy understanding presentation. The travel directions are likely to getting into the inner city, travel within area and travel to neighbor area respectively.

12.6

15.5

9.7

14.7

12.7

20.9

14.2

4.9

15.6

Average

Private car (PC)

Motorcycle (MC)

MRT/BTS

Public car

Van Taxi

Taxi

MC Taxi

School bus

33

36

24

37

41

50

34

15

41

Average

Private car (PC)

Motorcycle (MC)

MRT/BTS

Public car

Van Taxi

Taxi

MC Taxi

School bus

22.7

25.9

24.5

24.0

18.5

24.9

25.2

20.0

23.0

Average

Private car (PC)

Motorcycle (MC)

MRT/BTS

Public car

Van Taxi

Taxi

MC Taxi

School bus

32

61

10

42

15

29

112

28

7

Average

Private car (PC)

Motorcycle (MC)

MRT/BTS

Public car

Van Taxi

Taxi

MC Taxi

School bus



3-7

Zone District Zone District Zone District

Zone 1 Dusit, Pathumwan, Pom Prap Sattru Phai, Phra Nakhon, Ratchathewi, Samphanthawong

Zone 9 Khlong Sam Wa, Minburi, Ladkrabang, Nong Chok

Zone 17 Bangkruai, Bang Yai

Zone 2 Bangrak, Bang Kho Laem, Yannawa, Satorn

Zone 10 Khlong San, Thon Buri, Bangkok Noi, Bangkok Yai, Bang Phlat, Rat Burana

Zone 18 Bang Bua Thong, Sai Noi

Zone 3 Khlong Toei, Wattana Zone 11 Talingchan, Thawi Watthana, Bang Khae, Phasi Charoen Nongkhaem

Zone 19 Thanyaburi Nong Suea, Klong Luang, Lamlukka

Zone 4 Phayathai, Huay Kwang, Din Daeng, Wang Thonglang

Zone 12 Chom Thong, Thung Khru, Bang Khun Thian, Bangbon

Zone 20 Pathumthani, Lat Lum Kaeo, Samkhok

Zone 5 Bang Sue, Jatujak Zone 13 Phra Samut Chedi, Phra Pradaeng

Zone 21 Kamphaeng Saen, Don Mueang, Nakhon Chaisi, Bang Len, Phutthamonthon, Nakhon Pathom, Sam Phran

Zone 6 Donmuang, Bang Khen, Sai Mai, Laksi

Zone 14 Muang Samut Prakan, Bangplee

Zone 22 Samut Sakhon, Krathumbaen, Ban Phaew, Southern Provinces

Zone 7 Kanchanaburi, Bangkapi, Bueng Kum, Ladprao, Saphan Sung

Zone 15 Bangbor, Bangsaotong Zone 23 The provinces in the north and northeast

Zone 8 Phra Khanong, Pravet, Suanluang, Bangna

Zone 16 Nonthaburi, Pakkret Zone 24 Eastern Province

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( - )300,000 150,000 75,000

1

23

5

46

6

9

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12

13

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15

16

17

18

19

20

21

22

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Number of trip (person-trip/day)



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Survey and Analysis of travel behavior and mode choices 3.2

To be consistent with the behavior of travel and current travel modes patterns, the consultants use a model of travel selection in the form of Nested logit model or Hierarchical logit model as a Logit model, which is used for simulating the selection of travel patterns. The factors influencing the choice of travel options were determined by a hierarchical selection hierarchy to examine the choice of travel patterns of the target population. Target groups are divided into two groups: Private Transports and Public Transports.

3.2.1 Surveying the Choice of Travel Forms (MSP)

Mode Choice surveyed 2,582 samples, covering Bangkok and the suburbs. 6 types of travel modes are classified into four categories:

1. Home base work (HBW)

2. Home base education (HBE)

3. Home base others (HBO)

4. Non-home base (NHB)

Travel modes

Private transports Public transports

Private Car (PC)Private

Motorcycle (MC)High Performance

Transit (HPT)

Medium Performance Transit (MPT)

Low Performance Transit (LPT)

Paratransit (PRT)

BTS MRTA Etc. ACBus

Public van

Ordinary bus

Vessels RailEtc. Etc. Hired-motorcycle

Taxi Tuk-tuk Etc.

13

7

14

89

10

11

12

15

16

6

54

3

2

1



3-9

Travel Form Number of samples (set)

Personal Car (PC) 760

Motorcycle (MC) 485 High Performance Public Transport (HPT) 320

Medium Performance Public Transport (MPT) 316 Low-Performance Public Transport (LPT) 318

Traveling By taxi (PRT) 300 Total 2,582

Setting the study area and target audience for the survey by gathering information covering all target groups, either it is a personal vehicle or a public transport. The study area was scattered throughout Bangkok and the suburbs. Determine the variables to decide the travel patterns can be divided into 3 groups according to the characteristics of the data.

- Travel characteristics

- Variables from demographic data. (Socioeconomic characteristics) and

- Variables from the travel characteristics (Mode characteristics)

According to the survey, vehicle ownership is a key factor in choosing a travel style. Most people who do not have a vehicle will choose a form of travel using public transport and taxis.

Those who occupy most of the vehicles will use a form of travel that corresponds to the vehicle occupied.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

0VEH

MC

PC

MULTI

Private car Motorcycle Public car School bus Taxi Other



3-10

3.2.2 Survey Results and Analysis of Trip Model Selection

Considering the factors of choosing the travel pattern of the sample, the first three groups of personal car users were fast, safe and easy to access. The factors in choosing the travel patterns of the public car users group were as follows: Easy access

Considering the nature of public transport, the time it takes to travel from the point of

origin to the point of change, the average journey mode takes about 10 minutes and takes an average of 4-10 minutes. The average journey is 40-70 minutes.

(BTS/MRT/ARL)

regular bus / minibus / four

wheeler

Air-conditioned

bus

Public van

Boat

Access Time (Min.) 10.78 12.51 10.29 11.46 5.75 Waiting Time (Min.) 4.16 8.57 8.49 9.41 10.00 In Vehicle Time (Min.) 18.15 34.55 35.70 38.54 26.67 Egress Time (Min.) 10.62 16.28 12.52 9.05 27.5

Total Time (Min.) 43.71 71.91 67.00 68.46 69.92 Average Travel Expenses (Baht) 33.69 10.89 17.99 27.88 20.67

Based on the factors influencing decision-making, choice of travel patterns and theories related to education, model selection, and travel patterns in each selection. Travelers will choose the most discretionary or desirable travel option. The utility function can be used to check the satisfaction of the traveler. The results will be presented in the model development section.

Punctuality2.25%

Security16.18%

Easy access10.95%

Low cose7.17%

Speed63.21%

No choice0.24%

Factors of mode choice for private carPunctuality

1.81% Security9.27%

Easy access17.71%

Low cose23.29%

Speed47.55%

No choice0.38%

Factors of mode choice for public car



4-1

4. Update on the information of the country’s goods transportation

4.1 The concept of analysis of goods transportation and the issues to update

Updating the information on goods transportation will integrate the analysis of secondary data that is received from agencies and studying results accompany with survey result on entrepreneurs, fieldwork transportation, and database from Department of Land Transport’ cars’ GPS. The analysis of transportation quantity between the origins and the destinations will consider from the information shown below;

1) Information on goods transportation in various types of transportations. The information about rail transportation came from State Railway of Thailand, the information about water transportation came from Harbor Department, and the information about air transportation came from Thai Airways International Public Co., Ltd. and Department of Airports. The information about land transportation are the survey result of Department of Highways, accompany with the database from Department of Land Transport’ cars’ GPS.

2) Information on the export goods’ production in each regions or information of the import goods’ consumption.

3) Information on goods’ exports and imports at the trading gates.

4) Information on made-in-country-goods’ consumption in the country.

5) Information on the country’s population and Gross Product Value of each provinces.

4.2 Survey results of the information on goods transportation.

4.2.1 Surveying the entrepreneurs

The processes will be in-depth interviewing in forms of individual interviews and in small groups. The small groups interview will be like focus group with entrepreneurs from different kinds of products, which are prioritize those who produce industrial goods from the Federation of Thai



4-2

Industries, many Manufacturers Associations, Logistics Association, etc. the numbers of entrepreneurs that had contacted for interviewing are 120 entrepreneurs, covering 180 items.

4.2.2 Cargo’s Roadside Interview Survey: RIS

The example of 20 Department of Highways’ weight checkpoint stations that were being surveyed, checked in total of 8,071 trucks. When considering types of goods that were being transported through those 20 stations, they found out that types of goods that are being transported, the majority were industrial goods and construction materials, the minority were agricultural processed goods and consumer products.

Survey results from the customs checkpoints on the list of goods that were being transported on weight checking stations said that the products are separated into 34 groups, according to the list from the Ministry of Transport and the Department of Land Transport. Those products were being surveyed on the weight checkpoints were separated according to type of goods, the result found out that in each region, the majority of goods were agricultural and industrial goods.

51718

83

910

51

32

60

610

158

265

66

610

136

137

216

79

52214

1110

73

30

2617

107

2113

1813

384646

950

411713

1330

276

85

158

011

73

03

20

91

77

23

250

1717

3251

4418

2358

221719

6232

916

3743

2122

46

2222

1710

1138

178

21716

103

1232

139

254

8

1717

25

74

127

1787

31

944

1512

144

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Ko Kha (OUT)

Nong Han

Rassada

Tha Sae

Si Racha

Banphot Phisai

Rayong

Samut Sakhon

Ban Pong

Bang Pa-In

Agricultural Agricultural processed goods Industrial goods Energy Construction materials Consumer products Other



4-3

The survey results from Truck Terminal said that the number of examples that were being surveyed from 4 terminals are 1,647 examples. When considering about types of goods that were being transported through those 4 stations, they found out that the transportation through Rom Klao Terminal and Phutthamonthon Terminal were similar; consisted of 80% of consumer products, followed by 10% of industrial goods. When considering at Klong Luang Terminal, the majority of products that were being transported consisted of 60% of consumer products, followed by construction materials and industrial goods around 9%. The type of transportation at Ladkrabang Terminal were quite different comparing to other terminals, they found out that the majority, 30%, of goods transportation is industrial goods, and were some proportion of agricultural processed goods and consumer products around 10% to 15%.

Chiang Sae

Maesai

Chiang Khong

Saphan 2 (Mukdahan)

Khlong Yai

Saphan 3 (Nakhon Phanom)

MaeSot

Saphan 1 (Nong Khai)

AranPrathet

Sadao

Agricultural products

Agricultural products transform

Industrial Products

Energy Products

Construction materials

Consumer products

Others

Chong Mek (Ubon Ratchathani)

0

4

1

4

0

2

4

11

9

10

10

30

0

0

0

0

29

0

0

2

62

80

84

16

0

4

0

36

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Ladkrabang Cargo Terminal

Romklao Cargo Terminal

Phutthamonthon Cargo Terminal

Khlong Luang Cargo Terminal

Agricultural products

Agricultural products transform

Industrial ProductsEnergy Products

Construction materials

Consumer productsOthers



4-4

So, the result of the analysis of goods transportations’ behaviors from each station were used to analyze the goods transportations’ behavior in forms of models, to predict the transportation in the future.

4.3 The analysis of goods transportation

This study had improved and updated all of 180 lists of goods to label them in Harmonized System, also grouping the goods in order to be more suitable for further analysis and modeling, to be consistent with goods lists from Office of the Permanent Secretary of Ministry of Transport. They separated goods into 3 groups, as are;

Group A: Highly imported-exported Goods – 163 items, separated in 44 groups under 16 categories.

Group B: Lists of goods that are being transported only in Thailand, or 8 types of goods that are being imported-exported from group A.

Group C: Goods crossing the border – the lists of 9 goods that duplicate with goods from group A.

