Mascot Town Centre Precinct TMAP - City of Botany Bay · Mascot Town Centre Precinct TMAP Appendix...

Mascot Town Centre Precinct TMAP

Appendix A

APPENDIX A

Working Paper 1# Strategic Modelling Calibration Report

Strategic Model Development & Calibration Report (Rev A)

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MASCOT TMAP

Strategic Model Development &

Calibration Report

Rev No.

Date Prepared by Reviewed by

A 5/09/11 M Stephens C Wiafe

Contact for further information:

Matthew Stephens NSW Traffic & Transport Planning Manager

(02) 9925 5542 0414 236 130

[email protected]

© Snowy Mountains Engineering Corporation (SMEC Australia Pty Ltd)

The information within this document produced by SMEC Australia is solely for the use of the Client identified on the cover sheet for the purpose for which it has been prepared. SMEC Australia undertakes no duty to or accepts any responsibility to any third party who may rely upon this document. All rights reserved. No section or element of this document may be removed from this document, reproduced, electronically stored or transmitted in any form without the written permission of SMEC Australia.


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TABLE OF CONTENTS

1 INTRODUCTION .............................................1

2 TRINITY MODEL INPUTS ...........................2

3 TRAVEL PATTERNS .....................................7

4 MASCOT SUB-AREA MODEL ............... 10

APPENDIX ‘A’ TRINITY Model Calibration

APPENDIX ‘B’ Sub-Area Model Network

APPENDIX ‘C’ 2011 AM & PM Peak Link Flow Plots

APPENDIX ‘D’ 2011 AM & PM Peak Network LOS

APPENDIX ‘E’ Sub-Area Model Calibration


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1 INTRODUCTION

Background This working paper documents the development and calibration of 2011 AM and PM peak period strategic models for the Mascot Town Centre Precinct.

This work forms part of a broader TMAP modelling process as outlined in Figure 1. This working paper covers the modelling steps contained within the dotted box.

These base-case models will be used to assess the strategic traffic impacts of future land use and transport scenarios being developed as part of a Transport Management and Accessibility Plan (TMAP) for the precinct.

The Mascot TMAP strategic transport models were built using TransCAD software and were derived from a calibrated transport model of Sydney, Newcastle and Wollongong, developed by SMEC, named TRINITY.

The 2011 base-case models have been calibrated to reflect the land use, road network and traffic demands present in July/August 2011.

The calibrated models will be used to forecast 2021 and 2031 traffic growth, with and without the proposed redevelopment in the Mascot Town Centre precinct.

CALIBRATED TRINITY MODEL

(2011, 2021, 2031)

UPDATE MASCOT LAND USE AND RERUN TRINITY

(AM, PM)

CREATE MASCOT SUB-AREA MODEL & REFINE ZONES(2011 AM, PM)

RUN MASCOT SUB-AREA MODEL

(2011, 2021, 2031)

EXTRACT BASE TRIP MATRICES FOR PARAMICS

MODELS(2011, 2021, 2031)

RUN AND ANALYSE

DEVELOPMENT SCENARIOS

(2011, 2021, 2031)

CALIBRATE 2011 BASE MODELS

CODE UP2011 PARAMICS

BASE MODELS

IDENITFY LAND USE

ASSUMPTIONS

DEVELOP PARAMICS MODEL

OF PREFERRED TMAP

DEVELOPMENT SCENARIOS

CALIBRATE SUB-AREA MODEL

(2011 AM, PM)

CONSTRAINTS AND

OPPORTUNITIES

REVISE LAND USE, MODE SHARE AND

NETWORK OPTIONS

COLLECT TRAFFIC, SPEED

AND ROAD INVENTORY DATA

Figure 1: TMAP Modelling Methodology


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2 TRINITY MODEL INPUTS

Background The regional travel patterns contained within the Mascot TMAP models were derived from SMEC’s TRINITY Transport Model (TRINITY).

TRINITY is a strategic transport model of the Sydney, Newcastle and Wollongong metropolitan areas. It is a series of geospatial information layers, databases and spreadsheets embedded within a transport modelling software package. These elements combined create a mathematical representation of land use and travel patterns in the Sydney Greater Metropolitan Area (GMA).

TRINITY is a software tool for forecasting traffic growth and planning of Sydney’s future road infrastructure needs. It is unique in its socio-economic approach to travel demand, its geographic scope and the number (21) of trip purposes (work, shopping, recreational etc) it models.

TRINITY covers an area of 2.5 million hectares and contains 21,000km of road network and 20,500 intersections.

Modelling Overview The TRINITY model relies heavily on sound transport engineering practices.

The trip patterns that make up the engine room for TRINITY were developed from first principles using a well documented and established 3-step modelling process that includes:

Trip Generation

Trip Distribution

Trip Assignment

It is the first two steps in this process that have the biggest impact on model accuracy.

Trip Generation In the trip generation phase, TRINITY predicts the number of trips originating from or destined to a particular geographic area (or travel zone). In Sydney there are over 2,690 travel zones ranging in size from 0.4Ha (a city block) to over 120,000Ha (Hawkesbury region).

Trip generation mainly focuses on households. The total trips produced or attracted by a household are a function of the social and economic attributes of that household.

SMEC undertook cross classification analysis of data from BTS’s 170,000 Household Travel Surveys (HTS) collected across the Sydney GMA. The analysis identified average trip rates for 100 possible trip

purposes divided into 6 household income categories. The 20 most influential trip purposes are used in TRINITY.

The cross- classification method is widely used in transport planning. A 2007 survey of over 220 US Metropolitan Planning Organisations (MPOs) revealed that over 89% use this method for development of trip generation rates.