To analyze the quantity of transportation, the numbers goods that are being highly imported and exported will be considered together with information regarding the supply chain and transportation of each type of goods. Each type of goods in provincial level will be compared in the

Kaengkhoi Bang Pa-In Wang Noi Ban Pong PhotharamSamutSakhon

Wang NamKhiao

RayongLat BuaLuang

BanphotPhisai

PhayuhaKhiri

Si Racha Sai Noi Tha SaeMuangphon

Rassada Phitsanulok Nong Han Ko Kha (IN)Ko Kha(OUT)

Semi-Trailer Truck 30,961 52,667 27,405 6,578 2,738 7,245 18,621 20,435 9,999 11,268 39,048 11,400 8,530 34,238 42,772 2,858 2,910 7,758 9,474 13,051

Trailer Truck 33,220 56,038 22,049 9,574 6,912 7,017 8,061 7,460 13,882 21,771 36,340 3,762 23,530 22,115 17,486 10,160 6,904 10,305 8,144 7,685

Special Truck 13,113 5,180 693 181 135 116 110 840 129 4,947 6,984 943 258 429 12 662 1,020 47 5,334 2,646

Hazardous material Truck 1,509 345 1,755 257 71 1,163 216 2,941 419 1,277 13,106 3,840 342 1,003 1,502 662 1,426 931 790 6,112

Liquid tank Trailer Truck 672 567 481 273 247 457 212 1,416 137 969 7,337 1,768 70 3,761 744 78 389 233 257 518

Container Truck 3,523 45,442 14,327 1,800 1,313 7,262 2,704 4,125 1,030 3,247 18,396 3,336 1,496 18,210 6,212 1,123 636 1,786 6,315 3,943

Pickup Truck 15,265 37,295 17,877 5,734 4,872 5,729 2,731 4,121 2,959 9,386 23,702 2,239 4,080 23,206 9,764 4,444 3,551 2,974 7,478 8,587

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

200,000

Bord

er tr

ade

volu

me

Tons

/Day



4-5

transportation table (O-D Table), separated into transportation for imports and exports, and transportation for the in-country uses.

The analysis on quantity and transportation from Origin to Destination in the country’s big picture can be separated into Origin - Destination Corridor because Thai’s goods will depart from the country’s center, which is Bangkok and its perimeter provinces, except some types such as agricultural goods which is transported between central markets in specific groups of provinces, in the case of not being transported through Thai’s market. The O-D Corridor consists of northern line, eastern line, western line, southern line (east coast and west coast), north-eastern line (upper and lower), and north-eastern line (eastern border).

Paddy

Animal

Sugar Cane

Soil, Rock, Sand,

Consume

Animal feed

Construction Materials

Construction Metal

Total Volume of Domestic

Freight

Import-Export Lists

Total VolumeFor Import-

Export

Total Volume



4-6

For the quantity of the transportations, consisted of imported goods, exported goods, and in-country transportation, in total of 180 items, that came from the analysis of the result survey, concluded that the total amount of items being transported is 854 million tons, separated into groups of imported goods approximately 110 million tons, exported goods approximately 122 million tons, and goods for in-country consumption approximately 622 million tons. The most transported goods came from 50 types and considered to be 90% of the total number, majority is in-country consumer products.

Table 4.3-1 Top 50 Commodities by Transport Weight (Unit : Tones)

Ranking Data Goods Transport volume


1 soil stone sand 198,007,269 26 corn 4,751,800 2 sugarcane 94,047,042 27 wheat and meslin 4,577,888 3 cassava products/tapioca

products 45,165,943 28 residue of vegetable oil

and soybean 4,506,219

4 cement 44,320,404 29 molasses 4,425,142 5 instant oil/fuel oils 40,101,524 30 rubber/rubber tree 4,339,229 6 consumer products 36,500,000 31 steel structure/structure 4,273,190



4-7



made of steel 7 paddy/unmilled rice 28,345,813 32 fish, fresh and frozen fish

fillet 3,974,700

8 coal 22,313,544 33 ethylene 3,915,496 9 rice 22,304,778 34 component and

accessories of car/car parts and accessories

3,769,056

10 feed/animal feed 19,619,583 35 car/auto/automobile 3,347,504 11 fertilizer 12,746,009 36 lumber/timber 3,253,899 12 oil palm/palm 11,685,721 37 cylic hydrocarbon 3,081,051 13 gypsum 10,412,575 38 cold rolled steel 3,057,050 14 hot rolled steel 10,076,559 39 soybean 2,999,810 15 sugar 9,787,842 40 glass and mirror/glass and

looking glass 2,990,255

16 marble and granite 9,638,916 41 natural gas 2,811,165 17 crude oil 9,463,592 42 fibreboard 2,739,019 18 semi-finished products of steel or

stainless steel 8,823,563 43 pulp and scarp of paper 2,564,557

19 beverage 7,771,655 44 terephthalic acid 2,525,713 20 polyacetal 6,414,719 45 propylene 2,392,114 21 living creatures/living animals 5,712,968 46 acylic alcohaol and

derivative 2,200,539

22 paper and paper products 5,435,860 47 palm oil 1,971,972 23 acylic hydrocarbon 5,223,157 48 plastic packaging 1,836,487 24 floor tile wall and mosaic 5,140,736 49 synthetic rubber 1,777,544 25 petroleum 5,030,221 50 juice/fruit juice 1,732,886

However, to study about goods transportation’s quantity in this project, the adviser use secondary database from sources that related such as Office of Agricultural Economics, Office of Industrial Economics, Division of the Industrial Factory, Office of the Cane and Sugar Board, Department of Primary Industries and Mines, Ministry of Energy, Ministry of Commerce, and Thai Customs, so the information about production volume, in-country usage, imports, and exports gathered were reliable and credible, and there were also the organization that can be verified. So, the result of the prediction of the goods transportation’s quantity in the program was that the overall quantity increased 3% per year, and mainly transported via roads; more than 87% of the overall quantity, transported via water was 12%, and others 1%.



4-8

Table 4.3-2 Average Transportation

Type of Transportation

Quantity of Goods

Transportation

(tons per year)

Ration of Transportation (%) Transportation Cost*

(Baht/ton-km.)

Land Transportation 699,743,964 86.897 1.384

Rail Transportation 9,678,384 1.202 0.713

Water Transportation 95,775,615 11.894 0.518

Air Transportation 60,784 0.008 20.000

Total 805,257,963 100.00

So, mostly of goods transportation was transported by land, using roads, such as consumer products, agricultural goods, and constructional materials, because land transportation is the way that can access to the most destinations (door to door) as can be seen from the table – 84% of all transportations. For water transportation, mostly are goods that are very heavy, but not as much of values, such as unmilled rice, stones, soil, sand, cement, as shown in the table at 12% of all transportations. Rail transportation in Thailand is not as popular as others because the railway system in Thailand isn’t covered the whole country. And if the entrepreneurs don’t have access to connect their factories with the railway system, there would be double cost on transportation (double handling). The majority of rail-transported goods are instant oil, cement, iron, stones, and is calculated as 3% of all transportations. Air transportation is around 1% of all transportations in Thailand, which is rather stable because air transportation is only for specific types of goods, the very valuable ones, such as medicine, vaccine, transitional organs, orchid, vegetables, etc.



5-1

Develop Bangkok and metropolitan areas model and 5.adoption

5.1 A study of transportation and traffic modeling in Bangkok and its vicinity

5.1.1 Overview of the eBUM model

The extended Bangkok Urban Model (eBUM) model is structured as a 4-Sequential 4-Step Model, which is widely used throughout the world. It consists of 1) Model Travel 2) travel distribution model 3) travel model selection model; and 4) travel distribution model. The relationship of the HTS with the eBUM model is shown in Figure 5-1.

Figure 5-1 Overview of the eBUM model

5.1.2 Model Development Review

The consultants have reviewed the eBUM model as shown in Table 5-1. The details are as follows:

Household Travel

Survey (HTS)

- Trip Rate- Vehicle Ownership- Household size

- Origin- Destination

- Mode Choice

- Goods Vehicle Demand- External Matrix Demand- Special Generator

Traffic Analysis Zone (TAZ)

Planning Data- Population- Employment- Education- Commercial Demand

Transport Network- Highway- Public Transport

Assignment

Modal Split

Trip Distribution

Trip Generation



5-2

Table 5-1 Development and improvement of the eBUM model to date

Project Year comprehensive

(province) Subdivision

Census (BE)

HTS survey (household)

Survey Structure MSP

Program Structural model

UTDM 1993 520 2533

7,879 N/A - The model is structured as 4 Step Models: Trip Generation Trip

Distribution Modal Split and Traffic Assignment

TDMC 1995 - - TRIPS - Sector (Sector) of 15 divided into 32 areas

TDMC II 2001

1,521

19,899 - - Updated data according to the census of the National Statistical Office (2000) TDMC III 2002 - - Binary

TDMC IV 2003 6 - - - Improve the travel classification model as a classifier. (Multi

Class Assignment) - Develop a model in the Back Back Loop.

TDMC V 2004 625

- - - Improve virtualization

TDMC VI 2005 2543 - - - Improve economic and environmental analysis

TDML 2006 776 - - CUBE

Voyager - Subdivision by Green Line Extension Line

TDMLII 2007 1,657

3,018 2,000 Nested Logit Model

- Improve the parameters and parameters of the trip model

TDL 2008 - - - Improve communication network

TDL II 2011 8 1,771 2553 4,614 N/A Multinomial Logit Model

- Covering 8 provinces by adding Ayutthaya and Chachoengsao

- Improve the parameters and parameters of the trip model, distribution and travel

- Improve BTS/MRT corridor atleast one distribute area per station to better predict the amount of passengers

- improve trip generator models by dividing travelers into 4 groups including no vehicles, motorbike owner, car owner, and more



5-3

Project Year comprehensive

(province) Subdivision

Census (BE)

HTS survey (household)

Survey Structure MSP

Program Structural model

than one vehicles owner and analyze trip production in 3 areas including inner Bangkok, urban area, and suburban area.

- improve trip distribution model using the HTS information. - Update VOT and VOC to present time. - improve feedback loop by using average trips per day in

calculation and assigned up to 4 loops. - improve the use of special generator that is being use in

commercial shopping mall for the analysis of attraction rate. - improve trip distribution by using distribution method of multi

class assignment with equilibrium technique and assign convergence of 20 iterations.

- improve mode split model from MSP to Nested logit model.

TDS 2017 6+2 1,885 2553 18,833 2,582 Nested

Logit Model CUBE

Voyager

Source: compiled by consultants



5-4

5.2 Improvement of study area and sub-area (TAZ)

Develop eBUM model from UTDM project (1995) to TDL project (2011) or about 20 years ago. The study area covers 6 provinces including Bangkok, Nakhon Pathom, Nonthaburi, Pathum Thani, Samut Sakhon and Samutprakarn TDL II (2013) has expanded its coverage in eight provinces by adding Phranakhon Si Ayutthaya Province. And Chachoengsao In order to cover the suburban transport network. Especially the Red Line extension Rangsit - Ban Phich. And Huamark - Chachoengsao Appropriate However, the extension should only be operated by the Metro Corridor and the district of the province adjacent to the original study area.

The TDML subdivision (2008) has 776 subdivisions and is further subdivided. The TDL II (2556) subdivision is divided into 1,771 subdivisions this project has been further refined into 1,885 sub-areas, highlighted in detail in the density areas. Subdivision area by Metro Corridor Provide appropriate size and cover at least one sub-station per station To further improve the accuracy of public transportation in the MRT Corridor, and to consolidate (Group) existing subdivisions of the 3 outer provinces. By reference to the original subdivision of the TDML project.

Province Subdivision

TDL II (2013)

TDS (2017)

Bangkok 727 946

Nakhon Pathom

321 244

Nonthaburi 155 189

Pathum Thani 168 184

Samut Sakhon 115 70

Samut Prakan 148 147

Ayutthaya 40 49

Chachoengsao 74 38

Outer space 23 18

Total 1,771 1,885

กรงเทพมหานคร

นครปฐม

ปทมธาน

นนทบร

พระนครศรอยธยา

สมทรสาครสมทรปราการ

ฉะเชงเทรา

Ayutthaya

Pathum Thani

Samut Prakan

Chachoengsao

Nakhon Pathom

Nonthaburi

Samut Sakhon

Bangkok



5-5

5.3 Economic and Social Update

The socio-economic data was collected from various agencies for use in the eBUM model, consisting of population, number of households, employment (agriculture, industry and the service sector). And number of students the study area consists of 2022 2027 2032 2037 and 2042. Summarize the details of the data collected and the results of the study. Used to improve as shown in the table.

Table 5-2 Economics and social update lists Description Source

Number of population

Census and housing National Statistical Office Register Department of the Interior

Number of households

Census and housing National Statistical Office Register Department of the Interior

Average household income

Report on the distribution of household income.

National Statistical Office

Number of seats Education Information Ministry of Education Number of employed persons

Population aged 15 years and over National Statistical Office

City plan Land Use and Urban Development Bangkok Metropolitan Administration

5.3.1.1 Railway infrastructure development project and large scale development project

The development of the mass transit system on the railroad or metro has resulted in land use and urban development. This is due to the development of the area surrounding the MRT station under the concept of Transit Oriented Development or TOD. For example, the Bangkok Metropolitan Administration 2013 and the town plan include Nonthaburi. Building permit Or develop large projects. The area is within 500 meters from the vicinity of the MRT station. The development of the area around the station is based on the TOD concept, which increases the population and employment in the area. However, the development of the TOD concept can only be applied to potential stations For example, stations with commercial areas and original sources of work. Large government institutions Big school The station is a turning point, such as Laksi Station, Don Mueang Station, Rangsit Station on the Red Line,



5-6

Lad Phrao intersection. Ratchayothin Station Kasetsart University Station On the green line Pakkret Station Bangkok Government Center Station, Pink Line

Large development projects that affect the transformation of the city. Especially the population and employment in various areas. Including public and private projects.

5.3.1.2 Summing up the urban development trend

According to the present land use study, land use in Bangkok is currently commercial land within the ring road 1 (Ratchadapisek Road). Residential areas are concentrated within the ring road 2 (Kanchanapisek Road). Considering the overall area of the project, there has been an expansion of the urban area from Bangkok to the north side which, to Pathum Thani on Phaholyothin Road. The area along Phaholyothin Road from Amphoe Mueang Lamlukka up to Klong Luang. West side the urban area has continued to expand with the area in Mueang Nonthaburi and Mueang Samut Sakhon and to the east. The urban area has continued to grow together with Muang Samutprakarn. In the area of Nakhon Pathom Phra Nakhon Si Ayutthaya and Chachoengsao, the city is located and grow in the Muang (central district).

From the study of land use requirements and the concept for Bangkok and metropolitan area development in 2037, it is found the statement which controls the expansion of the city to avoid urban sprawl and preventive the poach of agricultural areas and drainage routes. For Bangkok, the commercial and residential developments are required to be within the ring road 2 (Kanchanapisek Road). This requirement has resulted in the location of large scale by public and private development projects concentrated within Second Ring Road. However, the extension of the mass transit network outside the Second Ring Road will affect the development in the surrounding area of the stations.



5-7

5.3.2 Population

The consultants have collected census data from the National Statistical Office (NESDB) and the registration information from Department of Internal Affairs Ministry of Interior then compare the population between the census and housing data with the 2010 population register. The consultant then distributed the population to the study area. The distribution of the population was preform accordingly to the proportion of the population in the district / district by adjusting the proportion of population growth in each area. Then adjust the data according to the population growth rate Quote from the register and distribute the sub-district / district population into the TAZ level again from the building utilization database (residential land use and Mixed-used) by pull the data from Department of Land Development.

For projection of population data, the ratio was based on Population Growth Ratio in Sub District / District, which consider suitable for population analysis as a base year 2017. The consultants have considered the improvement of this proportion in addition to the development of key areas. Population projections as shown below.

Population density in 2017 (TAZ) Population density in 2042 (TAZ)

5.3.3 Average household income

The National Statistical Office's Household Income Tax Report from 1998-2015, shows that the metropolitan area carry 3.55% of growth rates per year. The consultants have collected the average household income of each province in the study area, from the 20-year national strategy 2017-2036, which aims to increase per capita income of Thailand, by 2016, per capita to about $ 6,000



5-8

(Approximately 213,000 baht per person) for at least $ 13,000, or about 500,000 baht per year, representing an annual growth rate of 4.2 percent per year compared to 2016.

5.3.4 Number of students

The consultants have collected information on the number of students (number of seats) by class and province, which is published in 2013 and 2015. The information illustrates that Bangkok Nonthaburi and Samutprakarn has experiences an inclination in seats. Bangkok's average seat occupancy rate is 7.35 percent per year, while in Nonthaburi In Samut Prakan, the number of student seats decreased by 6.35% and 0.07%, respectively. However, Chachoengsao, Nakhon Pathom and Pathumthani showed a tendency in increasing their seats. The average occupancy rate is 2.85% per annum, 2.61% per annum and 1.66% per annum respectively. The rate variation among the province causes by the age range of school-age population (6-22 years old) has decreased but overall, the populations data remain stable with slightly drop.

The consultants have projected the number of seats in each province using the assumption is that the rate increases in line with the rate during the year, 2013-2015. It is found that in the year 2017, the number of seats in Bangkok is about 1.796 million seats, while the total number of seats in the study area is approximately. 3.10 million seats.

5.3.5 Number of Employment

The consultants have collected employment data from the National Bureau of Statistics. After the year 2014, the number of employment is quite stable. In anticipation of the number of people employed in the future year. The consultants were analyzed base on the data on the growth rate of the employed population. Estimate number of employed persons as shown below.

Industrial Employment Density, 2017 Industrial Employment Density, 2042



5-9

Employment sector employment density, 2017 Employment sector employment density, 2042

5.3.6 Summary of socio-economic data

Economic and Social Information the eBUM model is comprised of the population, the number of households Number of students (Study Seat), Employment (Agriculture Sector, Industry and the service sector) and the average household income. Table 5-3 shows the list of study areas.

Table 5-3 Economic and social data forecasts

Year population (Millions)

households (Million

households)

Study Seats

(Millions of seats)

Employment (millions) Average household

income (Baht / month)

Agro Industry Services Total

2017 16.430 6.164 3.096 0.287 1.842 8.301 10.430 42,450 2022 17.471 6.856 2.992 0.305 1.961 8.961 11.227 47,200

2027 18.269 7.556 2.894 0.327 2.093 9.688 12.108 52,660 2032 18.774 8.067 2.799 0.350 2.237 10.360 12.947 58,530

2037 19.067 8.467 2.710 0.376 2.389 11.065 13.830 65,000

2042 19.388 8.882 2.624 0.405 2.556 11.832 14.793 72,190



5-10

5.4 Improvement of transportation network

Currently, the Transport Network consists of the Highway Network, the Public Transport Network, the BTS Sky Train and the MRT Mass Transit Network. They are used as an input data in various models during the year for future BTS network. The consultants have assembled a series of routes and station location according to recent study results to increase the model efficiency.

5.5 Improvement of Trip Generation Model

Trip generation model is the dominant model that will be used to forecast traffic volume and transportation network volume. The results of the model give the traffic volume in each sub-area of analysis (Traffic Analysis Zone). The results itself from trip generation model will be used as an important input to the next level of model or another sequence model. The consequence of improper model and its result will caused a number of inaccurate planning and operating in the future.

Improvements to the Trip Generation Model include:

Vehicle segregation and vehicle occupancy distribution.

Household Size Distribution Model

Trip Production Model

Trip Attraction Model

TDL II (2013) has further improved the vehicle acquisition group by separate to people who own 2 cars (2CAR) and more than 2 cars (2CAR +), which reflect more travel behavior. The improvement of the TDS 2017 will be divided into 4 groups, consisting of no cars (OVeh), motorcycles (MC), cars (PC) and cars and motorcycles (Multi)



5-11

5.5.1 Classification of Vehicles

According to the analysis on owned vehicles ratio and the travel behaviors difference from HTS shows that trip selection depends on the type of vehicle. Therefore, TDS 2017 have divided owned vehicles personnel into 4 categories including no vehicle, motorbike owner, car owner, and more than one vehicles in process.

5.5.2 Household Size Distribution (HHSD)

This model is used to predict the distribution of household size (HH Size) in each sub-area to use as input in Trip Production Model. Because the database use in forecasting the future will goes into Aggregate Zonal Levels, which is consist of the number of households and the population of that zone. The model will divide the total number of households in the sub-area into the number of households with different size surveyed in 2017 and Census 2010

5.5.3 Trip Production Model

This model is sub-model that calculates the travel volume of each sub-region. The model catagorized the journey as follows:

1) Home-based Work (HBW) - Traveling Between Workplace and Workplace 2) Home-based Education (HBE) - Homestay 3) Home-based Other (HBO) - Traveling between shelters and other places such as

department stores. 4) Non-home-based (NHB) - Non-residential travel

The structure of the model is in the form of a Cross Classification model. The output as a table shows the trip rates. The 2017 HTS information is organize the travel information by household size; vehicle occupancy and the purpose of travel at the sub-level (Zone level and district level) then calculate trip rate accordingly to each objective. Overall, the rate of travel in this model increased from 1.52 trips / person / day to 1.97 trips / person / day.

Table 5-4 Trip Rate for each objective of the trip Household size No vehicles No vehicle (OVEH) Motorcycle Car Car and Motorcycle

HBW Purpose

1 1.092 1.153 1.214 1.242

2 2.346 2.476 2.607 2.667

3 3.381 3.568 3.756 3.844

4 4.536 4.788 5.040 5.158



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Household size No vehicles No vehicle (OVEH) Motorcycle Car Car and Motorcycle

5 5.670 5.986 6.301 6.447

6+ 6.805 7.183 7.561 7.736

HBE Purposes

1 0.329 0.347 0.365 0.374

2 0.705 0.745 0.784 0.802

3 1.017 1.073 1.130 1.156

4 1.364 1.440 1.516 1.551

5 1.705 1.800 1.895 1.939

6+ 2.046 2.160 2.274 2.327

HBO Purposes

1 0.146 0.154 0.162 0.166

2 0.314 0.331 0.349 0.357

3 0.452 0.477 0.502 0.514

4 0.607 0.640 0.674 0.690

5 0.758 0.801 0.843 0.862

6+ 0.910 0.961 1.011 1.035

NHB Purposes

1 0.115 0.121 0.128 0.131

2 0.247 0.260 0.274 0.280

3 0.355 0.375 0.395 0.404

4 0.477 0.503 0.530 0.542

5 0.596 0.629 0.662 0.678

Source: Consultant

However, the above trip rate is the average derives from the study area. In the implementation, there will be adjustments in areas such as inner cities (CBD), urban areas (Urban) and suburban areas (Sub Urban).

5.5.4 Trip Attraction Model

This is a sub-model that calculates the amount of travel into each area. The Trip Attraction Model is in the form of linear regression.

Aj = a1+b1x1+b2x2+………bnxn

By

Aj = Trip Attraction at zone j

X1-n = Variable Number of Employment Primary Secondary Tertiary Student Commercial



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a1, b1-n = Constants and coefficients of variables.