Trip Distribution In trip distribution TRINITY matches trip makers’ origins and destinations to develop an origin and destination matrix (or Trip Table) that displays the number of trips going from each origin to each destination. Historically, this component has been the least developed component of transport planning models.

BTSHome Travel Survey Data

Flat File

Category Analysis

• Income Categories

• Trip Rates per Income Category

• Trip Length by Purpose

• Trip Purpose by Time of Day

ABSSocio

Economic (HH Income)

ABSPopulation

DataHousehold

Data

Trip Generation

Rates (6 x 20=120)

ZonalProductions &

Attractions

Trip Zone to ZoneDistribution

(Gravity Model)

Traffic Assignment & Model Calibration

1

2

3

Figure 2: The 3-Step Modelling Process


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Trip distribution in TRINITY is based on the ‘Gravity’ model concept. As the name implies, this model adapts the gravitational concept, as advanced by Newton in 1686, to the problem of distributing traffic throughout an urban area.

The gravity model is one of the most widely used formulae in transportation planning, mainly because it is simple in concept and because it has been well documented. In essence, the gravity model says that trip interchange between zones is directly proportional to the relative attraction of each of the zones and inversely proportional to some function of the spatial separation between zones. This function of spatial separation adjusts the relative attraction of each zone for the ability, desire, or necessity of the trip maker to overcome the spatial separation involved.

TRINITY was calibrated for each trip purpose by comparing surveyed trip length profiles with the modelled profiles until we achieved a satisfactory match. For example average trip lengths for shopping trips (11 minutes) are significantly lower than for work trips (27minutes).

The gravity model responds by limiting the distribution of shopping trips to predominantly local shopping destinations (within 11 minutes travel time) but permits distribution of work trips to a wider range of possible work destinations.

The TRINITY model incorporates the following innovations designed to refine the trip distribution process:

K-factors

Public transport accessibility factors

K-Factors

K-factors are a specific zone-to-zone adjustment factor for work trips which incorporates travel patterns not otherwise accounted for in the gravity model.

Our review of household travel survey data identified distinct socio-economic relationships between employment and income category e.g. people in high income households tend to work in high paying white collar industries.

ORIGINZONE

IC6Households

(White Collar)

IC1Households(Blue Collar)

Primary Industry/

Manufacturing

Office

Figure 3: The K-Factor Concept

The K-factor:

reduces the ‘attractiveness’ of Office jobs to low income category work trips

reduces the ‘attractiveness’ of primary industry jobs to high income category work trips

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

IC1 IC2 IC3 IC4 IC5 IC6

Primary Industry

Manufacturing

Office

Health

Recreation

Construction

Figure 4: Socio-economic Relationship between

Employment & Household Income Category (IC1 to IC61)

Public Transport Accessibility

The second innovation was the introduction of origin (O-car) and destination (D-car) public transport accessibility factors.

Whilst the earlier trip generation process develops 120 generic trip production profiles (6x 20 = 120), these profiles do not reflect the accessibility of public transport alternatives unique to each travel zone.

To address this issue, TRINITY factors the generic production and attraction profiles up or down based on the individual mode share profiles for each travel zone.

In essence, TRINITY generates close to 320,000 unique trip profiles (6 x 20 x 2,690 = 322,800).

These factors simulate the impacts of public transport and parking accessibility on car trip productions and attractions in each travel zone. For example, the D-car factor reduces the attractiveness of the Sydney CBD as a destination for car trips to reflect the excellent accessibility of public transport services and poor availability of car-parking.

1 IC1 represents an annual household income less than $25,000. IC6 represents an annual household income more than $150,000.


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Data Inputs TRINITY incorporates the latest land use and travel data sets available. Key inputs include:

2006 Census data

170,000 Home Travel Surveys (HTS) collected by the Bureau of Transport Statistics (BTS)

NSW Roads & Traffic Authority (RTA) road networks and traffic counts

BTS Freight Matrices

Calibration The calibration (accuracy) of transport models such as TRINITY is determined by comparing observed (counted) traffic volumes with modelled traffic volumes.

TRINITY has been vigorously calibrated and validated against the data from more than 440 RTA traffic count sites spread throughout the Sydney road network.

TRINITY has also been calibrated along the major RTA screen-lines. Screen-lines were established by the RTA for modeling calibration purposes. They are used to ensure that the models accurately replicate the movement of vehicles along natural corridors within the network. A plot of the RTA screen-line locations is provided below in Figure 5.

TRINITY meets or exceeds the minimum calibration targets required by the RTA.

Figure 5: RTA Screen-line Locations

The RTA has generally adopted the UK’s DMRB2 standards for model calibration. These rely heavily on a measure called the GEH statistic. The GEH statistic is a self-scaling empirical statistic with similarities to a chi-squared test. The desired target is to achieve a GEH value less than 5.0 at more than 85% of sites.

Because the GEH statistic is self-scaling, a single acceptance threshold based on GEH can be used over a fairly wide range of traffic volumes.

The formula for the "GEH Statistic" is shown below:

Where ‘M’ is the hourly traffic volume from the traffic model and ‘C’ is the real-world hourly traffic count.

Using the GEH Statistic avoids some difficulties that occur when using simple percentages to compare two sets of volumes.

For traffic calibration of the base year modelling the following is important:

GEH of less than 5.0 is considered a good match between the modelled and observed hourly volumes. When 85% of the volumes on screen lines in a traffic model have a GEH less than 5.0 model one could assume that the model is sufficiently calibrated.

If GEH values in the range of 5.0 to 10.0 are dominant this may warrant detail investigation.

If the proportion of GEH greater than 10.0 is significant, there is a high probability that there is a problem with either the travel demand model or the data (this could something as simple as a data entry error, or as complicated as a serious model calibration problem)

2 Design Manual for Roads & Bridges, Volume 12, Section 2, Traffic Appraisal Advice, May 1996


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Calibration Results In the 2006 AM peak, TRINITY has achieved the following excellent calibration results:

89% of sites achieved a GEH statistic less than 5.0

100% of major bridge crossings (for example, Sydney Harbour Bridge, Sydney Harbour Tunnel, Gladesville Bridge) achieved a GEH statistic less than 5.0

90% of sites on the major RTA screen-lines achieved a GEH statistic less than 5.0

In the 2006 PM peak, TRINITY has achieved the following excellent calibration results:

95% of sites achieved a GEH statistic less than 5.0

100% of major bridge crossings achieved a GEH statistic less than 5.0

94% of sites on the major RTA screen-lines achieved a GEH statistic less than 5.0.

The model matrices were also calibrated against household travel survey trip length data.

A scatter plot analysis of the modelled results for the major RTA screen-lines was undertaken to demonstrate the goodness of fit (R2) of the modelled results compared to the observed. These scatter plots are presented in Figures 6 to 9 below.

Table 1: 2006 AM Peak (7am to 9am) Calibration at All Count Sites

Road Type Total GEH Value

0-5 5-7.5 7.5-10 > 10

Freeway 39 27 5 2 5

Ramps 9 9 0 0 0

Main Roads (Arterial) 202 181 15 4 2

Secondary Roads (Sub-Arterial)

173 162 8 2 1

Secondary Roads (Collector)

18 15 1 2 0

Local Roads 2 2 0 0 0

TOTAL 443 396 29 10 8

100% 89% 7% 2% 2%

Table 2: 2006 PM Peak (3pm to 6pm) Calibration at All Count Sites

Road Type Total GEH Value

0-5 5-7.5 7.5-10 > 10

Freeway 39 32 4 2 1

Ramps 9 9 0 0 0

Main Roads (Arterial) 202 193 5 1 3

Secondary Roads (Sub-Arterial)

173 165 7 1 0

Secondary Roads (Collector)

18 18 0 0 0

Local Roads 2 2 0 0 0

TOTAL 443 419 16 4 4

100% 95% 3% 1% 1%


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y = 1.0042x + 21.855R² = 0.9997

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60 70

ModelledVolumes(000's)

ObservedVolumes

(000's)

Figure 6: Comparison of Observed versus Modelled screen-line flows during AM Peak (Link Direction A-B3)

y = 1.0121x + 113.89R² = 0.9997

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60 70


ObservedVolumes

(000's)

Figure 7: Comparison of Observed versus Modelled screen-line flows during AM Peak (Link Direction B-A)

3 In TransCAD each link is defined by two nodes (A and B). Each link also has two possible flow directions. The direction of flows on each link is defined by the two nodes, Node A to Node B (A-B) and the reverse movement Node B to Node A (B-A).

y = 1.0069x + 5.5267R² = 0.9998

0

20

40

60

80

100

0 20 40 60 80 100


ObservedVolumes

(000's)

Figure 8: Comparison of Observed versus Modelled screen-line flows during PM Peak (Link Direction A-B)

y = 0.9952x + 169.92R² = 0.9997

0

20

40

60

80

100

120

0 20 40 60 80 100 120


ObservedVolumes(000's)

Figure 9: Comparison of Observed versus Modelled screen-line flows during PM Peak (Link Direction B-A)


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3 TRAVEL PATTERNS

The NSW Government’s HTS provides travel information for households surveyed across the Sydney GMA. These surveys tell us when, how, why and where the people in the surveyed households travelled on the day of the survey.

A major benefit of TRINITY’s first-principles approach to trip table development is access to a wealth of land use and travel pattern data relevant to TMAP development, including:

Socio Economics of households in the region

Mode share travel patterns

Trip Purposes

Trip Direction

The following sections summarise some this data for the Botany Bay LGA.

Socio- Economics Our analysis of HTS data for the Sydney GMA indicated that the number of trips generated by each household is closely related to the income of that household.

Households with an income less than $25,000 per annum generate less than 5.8 trips per day. Conversely, households with an income in excess of $150,000 generate more than 14.9 trips per day.

Household income is, therefore, a major trip production variable. A comparison of the income distribution for the Mascot Town Centre precinct (Travel Zones 404 and 406), Botany Bay LGA and the Sydney GMA is provided in Table 3.

The analysis reveals that:

Botany Bay LGA has a higher proportion of households in the lower income categories than the Sydney Average

Conversely, TZ404, which covers most of the Mascot Town Centre precinct, has a higher proportion of households in the higher income categories

Table 3: Proportion of Households in Each Income Category (ABS, 2006)

HH Income Categories (000's)

TZ404 TZ406Botany Bay LGA

Sydney GMA

<$25 9% 14% 14% 11%$25 to $50 16% 21% 22% 19%$50 to $75 22% 24% 21% 23%$75 to $100 20% 19% 18% 19%$100 to $150 21% 14% 17% 17%>$150 13% 8% 8% 10%

Source: HTS, 2006

Mode Share The mode share patterns for Botany Bay LGA are presented in Tables 4 to 6.

These patterns are derived from analysis of 2006 HTS data and are for all trip purposes. They have been broken down into outbound, inbound and internal trip purposes.