Previous models have used the Special Generator for the malls. Moreover, it is directly using the travel that connects to external areas such as bus stations, railway stations and airports, traffic volume and daily passenger volume in consideration without Mode Split considered. Also, these trips are not occur during AM Peak. The consultant is considered to improve the trip model and the attraction model by add the commercial area instead of the special generator for the best suits and accuracy of the model input. Trip attractions rate As shown in Table 5-.

Table 5-5 Travel attractiveness

Travel Rate OVEH MC PC MULTI

HBW

Primary Travel / People 0.172 0.193 0.347 0.227

Secondary Travel / People 0.246 0.276 0.495 0.324

Tertiary Travel / People 0.319 0.359 0.644 0.422

HBE SCHOOL Travel / People 0.341 0.387 0.703 0.454

HBO Tertiary Travel / People 0.052 0.058 0.128 0.083

Comercial Travel / Square Meters 0.018 0.018 0.034 0.030

NHB Tertiary Travel / People 0.032 0.067 0.090 0.062

Comercial Travel / Square Meters 0.018 0.018 0.034 0.030 Source: Consultant

5.6 Improvement of Trip Distribution Model

After have the analysis of the travel volume to and from such an area done by take the relationship between travel volume and socio-economic data of each area in consideration. The results will be distributed to each sub-area by using a travel distribution model called "Gravity Model"

The study area is divided into 24 groups; the most proportion is the one that travel in and out Bangkok area with 54.2%. The three highest groups which travel to Bangkok are, Samutprakan province. 2.4% in Nonthaburi Province 2.1% and Pathum Thani Province This is 0.7%.



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5.7 Model Split Model Improvement

Based on the review of the structure of the model, the UTDM (1995) model, is Binary Logit Model TDMC II (2009) is likely a Nested Logit Model and TDL II (2013), is likely a Multinomial Logit Model. According to the literature review shows that the Nested Logit Model is more accurate than the Multinomial Logit Model.

In order to be consistent with the current travel behavior and current mode of travel, and to improve the model, the consultants will analyze the model of travel choice in the form of Nested logit model or Hierarchical Logit model as a Logit model, which is used for modeling the selection of travel patterns. The factors influencing the choice of travel options were determined by a hierarchical selection hierarchy to examine the choice of travel patterns of the target population. Target groups are divided into two groups: Private Transports and Public Transports, as shown in Figure 5-2.

Bangkok

Pathum Thani

Samut Prakan

Chachoengsao

Ayutthaya

NakhonPathom Nonthaburi

Samut Sakhon

In area . %

In area 4.2%

In area 5.1%

In area 4.8%

In area 2.2%

In area .4%

In area 7.3%In area 7.7%

0.1%2.

4%



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Figure 5-2 Model structure of the project selection model

5.8 Improving Trip Assignment Model

1) Improve VOC and VOT costs

The consultants have reviewed the Vehicle Operating Cost (VOC) which is the consumer perceive, the Value of Time (VOT) and used in the estimation of generalize travel cost in travel distribution. The forecast of fuel price will be increased accordingly per the increasing rate of people income with 4.7 percent not including the inflation of 2.5 percent, where it is increased average roughly 2.2 percent per year as shown in the table.

VOC and VOT cost tables (2018) Table 5-8

Vehicle type

Vehicle Operating Cost (VOC) VOT

(Baht/Hr/Person) 3) Petroleum

(Baht/liter) 1)

Petroleum Rate

(KM./liter)2) Baht/km./Car

Personal car (PC) 28 10.0 2. 0 140.7

Motorcycle (MC) 28 25.5 1.10 .4 Note: 1) Fuel average prices every type within 2017 2) TDS (2017) Emission Inventory of On-Road Transport in Bangkok Metropolitan Region (BMR), Development during 2007 to 2015 using the

GAINs Model, 2017 3) Survey results of HTS project

2) Congestion Loop and how to enumerate the journey

Loop is to adjust the time and travel expenses (Generalize Cost) Due to TDL II traffic conditions (2013), traffic conditions have been used during rush hours results in higher

Travel modes

Private transports Public transports

Private Car(PC)

Private Motorcycle

(MC)

High Performance Transit (HPT)

Medium Performance Transit (MPT)

Low Performance Transit (LPT)

Paratransit (PRT)

BTS MRTA Etc. ACBus

Public van Ordinary bus

VesselsRail

Etc. Etc. Hired-motorcycle

Taxi Tuk-tuk Etc.ARLBRT



5-16

price for inbound direction. It is considered to use the traffic conditions in average for the whole day in a loop and have decided to assign atleast 4 times for equilibrium model.

The TDL II (2013) use the Multi class Assignment method with the Incremental Loading technique, which breaks down the travel schedule. In this study, the consultant will improve the technique. Equilibrium (EQU) considers the equilibrium of travel as a whole and is assigned to be 20 Iteration.

5.9 Model Calibration

The consultants have calibrated the model and keep up to date by comparing the data obtained from the eBUM model with data from the survey and compilation.

1) Traffic volume monitoring along the screen line (2 lines) which is along the Chao Phraya River, doing so is to check the travel volume in east-west direction. For along the main and secondary roads (Crossing the canal) is performing in order to check the north-south direction travel volume. Refer to TDL II (2013) as well as traffic volume in Ratchada and Cordon External Zone.

2) The current users of mass transit green line, blue lines and airport rail link.

The information will be reviewed by the consultants to collect the statistics of each relevant agency, such as Bangkok Expressway, Department of Highways, BTS, MRTA and their related studies.

Table 5-6 Calculation of passenger volume

Mass Transit Line Passenger volume of 2017

(People - trips / day) Difference

(%) Survey Model

Green line Commemoration of HM the King's 6th Cycle Birthday Anniversary

740,000 745,000 0.7

Blue line Chaloem Ratchamongkhon Line 333,000 353,000 6.0

ARL Metro connects Suvarnabhumi Airport 69,000 80,000 15.9

Purple line Commemoration of HM the King's 6th Cycle Birthday Anniversary

51,700 56,000 8.3

Total 1,186,887 1,234,000 3.4 Note: average passenger volume per working day, 2017



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Table 5-7 Calculation of average traffic volume in Expressway system

Expressway Traffic volume (PCU / day) Difference

(%) Survey Model

The Chalerm Mahanakorn Expressway 385,888 395,900 2.6

Si Rat Expressway (Second Stage Expressway System)

720,051 717,600 -0.3

The Chalong Rat Expressway (Ramindra-Narong Expressway)

220,023 228,500 3.9

Burapha Withi Expressway (Bangna-Chonburi Expressway)

144,044 141,500 -1.8

Udon Ratthaya Expressway (Bang Pa-in - Pak Kret Expressway)

84,312 78,800 -6.5

Kanchanapisek Expressway (Bang Phli - Suksawat Expressway)

264,051 267,600 1.3

Si Rat - Outer Ring Road Expressway 56,306 58,800 4.4

Total 1,874,675 1,888,700 0.7

HBW, 19.59 HBE, 5.43

HBO, 4.29

NHB, 3.38

travel capacity 2017 (million trips/day)



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5.10 The analysis and development of the forecast model.

The development of model mentioned above will be given the appropriate model to use for

2017 (based year), 2022, 2027, 2032, 2037 and 2042. The information include in the model are socio

economic and the future projects. The information is collected from relevant authorities, which are

Department of Highway, Department of Rural Highway, Expressway Authority of Thailand, BMA, State

Railway of Thailand and Mass Rapid Transit Authority of Thailand.

Car [PERCENTAGE]

Motorbike [PERCENTAGE]

Taxi [PERCENTAGE]

public transport [PERCENTAGE]

pick up car [PERCENTAGE]

walk [PERCENTAGE]

Travel Ratio 2017

1.23

7.767 0.623

0.069

0.135

0 1 2 3 4 5 6 7 8

รถไฟฟา

รถโดยสาร

รถต

รถไฟชานเมอง

เรอโดยสาร

passeners capacity (million-trip/day)

Water

taxi

Train

Van

Bus

MRT/BTS



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Table 5-8 number of passengers using public transport

รปแบบ Number of passengers(million-trip/day)

2560 2565 2570 2575 2580 2585 BTS/MRT 1.234 3.429 4.150 4.612 4.794 5.267

Boat Transport 0.135 0.093 0.076 0.076 0.082 0.087 Bus Transport 7.767 7.839 8.843 8.852 9.336 10.435

Urban Train 0.069 0.040 0.048 0.046 0.048 0.051 Van 0.623 0.143 0.190 0.202 0.213 0.252

Total 9.828 11.544 13.307 13.788 14.473 16.092

source from (eBUM)

car

motorbike

Taxi

public transport

pick up car walk

0

5

10

15

20

25

30

35

40

2560 2565 2570 2575 2580 2585

num

ber o

f trip

(mill

ion/

day)



5-20

0.00

1.00

2.00

3.00

4.00

5.00

6.00

2560 (109 km) 2565 (303 km) 2570 (496 km) 2575 (530 km) 2580 (530 km) 2585 (530 km)

num

ber o

f pas

seng

ers (

mill

ion

trips

/day

)

BTS/MRT passengers according to M-Map

0.002.004.006.008.00

10.0012.0014.0016.0018.0020.00

2560 2565 2570 2575 2580 2585

aver

age

spee

d (k

m/h

r.)

years

inner area average speed

เรงดวนเชา เรงดวนเยน

0.002.004.006.008.00

10.0012.0014.0016.0018.0020.0022.0024.0026.00

2560 2565 2570 2575 2580 2585

aver

age

spee

d (k

m./h

r.)

years

Greater Bangkok average speed เรงดวนเชา เรงดวนเยน AM Peak PM Peak

AM Peak PM Peak



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5.11 Implementation of eBUM

An extended Bangkok Urban Model: eBUM modified version proceeded under TDS 2017

project will be applied to two application, which are consists;

1) Test Mass Transit Policy Development The objective is to see the effect of the policy among the transit fare against mass transit ridership within

Bangkok and its vicinity. Consider cases are both with and without transfer fee being collected in the system. There are 3 providers of mass transit, consist of Bangkok Metropolitan Administration, Mass Rapid Transit Authority of Thailand and State Railway of Thailand who set up the fare structure (Boarding and Distance) accordingly to their assumption. The average between the fare of Bangkok Metropolitan Administration, Mass Rapid Transit Authority of Thailand is 13.2+2.5 baht/km. and 13.5+1.0 baht/km. There will be a charged (Boarding fee) if the user transfer to a station which operate by different provider. The analysis shows in 2042 base year with transfer fee being collected, there are 5.3 million person-trip/day but for without fee being collected scenario, the ridership increases up to 5.66 million person-trip/day or 400,000 person-trip/day about 7.4%. Clearly be seen that without transfer fee being collected will able to maximize the ridership to the system. The relevant authorities should consider promoting policy relating to the transit fare reduction, and especially the common ticketing system to leverage the ridership of mass transit system, which will alleviate traffic congestion in Bangkok and its vicinity.

2) Determination and evaluation of Traffic Congestion Cost. The objective to test the traffic impact per the TDM project’s aim and evaluate the time lost that could be

alleviate within Bangkok and its vicinity. Base year scenario, per the implementation of relate project, such as the development of Chao Praya River

crossing bridge create severe traffic congestion within the inner part of Bangkok. The average speed within 2022 is projected about 10.19 km/hr then decrease to 9.05 and 8.21 km/hr in 2032 and 2042, respectively. If there is measure stated to increase the average speed up, says, inner part of Bangkok 15 km/hr and middle / outer part of Bangkok is 20 km/hr, it will save the private car user from 67,000 million baht/year to 117,000 and 322,000 million baht/year in 2032 and 2042. The result shows high number of saving. The relevant authorities should promote TDM strategies to the area that have enough public transit system such as common ticketing system policy, limit private car access in some area and road pricing.



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6. National model development and its application

6.1 Improvement and model structure design & development

National model (NAM) consists of 2 sub models, Passenger model and Freight model. Passenger model is model which contains 4 continuous procedures which are Trip generation model, Trip distribution model, Modal split model and Trip assignment model.

Freight model is also multi-procedure continuous model. For example, Production model, Mode distribution model, Logistics node model, Fine distribution and vehicle model by using Cube Cargo application.

In this study, both Passenger model and Freight model structures have been improved and developed as following criteria:

Improvement and National model (NAM) structure design & development Passenger Model - Improve Modal split model

- Add analysis of travel demand for travelers (Travel trips)

- Add analysis of increasing travel amount (Induced Trips) from high speed train project development

- Add analysis of Eastern Economic Corridor (EEC) development

Freight Model - Improve parameter in Transport logistics node model

- Add analysis of Eastern Economic Corridor (EEC) development

6.1.1 Social economic information improvement

For model development in this project, forecast of 2 main parameters, population information and gross product information, has been reconsidered and improved. Primarily, population data back in past 10 years during 2007-2016 from civil registration data of Department of Provincial Administration, Ministry of Inferior show that domestic population grew up by 0.5 percent per year (unit : thousand people)



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Region and

Province 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Northeastern

region 21,386 21,443 21,496 21,573 21,586 21,697 21,775 21,845 21,916 21,945

Northern region 11,872 11,879 11,770 11,788 11,783 11,803 11,826 11,847 12,072 12,079

Southern region 8,655 8,742 8,814 8,893 8,972 9,060 9,131 9,209 9,291 9,341

Eastern region 4,443 4,510 4,558 4,616 4,664 4,721 4,773 4,832 4,903 4,952

Central region 6,618 6,656 6,650 6,682 6,695 6,720 6,741 6,767 6,838 6,849

Bangkok and

extended urban 10,065 10,162 10,237 10,326 10,377 10,456 10,539 10,625 10,708 10,765

Thailand in

total 63,038 63,390 63,525 63,878 64,076 64,457 64,786 65,125 65,729 65,932

6.1.2 Population forecast improvement

In population forecast improvement for National model, 3 sources of information will be used: (1) Civil registration data from Department of Provincial Administration, Ministry of Inferior (2) Population and housing census data from National Statistical Office (3) Data from Thailand population forecast report for 2010-2040 by Office of the National Economic and Social Development Board (NESDB)

Region

Census Civil Registration

Difference Census/Registration

Ratio Pop 2553 (x1,000)

Growth/year Pop 2553 (x1,000)

Growth/year

Northeastern region 18,966 -0.931% 21,573 0.261% 13.75% 0.879

Northern region 11,656 0.193% 11,788 0.165% 1.14% 0.989

Southern region 8,871 0.929% 8,893 0.855% 0.25% 0.997

Eastern region 5,175 2.530% 4,616 1.235% -10.82% 1.121

Central region 6,687 0.470% 6,682 0.407% -0.08% 1.001

Bangkok and extended

urban 14,626 3.712% 10,326 0.930% -29.40% 1.416

Thailand in total 65,982 0.802% 63,878 0.517% -3.19% 1.033



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6.1.3 Gross product information forecast improvement

Based on collected gross product value data statistic, linear trend line is able to use for estimating data of each year in the past quite well (i.e. R2 is high) among level of gross domestic product, regional and provincial product. Therefore, linear trend based on historical statistics has been used for gross product information forecast for National model (NAM).

6.1.4 Transportation network improvement

Transport network improvement is for passenger transport and all modes of freight transport, including updating all types of transportation service. Transport network consists of roads network, railways network, waterways network and airways network.



6-4

Future roads network improvement for model development. Consultant has gathered information of future roads construction and expansion projects operated by both The Department of Highways and Expressway Authority of Thailand: 21 projects operated by The Department of Highways and 7 projects operated Expressway Authority of Thailand.

Future railways network improvement for model development. Consultant has gathered information of future double-track construction projects operated by State Railway of Thailand: 12 projects are double-track railways and 6 projects are standard gauge double-track railways.

Current waterways network is divided into inland waterway transportation and coastal waterway transportation. Inland waterway transportation has 2 routes, which are (1) Domestic freight transport route via Chao Phraya river (year-round traffic), Pa Sak river, Bang Prakong river, Mae Klong river and Tha Chin river, (2) International freight transport route via sea and MeKong river among Quadrangle Economic Cooperation (China, Myanmar, Thailand, Laos). For coastal waterway transportation, mostly origin or destination lies in coasts of central region, eastern region and southern gulf of Thailand region.

For airways network in the model, Consultant has gathered airports in Thailand information which is air transportation information from departments such as Airports of Thailand Public Company Limited, Department of Airports and The Civil Aviation Authority of Thailand. There are 34 airports in Thailand.

6.2 Data survey for national transport model and traffic model (NAM)

Data survey for National transport model and traffic model (NAM) will be obtained by using Screen Line Count Method. In order to deter-mine survey point, imaginary line will be drawn across important highways where traffic count is more than 5,000 vehicles per day.

Consultant has drawn 6 screen lines covering each region in Thailand resulting in 16 survey points: northern region line (SL1) 4 points, northeastern region line (SL2) 4 points, central region line (SL3) 2 points, eastern region line (SL4) 2 points, upper southern region line (SL5) 1 point and lower southern region line (SL6) 3 points. The survey result of traffic count and roadside interview is as illustrated.



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When considering passenger occupancy obtained from survey result of both large public bus and small public bus, we found that 50 percent of northern region small bus carries full passenger capacity, following by lower southern region, 40 percent. For northeastern re-gion, 70 percent of small bus carries approximately half passenger capacity. Meanwhile in upper southern region, 60 percent of small bus carries almost full passenger capacity.

6.3 Analysis and development of future years

The analysis and forecast of transportation demands in the future consists of year 2017 (base year), 2022, 2027, 2032, 2037, and 2042. The forecast reflects the accurate and reliably transportation behavior and is within the allowable in revision of the model. The analysis results are divided into 2 sections: analysis of the base year model and analysis of future year’s model.

6.3.1 Analysis of base year model

After calibrating the model, it was found that the tolerance value of traffic volume between the survey data and the results of all model was 4.89, which is acceptable. The analysis of the base year model consists of the freight volume forecast in 2017 for 18 types of freights (including domestically and internationally transported freights). The freight volume is 854 million tons/year. The proportion of transportation type in 2017 and the forecast of passengers in 2017 are as below.



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6-7

Group Freight types Transportation volume

(tons/year)

1 Vegetable Products 98,235,922

2 Live Animals & Animal Products 6,738,605

3 Foodstuffs 55,983,267

4 Textiles 2,739,763

5 Raw Hides, Skins, Leather, & Furs 573,417

6 Wood & Wood Products 7,743,768

7 Pulp & Paper 8,160,426

8 Mineral Products 133,766,576

9 Chemicals & Allied Industries 35,888,003

10 Plastics & Rubber 26,833,707

11 Stone / Ceramic Products / Glass 8,509,169

12 Pearl and Precious Stones 625,456

13 Base Metals 32,112,099

14 Machinery & Mechanical Appliances / Electrical Equipment 5,925,761

15 Transportation 8,315,308

16 Miscellaneous 148,898

17 Domestically transported freight (Group B) 377,237,019

18 Internationally transported freight (Group C) 137,038

Total 809,674,202

Source: Data from the national transport model and traffic model (NAM)

Mode of transportation 2017

Transportation volume (tons/year)

Domestic transportation (million tons-km /year)

Average distance (km)

Road 709,027,881 131,170 185.00

Rail 10,162,498 2,044 201.11

Water 90,428,938 15,834 175.10

Air 54,886 35 629.50

Average of all modes 809,674,202 149,082 184.13




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6.3.2 Analysis of future year’s model

Analysis of future year’s model consist of the years 2022, 2027, 2032, 2037, and 2042. The model can analyze the changing transportation behavior and the results can be used for planning national transportation system planning in the future. The freight transportation forecast result of future years consists of the proportion of freight transportation sorted by mode of transportation in the future and the forecast of travelers sorted by mode of transportation in the future.

Transportation of travelers sorted by mode of transportation (1000 people-trip/day) Mode of transportation 2017 2022 2027 2032 2037 2042

Passenger’s car 1,535 1,883 2,243 2,607 2,985 3,410

Bus 1,004 1,175 1,390 1,606 1,832 2,084

Railway 109 178 212 245 281 320

Air 83 102 121 140 160 182

Total 2,731 3,338 3,966 4,598 5,258 5,996


Regarding the analysis and development of the future year’s transportation model mentioned above, the Consultant will add the transportation and traffic system development for future years project or the test scenario. Also, the socio-economic growth rate will be adjusted based on the socio-economic condition of the current year with reference to updated data from Office of the National Economic and Social Development Board and National Statistical Office.

Year Million vehicles-km. Million vehicles –hr. Speed (km/hr)

2017 277.282 3.466 79.993

2022 326.879 4.182 78.161

2027 295.918 3.735 79.220

2032 428.820 5.750 74.572

2037 485.283 6.680 72.652

2042 547.795 7.735 70.819

Source: Data from the national transport model and traffic model (NAM) Remark : Veh-Kms : vehicle x transportation distance Veh-Hrs : vehicle x transportation time



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Freight transportation volume from the national

transport model and traffic model (NAM) (tons/year)

2017 2022 2027 2032 2037 2042

Road 709,027,881 752,418,766 788,702,188 808,873,179 831,015,037 852,955,532

Railway 10,162,498 31,119,109 40,624,127 48,912,897 53,448,909 58,169,673

Water 90,428,938 100,439,931 106,534,708 110,725,376 115,001,908 119,472,564

Air 54,886 60,614 61,917 63,220 64,523 65,826

Total 809,674,202 884,038,420 935,922,939 968,574,672 999,530,376 1,030,663,594


6.4 Model Application of National Model

National model under travel demand survey; TDS project will be applied 3 topics consist of

1) Transport Performance Index; TPI of Infrastructure testing

Thailand is required to have performance indicators for transport and traffic that are appropriate to the environment. To enhance the efficiency of transportation and traffic of the country. The OTP has developed a transport and traffic information database that is important for the development of the Transport Performance Index: TPI to assess the competitiveness of the country systematically and effectively. The database contains 44 indicators, divided into 4 groups.

- Group 1: Supply/Availability/Capacity amount 13 indicators

- Group 2: Quality of Service amount 16 indicators

- Group 3: Utilization amount 9 indicators

- Group 4: Safety amount 6 indicators The data for analysis is derived from data collection from various agencies. The Ministry of

Transport and other ministries. Some import data from the survey. And some of the traffic and transportation models, such as proportion of travel and transportation. In this study. Review some indicators analysis by applying the national traffic and transportation model (NAM) to the infrastructure test to calculate the indicators to assess the competitiveness of the country.

Found that, the project was completed according to the master plan for the development of the railway network. It will help to transport the railways, which are economical. The master plan (20 years) all three phases will increase access to the system, the railway network will cross 62



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provinces of the country from 47 provinces with the network doubling from 4,043 km to 8,852 km. In terms of efficiency, the 1-meter network will provide faster and more punctual service. And with increased capacity. As a result, there will be a doubling in the network to 88% from the current 7%. For network performance testing using a national model. When the couple develops in accordance with the twin rail development plan. Currently, two new routes are planned, namely Ban Phai - Nakhon Phanom and Denchai - Chiang Khong. The development of the planned projects has resulted in a change in the usage patterns of the rail system from 1.1 percent. 3.5% in 2022, resulting in an increase in mobility on the road network as compared to no project development.

2) Induced Trips from High Speed Rail The government currently offers 4 high speed rail projects, namely Bangkok - Phitsanulok.