Table 4: Botany Bay LGA Mode Share for All AM (2-hr) Peak Trip Purposes

Outbound Internal Inbound

PT 19% 7% 7%Car 77% 51% 92%Bicycle 0% 2% 0%Walk 3% 38% 1%Other 1% 2% 0%Totals % 100% 100% 100%Totals Trips 14910 6410 21990

Trip TypeMode

Source: HTS, 2006

Table 5: Botany Bay LGA Mode Share for All PM (3-hr) Peak Trip Purposes



ModeTrip Type

Source: HTS, 2006


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Table 6: Botany Bay LGA Mode Share for All Daily Trip Purposes



ModeTrip Type

Source: HTS, 2006

The review of mode share data revealed the following:

Up to 40% of internal daily trips within the Botany Bay LGA are walking trips. Walking is also a popular mode during the AM peak

In the PM peak, the percentage of walk trips drops significantly to less than 24%

Public transport is used for less than 10% of the Botany Bay LGA’s daily inbound and outbound trips

Public transport accounts for less than 4% of Botany Bay LGA’s daily internal trips

Use of public transport peaks at 19% on the outbound journeys during the AM peak

Use of private vehicles peaks at 73% for Botany Bay LGA internal trips during the PM peak

Trip Purpose The purpose of daily trips within the Botany Bay LGA is summarised in Table 7.

These patterns are derived from analysis of 2006 HTS data and are for all trip purposes. They have been broken down into outbound, inbound and internal trip types.

Analysis of the Botany Bay LGA trip purpose data revealed the following:

13% of outbound movements and 4% of inbound movements are Home to Work

7% of outbound movements and 2% of inbound movements are Home to Shopping

5% of internal movements are Shopping to Shopping

8% of outbound movements and 5% of internal trips are Home to Serve Passenger

7% of inbound movements and 5% of outbound movements are Home to Social/Recreation

Internal trips are a lot more varied in purpose. Less than 70% of internal trips are covered in the top 20 categories.

Focusing more on the directionality of commuter trips in, out and through the Botany Bay LGA, the data reveals:

72% of daily Home to Work trips are outbound

22% of daily Home to Work trips are inbound

6% of daily Home to Work trips are internal

Table 7: Summary of Top 20 Trip Purposes for Botany Bay LGA Daily Trips

Origin Purpose

Destination Purpose

In Out Int

Work Home 18% 6% 3%

Home Work 4% 13% 2%

WR Business WR Business 8% 8% 5%

Serve Pax Home 9% 5% 5%

Home Social/Recrtn 7% 5% 7%

Home Serve Pax 4% 8% 5%

Social/Recrtn Home 4% 8% 6%

Home Shopping 2% 7% 9%

Shopping Home 5% 2% 8%

WR Business Home 6% 2% 1%

Home WR Business 2% 5% 1%

Shopping Shopping 1% 1% 5%

Serve Pax Serve 2% 2% 1%

Home Return to wk 1% 2% 0%

Social/Recrtn Social/Recrtn 1% 1% 2%

Edu/ C'care Home 0% 2% 1%

Personal Home 2% 1% 2%

Shopping Go to work 1% 1% 2%

Return to work WR Business 1% 1% 2%

WR Business Work 1% 1% 1%

Other Other 21% 18% 30%

TOTALS % 100% 100% 100%

TOTAL TRIPS 127280 128330 70660

Source: HTS, 2006

Trip Direction Analysis of the 2011 AM and PM peak sub-area matrices has been undertaken to identify the directionality of movements in/out and through the study area.

The results of the analysis are presented in Figures 7 and 8.

A similar analysis was done for movements through the smaller Mascot Town Centre precinct as defined in the PARAMICS modelling. The results are presented in Figures 9 and 10.


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27%36%

15%

22%

Through Inbound Internal Outbound

Figure 7: Directionality of Movements in, out and through the Mascot Sub-Area Model in 2011 AM Peak

26%25%

19%

30%


Figure 8: Directionality of Movements in, out and through the Mascot Sub-Area Model in 2011 PM Peak

45%

37%

1% 17%


Figure 9: Directionality of Movements in, out and through the Mascot Town Centre PARAMICS model in 2011 AM Peak

47%

18%

1%34%


Figure 10: Directionality of Movements in, out and through the Mascot Town Centre PARAMICS model in 2011 PM Peak


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4 MASCOT SUB-AREA MODEL

Model Scope The 2011 Mascot TMAP strategic transport models are extracts from the 2011 TRINITY Transport model of Sydney, Newcastle and Wollongong.

A smaller sub-area model was used for the TMAP for reasons of practicality, namely;

Scenario run times are significantly reduced

So that the zonal system could be refined to improve accuracy of loading required for a micro-simulation (PARAMICS) model

The traffic impacts of the proposed Mascot Town Centre precinct redevelopment are unlikely to have a significant impact on the wider Sydney GMA network

The Mascot sub-area model extends from:

Surrey Hills in the north to Botany Bay in the south

Dulwich Hill in the West to Randwick in the east

A plot of the sub-area model network and zonal system is presented in Appendix ‘B’.

The Mascot sub-area model contains:

147 Internal travel zones

78 External Travel Zones

2,764 Road links

A car, taxi and light commercial vehicle matrix

A rigid truck matrix derived from BTS commercial trip tables

A semi-trailer matrix derived from BTS commercial trip tables

A B-double matrix derived from BTS commercial trip tables and known b-double routes

The Mascot sub-area model covers the following peak periods:

AM peak (7am to 9am)

PM peak (3pm to 6pm)

Travel Zone System The travel zones adopted for the Mascot sub-area model are based on the BTS 2006 travel zone boundaries. However, travel zones TZ404 and TZ406 are the exception. These two zones have been further divided into 11 smaller zones to increase the accuracy of traffic loading to a level suitable for the PARAMICS models. The refinements are as follows:

TZ404 was divided into 8 new zones (9001 to 9008).

TZ406 was divided into 3 new zones (9009 to 9011)

Link Flow Outputs 2011 AM and PM peak link flow plots for the Mascot Town Centre precinct, extracted from the sub-area network, are presented in Appendix ‘C’.

Level of Service Outputs A level of service (LOS) analysis was undertaken of the links within the Mascot Town Centre precinct under 2011 AM & PM peak flows. The LOS estimates for the precinct network are provided in Appendix ‘D’.

This LOS estimate was determined based on:

the volume/ capacity ratio of each link

AUSTROADS standard mid-block capacity values for typical urban roads with interrupted flows

Flows extracted from the Mascot sub-area strategic model which were converted to passenger car unit equivalents (PCUs) using the conversion factors outlined in Table 8

The LOS criteria as defined in Table 9

Table 8: Vehicle to PCU Conversion Factors

Vehicle Conversion Factor (PCUs)

Cars 1.0 Rigid 2.0

Articulated 2.5 B-Double 4.0

Table 9: LOS Criteria

LOS Volume/Capacity Ratio

A < 0.34 B 0.35 to 0.5 C 0.51 to 0.74 D 0.75 to 0.89 E 0.9 to 0.99 F <1.0


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Sub-area Network Calibration The calibration (accuracy) of the 2011 AM and PM peak sub-area models have been determined by comparing observed (counted) traffic volumes with modelled traffic volumes.

The model has been calibrated against 70 observed link flows derived from classified intersection counts undertaken at the following 12 sites:

1. Gardeners Road and Kent Road

2. Gardeners Road and Bourke Street

3. Gardeners Road and O’Riordan Street

4. Kent Road and Ricketty Street

5. Kent Road and Coward Street

6. Bourke Street and Coward Street

7. Coward Street and O’Riordan Street

8. O’Riordan Street and Bourke Street

9. O’Riordan Street and King Street

10. O’Riordan Street and Robey Street

11. Bourke Street and Church Avenue

12. Botany Road and Robey Street

The calibration results for the 2011 AM and PM peak models in the vicinity of the Mascot Town Centre precinct are presented in Tables E1 and E2 of Appendix ‘E’.

A summary of the results is presented in Table 10.

Table 10: Summary of 2011 AM & PM Peak Link Flow Calibration

GEH Values

AM PM No.

Links % No. Links %

< 5.0 60 86% 66 94% 5.0 to 7.5 9 13% 4 6% 7.5 to 10 0 0% 0 0% 10 to 15 1 1% 0 0% TOTALS 70 100% 70 100%

The analysis suggests that the following satisfactory levels of calibration have been achieved:

86% of sites achieved a GEH statistic less than 5.0 in the AM Peak (7am to 9am)

94% of sites achieved a GEH statistic less than 5.0 in the PM peak (3pm to 6pm)

Conclusion Given the good match between observed and modelled flows, it is concluded that the Mascot AM and PM peak sub-area models are sufficiently calibrated to the level of accuracy acceptable for its intended use.


APPENDIX A

TRINITY Model Calibration Results

Table 1: Calibration of Major Bridge & Tunnel Crossings

Bridge-Tunnel Crossings AM (2hrs) PM(3hrs)

Count Model GEH Ratio Count Model GEH Ratio

James Ruse Dr, N 5,089 5,060 0.41 0.9943 7,868 8,073 2.30 1.0260

James Ruse Dr, S 5,850 6,215 4.69 1.0623 7,525 7,785 2.98 1.0346

Silverwater Rd, N 6,639 6,814 2.13 1.0263 6,608 6,807 2.42 1.0300

Silverwater Rd, S 4,284 4,494 3.16 1.0489 8,793 9,063 2.86 1.0307

Homebush Bay, N 5,766 5,939 2.26 1.0299 9,726 9,785 0.59 1.0060

Homebush Bay, S 7,687 7,993 3.45 1.0397 10,549 10,761 2.05 1.0201

Victoria Rd, Gladesville Bridge, N 7,845 8,070 2.53 1.0288 10,192 10,437 2.41 1.0240

Victoria Rd, Gladesville Bridge, S 7,006 6,647 4.34 0.9488 10,456 10,656 1.95 1.0192

Victoria Rd, Iron Cove Bridge, N 5,118 5,269 2.09 1.0295 9,775 9,765 0.10 0.9990

Victoria Rd, Iron Cove Bridge, S 6,159 5,996 2.09 0.9736 7,943 7,987 0.49 1.0055

Sydney Harbour Bridge N 10,166 9,830 3.36 0.9669 20,465 20,424 0.29 0.9980

Sydney Harbour Bridge S 16,588 16,067 4.08 0.9685 15,552 15,614 0.50 1.0040

Sydney Harbour Tunnel, N 7,254 7,418 1.92 1.0226 10,240 9,644 5.79 0.9436

Sydney Harbour Tunnel, S 6,967 7,216 2.96 1.0358 8,650 8,724 0.80 1.0086

Total N 47,877 48,400 2.38 1.0109 74,875 74,934 0.28 1.0010

Total S 54,542 54,628 0.36 1.0016 69,467 70,590 4.24 1.0162


Table 2: Calibration of Major RTA Screen-lines AM Peak (2-hr)

SL AM (2hrs)