Bangkok - Nakhon Ratchasima Bangkok - Hua Hin Bangkok - Rayong for the application of the National Model for the analysis of passenger volume for 4 high-speed rail routes, the increase was made possible by the development of high-speed train systems: Induced Trips. This is because the original national model did not calculate the amount of travel in this section. High-speed trains are also expected to be discouraged. Therefore, the application of the national model that adds Induced Trips due to the development of high-speed rail system will make the forecasts more accurate.

Hence, the model has been improved. Special Trips Generators are specially developed in Thailand for high speed trains in Thailand. By the National Science and Technology Development Agency, more on the national model. Special trips generators are in the form of Multiple Regression.

The analysis found that, high speed train case the traffic volume will be classified according to the change pattern by changing to the train mode increase. This information can be used for future policy planning. The data can be used to analyze the feasibility of the project in engineering, economics, finance, investment, environmental benefits and so on.



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3) Testing of the Transportation Roadmap for the Development of the Eastern Economic Corridor (EEC)

This National Model testing is an analysis of the impact on the transport network has been projected of EEC. For testing the results of the development of the transport project, which to support the development of the Eastern Economic Corridor (EEC), and the last is to propose an additional project to support the development of the Eastern Economic Corridor (EEC). Hence, when the area is developed in all aspects. As a result, the region will be the center of investment and tourism in the world. The development has a direct impact on transport. Infrastructure projects involving the transport sector, including road, rail and water transport.

The analysis and estimation of traffic volume using the national model showed that the formation of EEC resulted in an increase in traffic volume. This resulted in a denser road network and lower average network traffic. Due to increasing population and economic activity. Increasing travel both in the area and travel between areas. Especially between EEC area and Bangkok metropolis. After 2575, the average network speed dropped by more than 10 percent. Therefore, it is necessary to prepare measures and plans to develop infrastructure to support such large infrastructure development projects at U-Tapao International Airport. Interstate Highway High-speed train project connecting 3 airports in accordance with the plans of EEC’s plan. As well as the improvement of the internal network including highways, rural roads and major access roads such as U-Tapao international airport. Laemchabang Port Map Ta Phut Port passenger terminal high speed train station Industrial estates the downtown area. economic area tourist area and new cities will be developed according to the EEC policy.



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7. Developing an In-Depth Activity-Based Travel Behavior Model.

Developing the In-Depth Activity-Based Travel Behavior Model in order to advance the Activity-Based Travel Demand Model is a Pilot study for improving method, analyzing and anticipating People in Bangkok Metropolitan Region travel demand and simulate travel behavior that is the most consistent with travel fact in daily life. Yet, Amphoe Mueang, Nonthaburi Province is determined as a case study since it has high potential of travel and city activity relation. It also offers Activity-Based Travel within its area and related area with essential peripheral area.

7.1 The development of Activity-Based Travel Demand Model.

The development of Travel Demand Model for analyzing and anticipating travel volume at the present and in the future can be divided in 2 levels which are extended Bangkok Urban Model (eBUM) and National Model (NAM). These model considerations are based on original and destination point or quantities of trip for examining Trip-Based Model with an initial hypothesis of each traveler has one destination for that trip. However, the result shows that the hypothesis is not consistent with the travel fact that happens in daily life and it doesn’t reflect daily life travel fact of those travelers. Thus, another anticipation method of travel demand or Activity-Based Travel Demand Model is devised in order to minimize those mentioned limitations. This model studies the activities that occurs in each trip while they’re travelling instead of analyzing the purpose of the main destination of that trip. The elements of activity model consist of these following sub-elements:

1) Pattern Type Model

Pattern Type Model is travel choice model. For instances, the purpose of main

destination, travel time duration, quantities of sub-traveling or activity, etc.

2) Location Choice Model

Location Choice Model is a model of travel from home or back home option. It may be a starting point from a place that they stop by or the last stop of their main destination such as workplace, school or department stores.



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3) Mode Choice Model

Mode Choice Model is a model that used for making decision determining individual’s travel pattern and it is based on each utility of travel pattern option.

4) Assignment Model

This model is about route choice which is the same pattern as 4 Steps Model that is generally analyzed.

7.2 Traffic Survey and Home Interview.

The development of Activity-Based Travel Demand Model in this study offer a process that involve in 2 parts of data exploration which are Midblock Count Survey and Home Interview Survey according to these following process details:

7.2.1 Midblock Count Survey

Midblock Count Survey is designed for investigating the basic parameter of traffic on the main route network in its studied area. Then, it is applied to the travel demand model in Trip Assignment analysis process.

Table 7-1 Midblock Count Survey

Survey point

Highway Number Direction Passenger Car Unit

(PCU) AM PM

MB1 Nonthaburi 3021

(Ratchaphruek Road) Go to Chaiyaphruek Road 11,160 19,360

Go to Rattanathibet Road 16,549 14,654

MB2 Highway 306

(Tiwanon Road) Go to Samakkhi Road 5,154 8,799

Go to Chaiyaphruek Road 7,204 5,922

MB3 Highway 302

(Rattanathibet Road) Go to Bang Kruai - Sai Noi Road 7,499 19,827

Go to Ratchaphruek Road 15,164 12,543

MB4 Highway 302

(Rattanathibet Road) Go to Ratchaphruek Road 8,497 15,994

Go to Nonthaburi Road 16,342 11,141

MB5 Highway 302

(Rattanathibet Road) Go to Khae Rai Intersection 8,167 12,235

Go to Pracha Chuen Road 16,648 10,580

MB6 Nonthaburi 3021

(Ratchaphruek Road) Go to Ratchaphruek Circle 13,213 23,355

Go to Bang Kruai - Sai Noi Road 15,094 13,598



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Survey point

Highway Number Direction Passenger Car Unit

(PCU) AM PM

MB7 Nonthaburi 1020 (Nakhon In Road)

Go to Ratchaphruek Circle 7,372 8,548


MB8 Nonthaburi 1020 (Nakhon In

Road) Go to Pibulsonggram Road 7,650 13,317


MB9 Highway 306 (Pibulsonggram

Road) Go to Wong Sawang Road 7,232 12,412

Go to Nakhon In Road 8,475 6,881

Note : AM is 6.00-9.00 and PM is 16.00-19.00.

7.2.2 Home Interview Survey

Home Interview Survey relies on interviewing by survey at Amphoe Mueang, Nonthaburi Province. The studied area is separated into 50 areas. The number of household is determined by Confidence level at 95% and Error at 10% in statistics base on Nonthaburi population in Amphoe Mueang Nonthaburi which is 363,112. Thus, necessary samples are at least 400 samples explained in divided areas

To develop the Activity-Based Travel, it is divided by the activity that is the reason behind travel which are the main activity and the secondary activity or the activity that occurs during the trip including the trip that happens during the day in order to do new activity when travelers finally arrive main activity destination. Then, the data analysis result of samples primary trip will be presented by Travel Pattern of the activity that has been done from Monday to Friday including weekend.



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Figure 7-1 Travel Pattern (Monday- Friday)



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Figure 7-2 Travel Pattern (weekend)



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7.3 Model Development

The anticipation of travel demand in 2017 (base year) and in 2042 consists of morning rush hour (AM) during 6.01 AM-9.00 PM, non-rush hour (MD) during 9.01 AM-4.00 PM, evening (PM) rush hour during 4.00 PM-7.00 PM. and non-rush hour (OP) during 7.01 PM-6.00 AM. including a total distance of people who use those routes in vehicle-kilometers of travel (VKT), a total of time spent from those who take the routes in vehicle hours of travel (VHT) and Travel Speed. The result of prediction will reflect individual Activity-Based travel behavior for each time duration in a certain area and it is similar to the actual behavior which related to activity-choice and each family information. This model is suitable for applying and analyzing traffic-related policy. For instances, traffic network analysis of urban planning for province, traffic analysis for each time duration and area group for developing Activity-Based Model which affect traffic condition.

morning rush hour (AM) during 6.01 AM-9.00 PM non-rush hour (MD) during 9.01 AM-4.00 PM

evening (PM) rush hour during 4.00 PM-7.00 PM non-rush hour (OP) during 7.01 PM-6.00 AM

Figure 7-3 Travel Demand in 2017



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morning rush hour (AM) during 6.01 AM-9.00 PM non-rush hour (MD) during 9.01 AM-4.00 PM

evening (PM) rush hour during 4.00 PM-7.00 PM non-rush hour (OP) during 7.01 PM-6.00 AM

Figure 7-4 Travel Demand in 2042

Table 7-2 Result of the anticipation from Activity-Based Model in Amphoe Mueang, Nonthaburi Province.

Year

Time Duration

AM MD PM OP

VKT VHT SPEED VKT VHT SPEED VKT VHT SPEED VKT VHT SPEED

2017 540,808 21,772 24.8 510,286 16,808 30.4 517,670 18,736 27.3 49,924 979 51.0

2022 596,877 27,324 21.8 563,459 21,279 26.5 571,985 23,635 24.2 55,038 1,096 50.2

2027 658,731 35,436 18.6 620,857 26,957 23.0 630,562 30,673 20.6 60,391 1,232 49.0

2032 721,649 44,230 16.3 684,265 34,833 19.6 675,441 37,873 17.8 64,953 1,345 48.3

2037 768,197 50,789 15.1 722,406 40,810 17.7 730,630 44,354 16.5 69,774 1,497 46.6

2042 809,507 62,209 13.0 758,891 47,804 15.9 769,134 53,757 14.3 73,278 1,603 45.7

Note : 1. Time duration analysis are AM 6.00-9.00, MD 9.00-16.00, PM 16.00-19.00 and OP 19.00-06.00 respectively. 2. VKT measurement: car-Km/hour, VHT : Car-hour/hour and Speed : Km/Hour



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Table 7-3 Result from eBum in Amphoe Mueang, Nonthaburi Province.

Year

Time Duration

AM PM

VKT VHT SPEED VKT VHT SPEED

2017 418,313 19,843 21.08 392,611 16,542 23.73

2022 464,454 26,140 17.77 439,632 23,146 18.99

2027 475,551 27,433 17.33 466,504 24,694 18.89

2032 506,028 34,419 14.70 498,728 30,349 16.43

2037 535,033 42,643 12.55 529,789 38,148 13.89

2042 553,507 47,670 11.61 556,372 45,669 12.18

However, the Activity-Based Model help us understand more about travel behavior, compared to the original model, and be able to better analyze this model reaction and its effect on traffic. This project model examination will indicate empirical result of data and travel behavior in studied area by using detailed travel information. If the Activity-Based Model is developed compared to the original model of extended Bangkok Urban Model (eBUM), the transportation planner and experts in related fields will use this correct and proper model for analyzing the next project.

The advantage of building Activity-Based Model is activity participation behavior analysis in all day or

longer which will be able to study the policy that related to Travel Demand Management (TDM) more

effectively since it will study how an individual can change one’s own activity participation in order to

response to such policy. For example, one will change certain outdoor activity time with indoor

activity in the evening due to arriving home early and work time is changed.



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8. Network Improvement Using Geographic Information System (GIS) and Executive Information System

8.1 Integrated Design and Development of Transport and Service Networks Using GIS

The integrated design and the development of transport & service networks using GIS aims to upgrade transport & service network systems regarding travel volume as well as goods transport routes and amount. The data will be presented in the GIS format, emphasizing the accessibility of users through compatible and suitable user interfaces.

8.1.1 Geographic Information System (GIS) Design and Development

In designing and developing the GIS, the consultant will apply the guideline from the GIS Development Guides of the Local Government Technology Services, State of New York. The guideline is shown in Figure 8.1.

Source: Adapted from the Local Government Technology Services, State of New York

Figure 8.1 GIS Design and Development Guideline Chart



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8.1.2 Transport and Traffic GIS Data List

The consultant had summarized and classified the data presented in the transport and traffic GIS into three groups, as shown in Table 8.1.