Observed Flow Modelled Difference GEH

IN OUT TOTAL IN OUT TOTAL IN OUT TOTAL IN OUT

01 20,816 17,734 38,550 20,491 17,844 38,335 325 -110 214 2.3 0.8

02 69,195 61,162 130,357 69,626 62,009 131,635 -430 -847 -1,277 1.6 3.4

03 9,262 3,694 12,956 9,549 4,075 13,624 -288 -380 -668 3.0 6.1

04 15,634 5,511 21,145 15,645 5,750 21,395 -10 -239 -250 0.1 3.2

05 56,309 33,365 89,673 56,640 34,011 90,651 -332 -646 -978 1.4 3.5

06 17,234 14,434 31,668 17,227 14,190 31,417 7 244 251 0.1 2.0

07 11,787 9,548 21,335 11,860 9,866 21,726 -73 -318 -391 0.7 3.2

08 11,304 8,497 19,801 11,174 8,733 19,907 130 -236 -106 1.2 2.5

09 21,864 9,721 31,585 21,439 10,285 31,724 425 -565 -139 2.9 5.6

10 4,026 2,628 6,654 4,164 2,468 6,633 -139 160 21 2.2 3.2

11 16,094 9,782 25,877 16,970 10,516 27,486 -875 -734 -1,609 6.8 7.3

12 8,963 5,269 14,231 8,923 5,155 14,078 39 114 153 0.4 1.6

13 7,317 3,255 10,572 7,608 3,590 11,198 -291 -335 -626 3.4 5.7

14 6,195 2,902 9,098 6,112 3,044 9,156 83 -141 -58 1.1 2.6

15 15,058 8,903 23,961 15,033 9,004 24,037 25 -101 -76 0.2 1.1

16 2,144 782 2,926 2,326 845 3,171 -182 -63 -245 3.9 2.2

TOTAL 293,203 197,185 490,389 294,789 201,384 496,173 -1,585 -4,199 -5,784 2.9 9.4

Table 3: Calibration of Major RTA Screen-lines PM Peak (3-hr)

SL PM (3hrs)