Table 8.1 Recommended Transport and Traffic GIS Data

Key data No. Data lists Sources Year of data

1. Goods transport route data

Goods transport route data

1 Goods transport routes OTP 2017

NAM data

1 Zone OTP 2017

2 Travel demand OTP 2017

3 Goods transport demand OTP 2017

4 Goods transport volume OTP 2017

5 Travel volume OTP 2017

6 Goods transport routes OTP 2017

2. BKK and perimeter areal data

1 Sub-district administrative boundary MOT 2016

2 District administrative boundary MOT 2016

3 Land use LDD 2016

4 Vehicle registration statistics DLT 2017

5 Bus routes MOT 2016

Electric train route data

1 MRT routes MOT 2016

2 BTS routes MOT 2016

3 APL routes MOT 2016

4 MRT passenger volume BMCL 2017

5 Vehicles volume on expressway EXAT 2016

6 Traffic and transport project plans OTP 2017

7 Expressway routeห MOT 2016

eBUM data

1 Zone OTP 2017

2 Travel volume OTP 2017



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Key data No. Data lists Sources Year of data

3 Vehicles volume on expressway OTP 2017

4 Electric train passenger volume OTP 2017

3. Fundamental data 1 District administrative boundary MOT 2016

2 Provincial administrative boundary MOT 2016

3 Main roads MOT 2016

4 Railway crossing MOT 2016

5 Railways MOT 2016

6 Waterway and water resources MOT 2016

Office data 1 Customhouse MOT 2016

2 Provincial Land Transport Office MOT 2016

3 Marine Office MOT 2016

8.1.3 Transport and Traffic GIS Model of the Project

The consultant studied and developed the system to improve the presentation of the OTP’s transport and traffic GIS data, enabling it to show the map to users more interactively . The consultant will add more features such as display the overall image, distance and area measuring tools, map printing, show specific data of routes or networks and google street view (URL http://gistran.otp.go.th/gis/) to the system on top of the exis ting features which are zoom in, zoom out and pan, to be beneficial to the analysis or display of data for further study .



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Source: The consultant

Figure 8.2 GIS Model of the Project

8.1.4 Transport and Traffic GIS Application

The transport and traffic GIS can be applied to many usages, particularly to analyze different transport and traffic information together for understanding a big picture trend. For example, analyzing the goods transport and road network to show the readiness of network to serve key goods transport for planning and developing the transport network or determining potential locations for collecting and distributing goods to promote the potential of future business operators.

Moreover, GIS is also beneficial to all interested parties. For instance, promoting public transport by publicizing rail network and bus route information to passengers so that they know about their travel options using multi-modal transport types.

8.2 Preparation of Executive Information System (EIS)

The analysis and preparation of EIS is the process of applying the computer system to the transport and traffic management plan and decision. EIS will be useful for planning transport systems of the country and can be applied by agencies across the country to their development projects using the same transport and traffic database, resulting in less operation redundancy and investment efficiency of the government.



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1) Support strategic plans: To develop EIS, developers have to understand OTP’s strategic plans very well in order to apply the information technology efficiently.

2) Focus external environment: Since information is always a vital factor for management to make a decision, good EIS has to be designed to access the OTP database easily and fully connected with external organization data for effective decision making.

3) Have broad-based computing capabilities: The majority of decision makers usually scope out a big picture, so the information for management must be simple, clear, concrete and not complicated such as graphs or charts.

4) Emphasize exceptional ease of learning and use: EIS development must have user friendly interface and encourage interactive between users and software such as charts and fast response.

8.2.1 Transport and Traffic GIS Data List

The consultant had classified the data presented in the transport and traffic GIS into six groups, as shown in Table 8.2.

Table 8.2 Transport and Traffic GIS Data List

Key data No. Data lists Sources MIS

1. Socio-

economic

conditions

1 Number of population NSO Linked Website, Graph (editable)

2 Employment data NSO Linked Website, Graph (editable)

3 Average household income NSO Linked Website, Graph (editable)

4 Gross Domestic Product (GDP) NESDB Linked Website, Graph (editable)

5 Gross Regional Product (GRP) NESDB Linked Website, Graph (editable)

6 Gross provincial Product (GPP) NESDB Linked Website, Graph (editable)

7 Accommodation for tourist overnight stay TAT Linked Website

8 Foreign tourists to Thailand TAT Linked Website

9 Vehicle registration (new) DLT Linked Website, Graph (editable)



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10 Vehicle registration (accumulative) DLT Linked Website, Graph (editable)

11 Vehicle registration (accumulative) classified by fuel

categories

DLT Link Website

12 Aircraft registration CAAT Linked Website, Graph (editable)

13 Fuel use (economic sector) DEDE Link Website

14 Fuel use (travel and transport sector) DEDE Link Website

15 Thailand’s import goods MOC Linked Website, Graph (editable)

16 Thailand’s export goods MOC Linked Website, Graph (editable)

17 Import volume (classified by transport type) MOT Linked Website, Graph (editable)

18 Export volume (classified by transport type) MOT Linked Website, Graph (editable)

19 Import value (classified by transport type) MOT Linked Website, Graph (editable)

20 Export value (classified by transport type) MOT Linked Website, Graph (editable)

21 Domestic land transport volume (classified by goods

type)

MOT Linked Website, Graph (editable)

22 Domestic rail transport volume (classified by goods

type)


23 Domestic water transport volume (classified by goods

type)


24 Domestic air transport volume (classified by airport) MOT Linked Website, Graph (editable)

2. Transport

and traffic

25 General expressway information EXAT Linked Website, infographic (Picture)

26 Railway routes and stations SRT Linked Website, infographic (Picture)



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infrastructure 27 BTS routes and stations BTS Linked Website, infographic (Picture)

28 MRT routes and stations BMCL Linked Website, infographic (Picture)

29 ARL routes and stations (including existing extension

sections) SRT

Linked Website, infographic (Picture)

30 BRT routes and stations BMA Linked Website, infographic (Picture)

31 Double-track railway routes SRT Linked Website, infographic (Picture)

32 HSR routes SRT Linked Website, infographic (Picture)

33 General information of land transport stations DLT Linked Website, infographic (Picture)

34 General information of airports DOA/AOT Linked Website, infographic (Picture)

35 Road distance OTP Linked Website, infographic (Picture)

36 Rail distance OTP Linked Website, infographic (Picture)

3. Travel &

transport

characteristics

37 Traffic volume at survey sites

Traffic and

Transportation

Department

Graph (editable), infographic

(Picture)

38 Speed at survey sites

Traffic and

Transportation

Department

Graph (editable), infographic

(Picture)

39 Home interview OTP Graph (editable), infographic

(Picture)

40 Interview at survey sites OTP Graph (editable), infographic

(Picture)

41 Car speed on main roads OTP Graph (editable), infographic

(Picture)



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42 Passenger count (public transport system) OTP Graph (editable)

43 BTS passenger volume BTS Linked Website, Graph (editable)

44 MRT passenger volume BMCL Linked Website, Graph (editable)

45 ARL passenger volume SRT Linked Website, Graph (editable)

46 BMTA passenger volume DLT / BMTA Graph (editable)

47 Intercity bus passenger volume DLT / BMTA Graph (editable)

48 Railway passenger volume (city-intercity) SRT Graph (editable)

49 Van passenger volume in city DLT /BMTA Graph (editable)

50 BRT passenger volume BMA Graph (editable)

51 Air transport passenger volume (domestic-

international) AOT

Graph (editable)

52 Air transport passenger volume (domestic-

international) DOA

Graph (editable)

53 Water transport passenger Marine

Department

Link Website, Graph (editable)

54 Surveyed goods OTP Graph (editable)

55 Goods transport volume (rail transport) SRT Graph (editable)

56 Goods transport volume (water transport) Marine

Department

Graph (editable)

57 Goods transport volume (air transport) DOA/AOT Graph (editable)

58 Goods transport volume (road transport) DLT/MOT Graph (editable)



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4. Results of

transport and

traffic analysis

59 NAM of travel demand OTP Excel, Graph (editable)

60 NAM of goods transport demand OTP Excel, Graph (editable)

61 NAM of travel volume OTP Excel, Graph (editable)

62 NAM of travel proportion OTP Excel, Graph (editable)

63 NAM of goods transport volume OTP Excel, Graph (editable)

64 NAM of goods transport proportion OTP Excel, Graph (editable)

65 NAM of traffic volume on main roads OTP Excel, Graph (editable)

66 eBUM of travel demand OTP Excel, Graph (editable)

67 eBUM of travel volume OTP Excel, Graph (editable)

68 eBUM of traffic volume on expressway OTP Excel, Graph (editable)

69 eBUM of passenger volume OTP Excel, Graph (editable)

70 eBUM of travel proportion OTP Excel, Graph (editable)

71 Vehicle operating cost (VOC) OTP Excel, Graph (editable)

72 Value of time (VOT) OTP Excel, Graph (editable)

73 eBUM of average speed (by area) OTP Excel, Graph (editable)

74 eBUM of air pollution of Bangkok and perimeter OTP Excel, Graph (editable)

5. Data on

security, public

hazard and

environment

75 Accident fatalities (transport sector) MOT Linked Website, infographic

(Picture)

76 Accidents on main roads MOT Linked Website, infographic

(Picture)



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77 Land accident Royal Thai Police Linked Website, infographic

(Picture)

78 Land accident statistics (by accident causes) Royal Thai Police Linked Website, infographic

(Picture)

79 Release of hot-air balloon OTP Linked file (data sample),

infographic (picture)

80 Air pollution PCD Linked Website

81 Noise pollution PCD Linked Website

6. ITS

technology

development

82 Master plan and pilot project for ITS development OTP Linked file, infographic (picture)

83 Study reports of OTP’s projects OTP OTP’s Linked Website

(www.otp.go.th)

Source: The consultant

8.2.2 Executive Information System Data List

The consultant had classified the data presented in the executive information system into four groups, as shown in Table 8.3

Table 8.3 Executive Information System Data List

Key data No. Data List EIS

1. Socio-economic conditions

1 Thailand’s import goods Graph

2 Thailand’s export goods Graph

3 Import volume (classified by transport type) Graph

4 Export volume (classified by transport type) Graph

5 Import value (classified by transport type) Graph

6 Export value (classified by transport type) Graph

7 Domestic air transport volume (classified by airport) Graph

2. Travel & Transport Characteristic

8 Home interview Graph

9 Car speed on main roads Graph



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Key data No. Data List EIS

10 Passenger count (public transport system) Graph

11 BTS passenger volume Graph

12 MRT passenger volume Graph

13 ARL passenger volume Graph

14 BMTA passenger volume Graph

15 Goods transport volume (water transport) Graph

16 Goods transport volume (road transport) Graph

3. Results of transport and traffic analysis

17 NAM of goods transport volume Graph

18 eBUM of travel demand Graph

19 eBUM of travel volume Graph

20 eBUM of traffic volume on expressway Graph

21 eBUM of passenger volume Graph

22 eBUM of travel proportion Graph

23 Vehicle operating cost (VOC) Graph

24 eBUM of average speed (by area) Graph

4. TS technology development

25 Master plan and pilot project for ITS development Link file

26 Study reports of OTP’s projects Link Website สนข.(www.otp.go.th)

8.2.3 Executive Information System

Management information system (MIS)

The management information system (MIS) of transportation and traffic is presented in Excel table. It is also collected and summarized into infographics which can be easily learned and used. For example, shown in graphics, pictures, clear words and fast respond (http://mistran.otp.go.th/MIS) as shown in Figure 8.3



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Figure 8-3 Transport and Traffic GIS Data

Executive Information System (EIS)

Executive Information System (EIS) focuses on the information that is beneficial to project manager’s decisions. It focuses on providing the information needed in planning and making decisions about transportation and traffic, such as traffic volume data on major roads, passenger volume of the MRT system, data from the project model, etc. All data is summarized in the f orm of infographic in a way that is easy to understand and not too complicated (URL http://eis.otp.go.th/EISWeb) as shown in Figure 8-4

Figure 8-4 Executive Information System (EIS)



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8.2.5 Transport and Traffic Information System Application

The application of transport and traffic information system consists of two parts: MIS and EIS. MIS will be beneficial for collecting statistics and database from related organizations. The consultant has created the database which is easily editable and consistent with related organizations, so the staff can update data annually. EIS is the selected important information from MIS data presented to executives in the easily understood form. It is suitable for determining policies and further publicity.