Observed Flow Modelled Difference O-M GEH

IN OUT TOTAL IN OUT TOTAL IN OUT TOTAL IN OUT

01 26,915 32,179 59,094 26,876 31,728 58,604 39 451 490 0.2 2.5

02 94,669 100,024 194,693 95,700 99,008 194,708 -1,030 1,015 -15 3.3 3.2

03 7,472 13,008 20,480 7,710 13,478 21,188 -239 -469 -708 2.7 4.1

04 9,447 19,369 28,816 9,275 19,767 29,042 171 -398 -226 1.8 2.8

05 51,328 77,822 129,150 51,132 78,516 129,648 196 -694 -498 0.9 2.5

06 24,789 22,904 47,693 24,306 22,827 47,133 483 76 560 3.1 0.5

07 15,286 20,529 35,814 15,576 20,505 36,081 -290 24 -266 2.3 0.2

08 11,608 15,642 27,250 11,905 16,017 27,922 -297 -375 -672 2.7 3.0

09 17,641 26,178 43,819 17,843 26,147 43,990 -202 31 -171 1.5 0.2

10 4,248 6,089 10,337 4,108 6,248 10,356 140 -159 -19 2.2 2.0

11 18,425 22,743 41,168 19,187 23,470 42,657 -762 -727 -1,489 5.6 4.8

12 8,896 12,565 21,461 8,976 12,787 21,763 -80 -222 -302 0.8 2.0

13 6,775 9,932 16,707 7,067 10,011 17,079 -292 -79 -372 3.5 0.8

14 5,455 7,962 13,417 5,444 7,244 12,688 11 717 728 0.2 8.2

15 12,133 19,379 31,512 12,002 19,356 31,358 131 23 154 1.2 0.2

16 2,875 1,846 4,721 3,137 1,815 4,952 -263 31 -231 4.8 0.7

TOTAL 317,963 408,170 726,133 320,243 408,926 729,169 -2,281 -756 -3,036 4.0 1.2


APPENDIX B

Mascot Sub-area Strategic Model Network & Zonal System


Figure C1: Mascot Sub-Area Model Network

MALABARMATRAVILLE

BRIGHTON-LE-SANDS

HILLSDALE

KYEEMAGH

BANKSMEADOW

ROCKDALE

BANKSIA

BOTANY

MAROUBRA

RKPAGEWOOD

SOUTH COO

DACEYVILLETURRELLA

ARNCLIFFE

EASTLAKES

MASCOT

KINGSFORD

TEMPE

SYDENHAM

COOGE

RLWOOD

ROSEBERY

BEACONSFIELD

ST PETERS RANDWICK

ZETLAND

E PARK

KENSINGTON

WAVER

MARRICKVILLE

ERSKINEVILLE

QUEENS PARKWATERLOO

ALEXANDRIA

ENMORE

DULWICH HILL

EVELEIGH

BONDI JUNCTION

CENTENNIAL PARK

NEWTOWN

REDFERN

LEWISHAM

DARLINGTON

STANMOREPETERSHAM MOORE PARKSUMMER HILL

CHIPPENDALE WOOLLAHRA

CAMPERDOWN

PADDINGTON

EDGECLIFF

SURRY HILLS

HAYMARKETFOREST LODGE

DARLINGHURSTULTIMO

LEICHHARDT

BELLEVU

D

ANNANDALEHABERFIELD

Bourk

e Rd

O'R

iord

an S

t

Qan

tas D

r

King St

Church Ave

Gardeners Rd

Coward StBot

any R

d

Mascot TMAP

0 .5 1

KilometersSMEC's TRINITY MODEL

Mascot_R002


Figure C2: Mascot Sub-Area Model Zonal System

MAMATRAVILLE

BRIGHTON-LE-SANDS

HILLSDALE

KYEEMAGH

BANKSMEADOWROCKDALE

BANKSIA

BOTANY

MAROUBRA

PARKPAGEWOOD

SOU

DACEYVILLETURRELLA

ARNCLIFFE

EASTLAKES

MASCOT

KINGSFORDTEMPE

SYDENHAM

EARLWOOD

ROSEBERY

BEACONSFIELD

ST PETERS RANDWICK

ZETLAND

TONE PARK

KENSINGTONMARRICKVILLE

ERSKINEVILLE

QUEENS PARKWATERLOO

ALEXANDRIA

ENMORE

DULWICH HILL

EVELEIGH

BONDI JUNC

CENTENNIAL PARKNEWTOWN

REDFERN

LEWISHAM

DARLINGTON

STANMOREPETERSHAM MOORE PARKSUMMER HILL

CHIPPENDALE WOOLLAHRA

CAMPERDOWN

FIELD

581

411

425

423

580

393

421

413

386

414

412

420

524

514

211

540

378

290

544

286

409

426

416

532

239

596

388

418

508

525

391

589

579

575

387

415

571

407

405

417

384291

533

371

370

509

520

526

408

527390

377

392

576

287

519

9110

361

379

530

541

360

537

385

577

283 284

381

292

419

276

380

289

372

366

213281 277

367

238

389

278

282

270268

9103

269

207

263

9109

279

205

273 275

204

254

253

266

262

288

259

9106

240

256

9102

255

9111

206

570

271

280

258

9107

260

9104

265

9108

257

201

264

274

9101

199

9105

O'R

iord

an S

t

Gardeners Rd

Botany R

d

Mascot TMAP

0 .5 1


Mascot_TZ11


APPENDIX C

Mascot Town Centre Precinct 2011 AM & PM Peak

Link Flow Plots


Figure C1: 2011 AM Peak (7am to 9am) All Vehicle Link Flows

MASCOT

Mascot Station

Domestic Airport Station

856

Qan

tas

Dr

4313905

613141

King St

765

5234

1856

Bota

ny R

oad

1428

2454

King St

Gardeners Rd

462562

484653

2133

2113

Ricketty St

545411

176828

43

466389

139625

14

13092135

O'Rior

dan S

t

2026

2388

Church Ave

760617

673217

Church Ave

Gardeners Rd

O'R

iord

an S

t, N

orth

3878

2606

802862

2082

1058

110

414

14

313

0

16093

4557

6

1143010

Bou

rke

Rd

982

827

16011865

4275

2091

199442

44

707191

2332

1766

Bot

any

Rd

587611

220142

2236

1623

1398

2813

1303

2667

1642161

104

1421

1104

2029

Bou

rke

St

187

128139

26056

00

26284

4307

1998

1421

1104

602713

166

3

2793

554

Ricketty St

115

5

12

91

2650

1703

1857

369

4

83 254

1856

1998

442

598

0

115

5

1291

174719

1421

1104

537

221145

14

2793

1811

1104

Mascot TMAP

0 .1 .2


MFlow_2011AM

10000 5000 2500MFlow_2011AM


Figure C2: 2011 PM Peak (3pm to 6pm) All Vehicle Link Flows

MASCOT

Mascot Station


2746

Qan

tas

Dr

2169

4153

Qan

tas

Dr

742837

King St

50

29

24

14

1640

Bot

any

Roa

d

32

64

22

82

King St

Gardeners Rd

753685

1065558

4291

3073

Ricketty St

648940

378433

94

777583

34002494

35652118

O'Ri

orda

n St

4371

3253

Church Ave

1116

1267

171788

Church Ave

Gardeners Rd

O'R

iord

an S

t, N

orth

4247

6662

1119

1049

1372

2528

23

59

11

54

37

18

32

2052

48

31

3017 021

Bou

rke

Rd

1740

1067

3090

2653

35

72

528

65

33

8

41

07

648

1161

28

95

43

22

Bot

any

Rd

960877

392379

37

16

394

8

24

83

3366

3231

3144

3354254

371

1922

1732

1688

Bou

rke

St

510

33447

48358

00

172151

4477

576

3

1922

1732

1262647

40

46

30

83

68

8

15

65

17

50

3131

3353

49

26

37

35

45

86

1

1640

77

18

59

0

15

65

17

50

923

804

1922

1732

65

95

904

35

74

30

83

1371

2359

Mascot TMAP

0 .1 .2


MFlow_2011PM

10000 5000 2500MFlow_2011PM


APPENDIX D

Mascot Town Centre Precinct 2011 AM & PM Peak

Network LOS


Figure D1: 2011 AM Peak Network LOS

ROSEBERY

Mascot Station


Qa

nt a

s D

r

King St

O'Rio

rdan S

t

Church Ave

Gardeners Rd

Coward St

Bo

ur k

e S

t

Bo tany R

dRicketty St

Mascot TMAP

0 .1 .2


LEVEL OF SERVICEABCDEFMFlow_2011AM

10000 5000 2500MFlow_2011AM


Figure D2: 2011 PM Peak Network LOS

MASCOT

ROSEBERY

Mascot Station


Qa

nta

s D

r

King St

O 'Riord

an St

Church Ave

Gardeners Rd

Coward St

Bo

u rk e

St

B o tany R

dRicketty St

Mascot TMAP

0 .1 .2


LEVEL OF SERVICEABCDEF

MFlow_2011PM

10000 5000 2500


APPENDIX E

Sub-Area Strategic Model Model Calibration


Table C1: Comparison of Modelled & Observed Link Flows for AM Peak (7am to 9am)