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9. Public Consultation, Technical Training and Project Public Relations

Public consultation and technical training focuses on receiving comments and transferring knowledge regarding the travel demand survey, transport and traffic model development as well as that related to the project study, to the Office of Transport and Traffic Policy and Planning (OTP) and relevant agencies in order to enhance the knowledge, create understanding and develop practical skills and potential of relevant officers.

9.1 Summary of 1st Public Consultation

The first public consultation was held on 1st September 2017 at Jubilee Ballroom, Berkeley Hotel Pratunam Bangkok. There are 150 attendees from organizations: agencies involving in transport planning, state enterprises corresponding to transport infrastructure development, private sector related to transport work and educational institutes and academics associated with transport field of work. The consultant presented and explained the background of project, the necessity, guidelines and procedures of the project study as well as obtained opinions and suggestions to improve the project completeness.

Figure 9-1 Atmosphere of 1st Public Consultation



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Suggestions

1 The project should focus on developing model rather than surveying data and updating database.

2 The consultant should collect samples comprehensively, accordingly and sufficiently for the usage in the future.

3 The consultant should add the result of eBUM forecast and compare it with that of the base year.

4 The project should offer online channel for travel demand survey via internet as additional alternative.

5 The consultant should collect and find information from post offices and FedEx as present goods behavior is changed.

6 The committee would like to see the forecast of car use; a variable indicating the increasing figures of car each year, which is an important factor for policy makers.

9.2 Public Consultation with Model Users (Government Agencies)

The consultant organized the public consultation with model users -- the government

agencies -- in order to develop and modernize eBUM and NAM models, integrate them into the

transport masterplan of the country and use them among government agencies. The list of target

organizations are as follows:

Departments Date

1. Mass Rapid Transit Authority of Thailand 8 November 2017 2. Expressway Authority of Thailand 15 November 2017

3. Department of Highways 24 November 2017 4. Department of Land Transport 24 November 2017

5. Department of Rural Roads 29 November 2017



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Figure 9-2 Atmosphere of Public Consultation with Five Government Agencies

Suggestions

1 The committee agreed to set a survey standard and prepare user’s handbook and survey manual.

2 The model development should provide the details since how to input data, in order to create understanding and accurate practical application.

3 eBUM and NAM model database should be available to all related organizations. 4 Each skytrain project should have central database for detailed data collection and

forecast in each area.

9.3 Focus Group Meeting

The focus group meeting was held on 28th December 2017 at Noppawong Ballroom 1, The Twin Tower Hotel, Bangkok. There are 36 attendees from organizations: agencies involving in transport planning, state enterprises corresponding to transport infrastructure development, private sector related to transport work and educational institutes and academics associated with transport field of work. The topics of the meeting are, “Travel Demand Survey and eBUM Model” and “National



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Logistic Database Improvement and NAM Model”, including obtaining opinions and suggestions about eBUM and NAM models improvement from the attendees.

Figure 9-3 Atmosphere of Focus Group Meeting

Suggestions 1 The consultant should consider the survey and travel periods.

2 The consultant should consider the actual public transport cost to further analyze economic benefits and nonregistered population which affects the model result.

3 The consultant should consider to collect data at office and school zones as well. 4 The study report might have some errors in transport distances, time duration, average

transport costs data.

9.4 Meeting with Academics for Model Development Suggestions

The consultant organized the meeting with academics for model development purpose, the meeting was held on 22nd March 2018. There are six academics from leading universities of the country join the meeting.



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Figure 9.4 Atmosphere of Meeting with Academics for Model Development Suggestions

Academics Name List

Name University Assoc. Prof. Dr. Somphong Sirisophonsin Chulalongkorn University

Assoc. Prof. Dr. Kasem Chucharusakun Chulalongkorn University Assoc. Prof. Dr. Thoedsak Rongwiriyaphanit King Mongkut’s University of Technology North

Bangkok Assoc. Prof. Dr. Sitha Chensirisak Ubon Ratchathani University

Dr. Suthiphong Miyai Suranaree University of Technology Dr. Theeraphot Siriphairot Srinakharinwirot University



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Suggestions

1 The model with too-complicated zone dividing will lead to problem of inadequate data for processing. The model processing should not take too long time as developers need time to recheck.

2 Some information in the report such as travel cost, speed and time should be presented in transportation mode between areas in order to have clearer overview.

3 As the travel rate will be different based on the employment or activity types, is the travel rate categorized by the employment or activity types? The model should be separated into two scenarios increasing and decreasing travel rate.

4 The O-D should be adjusted according to monthly traffic count in order to monitor monthly traffic data.

5 The survey data might not cover all areas and O-D so, the consultant should weight the data in the questionnaire according to present available data, such as traffic volume at screen line and passenger volume, so that the surveyed data well represents the population.

6 The consultant classifies main mode from the longest route and choose to apply the traditional travel mode, which are HBW HBE HBO. However, travel behavior of Thai people has been related to several modes of travel these days and multi-modal transport becomes more familiar with Thai people, so the trip chaining method might be more suitable at present.

7 The next study should add Transport Land Use Model in TOR because when the rail routes are fully operated, O-D will be changed. Additionally, the present model takes too long time to process data, so it should be adjusted.

9.5 Summary of 2nd Public Consultation

The second public consultation was held on 23rd April 2018 at Watergate Ballroom C, Amari Watergate Hotel Bangkok. There are 128 attendees from: agencies involving in transport planning, state enterprises corresponding to transport infrastructure development, private sector related to transport work and educational institutes and academia associated with transport field of work. This seminar focuses on feature development of both eBUM and NAM models, including activities-based study to identify target groups and receiving suggestions to improve the project completeness.



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Figure 9-5 Atmosphere of 2nd Public Consultation

Suggestions

1 The consultants should consider the statistical possibility in the past and check with the department who provide it.

2 The consultants should provide additional data in MIS for the future use. 3 The freight transport should be linked to the transportation route, which will benefit the

development of the freight transport modelling. 4 The consultants should note cautions in model parameter adjustment.

5 The consultants should do a validity check on presented average travel expenses. 6 What is the application of eBUM on Bangkok road project including priorities of the project,

cost effectiveness? Some projects have been design for many years.

9.6 Technical Workshop and Technology Transfer

For the implementation of academic training, the consultant will train the staff of the Office

of Transport and Traffic Policy and Planning (OTP) and other relevant agencies, including government

agencies and state enterprises involved in transport planning and infrastructure transport & traffic



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development, for six courses. The purpose of the courses is to transfer the knowledge of transport

model application (eBUM and NAM) and other knowledge on TDS project to the staff.

Table 9-1 Technical Workshop and Technology Transfer

No. Courses

Number of

attendees

Hours Date Lecturers

According to TOR (2 courses)

1 Introduction to Transport Modeling

Survey

Data analysis

4-Step model

42 8 24 Apirl 2017 Dr. Surasak Taweesin Asst. Prof. Surames Piriyawat

2 Model Practice

Zone/ Node & Link Network

35 8 25 Apirl 2017 Dr. Siradol Siridhara Mr. Boonchuay Thongkam

Additional courses (4 courses) 3 Software cube 1 5 8 7 August 2017 Citilabs team 4 Software cube 2 3 16 8-9 August 2017 Citilabs team 5 eBUM (Survey+Model)

5.1 Overview of eBUM 5.2 eBUM Details 5.3 eBUM Application

8 8 8

3 3 3

5 February 2017 13 February 2017 26 February 2017

Mr. Jatupol Rakdee Mr. Jatupol Rakdee Mr. Jatupol Rakdee

6 NAM (Survey+Model) 6.1 A Survey of Travel Behavior and Movement of Goods 6.2 NAM Details 6.3 NAM Application

6 8 8

3 3 3

26 February 2017 27 February 2017 28 February 2017

Mr. Boonchuay Thongkam Mr. Boonchuay Thongkam Mr. Boonchuay Thongkam Mr. Anuchit Phanchana



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Chairperson delivers an opening speech workshop introduction speech

lecture on project overview lecture on project overview

registration atmosphere in the workshop class

photo of attendee sharing opinion photo of attendee sharing opinion Figure 9.1-1 Atmosphere of Technical Workshop and Technology Transfer

(Introduction to Transport Modeling)



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lecture on project overview lecture on project overview

registration atmosphere in the workshop class

photo of attendee sharing opinion photo of attendee sharing opinion Figure 9.6–2 Atmosphere of Technical Workshop and Technology Transfer

(Modeling Practice)



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9.7 Project Public Relations

Project public relations aim at creating perception and accurate understanding of the project and listening to ideas and comments from the attendees and interested people. The media and tools used in the project public relations are as follows:

9.7.1 Social Network (Facebook)

The consultant had published and presented the project information through social network – Facebook -- because it can be accessed easily and is a suitable channel to reach target groups and create the project understanding. It is also convenient for current target groups (Facebook URL: https://www.facebook.com/traveldemandsurveyOTP). The Facebook aims at advertising project activities, data and tips to the interested people.

Figure 9.6–3 Atmosphere of Technical Workshop and Technology Transfer

(4 Additional Courses)



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Figure 9-7 Project’s Social Network (Facebook)

9.7.2 Project Website

The consultant had created project website to present the project study result and details to stakeholders and interested people. The entire project information and the project ongoing progress can be searched and monitored via https://www.tdsotp.com.

Figure 9-8 Project’s Website

9.7.3 PR Media in Seminar

Project public relations aim at creating perception and accurate understanding of the project and listening to ideas and comments from the attendees and interested people. The media and tools used in the project public relations are as follows:

https://www.tdsotp.com/



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Table 9-2 PR Media / Tools Used in Meetings

Media/Tools Meetings

1st public consultation Focus group 2nd public consultation Project PR leaflets 3-folded leaflets (A4

size), 120 copies 3-folded leaflets (A4

size), 50 copies 3-folded leaflets (A4

size), 200 copies Supporting documents 120 copies 50 copies 150 copies

Exhibition boards 4 Roll- up boards, 0.8x1.8 m in size

2 Roll- up boards, 0.8x1.8 m in size

5 Roll- up boards, 0.8x1.8 m in size

Information boards 1 roll-up board, 4.14x2.30 m in size

- -

Videos 3-min length - 5-min length

Figure 9-9 Project PR Leaflets of 1st Public Consultation



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Figure 9-10 Supporting Documents of 1st Public Consultation



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Figure 9-11 Exhibition and Information Boards of 1st Public Consultation

Figure 9-12 Video Presentation of 1st Public Consultation



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Figure 9-13 Project PR Leaflets of Focus Group Meeting



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Figure 9-14 Supporting Documents of Focus Group Meeting

Figure 9-15 Exhibition Boards of Focus Group Meetings



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Figure 9-16 Project PR Leaflets of 2nd Public Consultation



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Figure 9-17 Supporting Documents of 2nd Public Consultation

Figure 9-18 Exhibition and Information Boards of 2nd Public Consultation



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Figure 9-19 Video Presentation of 2nd Public Consultation

TDS Exsum-EN 03.Content Final 20180404 · 2018-05-15 · 2-1 2.1 Review transportation and traffic...

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