Link Road Name Observed

Vehicle Flows

Modelled Vehicle

FlowsGEH

10876 Kent Rd , South of Gardeners Rd

2295 2330 0.8

10877 Bourke St Exit, North of Gardeners Rd

790 870 2.7

10881 Gardeners Rd , West of O'Riordan St

2070 2110 0.9

10884 Gardeners Rd Exit, East of O'Riordan St

2419 2470 0.9

10892 O'Riordan St , North of Bourke St

1597 1780 4.5

10907 O'Riordan St Exit, South of King St

1803 2090 6.5

10908 Bourke St Exit, West of O'Riordan St

458 480 1.2

10909 O'Riordan St , South of Robey St

2773 2810 0.8

10910 O'Riordan St , South of Bourke St

4030 4240 3.3

10914 Coward St Exit, West of O'Riordan St

589 710 4.8

11905 Robey St Exit, West of O'Riordan St

1041 1060 0.5

14874 O'Riordan St Exit, South of Bourke St

1486 1670 4.7

21432 Bourke St , North of Church Ave

414 580 7.3


1836 2030 4.4

24516 Bourke St Exit, South of Coward St

997 1150 4.8

24517 Coward St Exit, West of Bourke St

1331 1420 2.4

26071 O'Riordan St Exit, South of Gardeners Rd

1555 1610 1.4

26072 Kent Rd Exit, South of Ricketty St

1710 1810 2.4

26073 Kent Rd Exit, North of Coward St

971 1100 4.1

26074 Bourke St Exit, North of Coward St

326 440 5.9

26075 Bourke St Exit, South of Church Ave

511 550 1.9

26076 O'Riordan St Exit, North of Coward St

2490 2650 3.2

40206 King St Exit, East of O'Riordan St

367 390 1.2

40212 Coward St Exit, East of Kent Rd

1104 1100 0.0

43687 Church Ave Exit, East of Bourke St

201 190 1.0

56789 Coward St , East of O'Riordan St

705 800 3.5

56791 O'Riordan St , South of Coward St

2628 2510 2.2

56916 O'Riordan St , North of Gardeners Rd

1629 1770 3.4

63008 King St Exit, West of O'Riordan St

151 140 1.0

63010 Coward St Exit, West of Kent Rd

595 670 3.1

63089 Gardeners Rd , West of Bourke St

2268 2390 2.5

63215 Ricketty St , West of Kent Rd

3611 3880 4.4

63225 Coward St , East of Bourke St

497 610 4.8

63231 O'Riordan St , North of Robey St

2250 2210 0.8


Vehicle Flows

Modelled Vehicle

FlowsGEH

63233 Robey St , East of O'Riordan St

357 410 2.7

10876 Kent Rd , North of Ricketty St

1698 1770 1.6

10877 Bourke St , North of Gardeners Rd

607 720 4.3

10881 Gardeners Rd , East of Bourke St

1999 2130 3.0

10884 Gardeners Rd , East of O'Riordan St

1929 2040 2.5

10892 O'Riordan St Exit, North of Bourke St

2814 3070 4.7

10907 O'Riordan St , South of King St

4075 4270 3.1

10908 Bourke St , West of O'Riordan St

626 650 1.1

10909 O'Riordan St Exit, South of Robey St

1444 1400 1.2

10910 O'Riordan St , North of King St

1701 1990 6.8

10914 Coward St , West of O'Riordan St

500 600 4.4

11905 Robey St , West of O'Riordan St

1857 2080 5.0


2540 2790 4.9

21432 Bourke St , South of Gardeners Rd

235 350 6.5


834 900 2.2

24516 Bourke St , South of Coward St

1197 1290 2.7

24517 Coward St , West of Bourke St

989 1100 3.6

26071 O'Riordan St , South of Gardeners Rd

3013 3130 2.1

26072 Kent Rd , South of Ricketty St

902 1100 6.4

26073 Kent Rd , North of Coward St

1284 1410 3.5

26074 Bourke St , North of Coward St

500 600 4.2

26075 Bourke St , South of Church Ave

301 510 10.3

26076 O'Riordan St , North of Coward St

1570 1700 3.3

40206 King St , East of O'Riordan St

406 470 2.9

40212 Coward St , East of Kent Rd

1227 1420 5.3

43687 Church Ave , East of Bourke St

1 0 1.4

56789 Coward St Exit, East of O'Riordan St

740 860 4.3


1353 1400 1.2

56916 O'Riordan St Exit, North of Gardeners Rd

2668 2840 3.3

63008 King St , West of O'Riordan St

119 130 0.8

63010 Coward St , West of Kent Rd

208 220 0.6

63089 Gardeners Rd , East of Kent Rd

1875 2030 3.4

63215 Ricketty St Exit, West of Kent Rd

2270 2610 6.8

63225 Coward St Exit, East of Bourke St

474 590 4.9

63231 O'Riordan St Exit, North of Robey St

4306 4510 3.1

63233 Robey St Exit, East of O'Riordan St

563 550 0.8


Table C2: Comparison of Modelled & Observed Link Flows for PM Peak (4pm to 6pm)


Vehicle Flows

Modelled Vehicle

FlowsGEH

10876 Kent Rd , South of Gardeners Rd

2019 1980 0.8

10877 Bourke St Exit, North of Gardeners Rd

678 750 2.7

10881 Gardeners Rd , West of O'Riordan St

2008.5 2100 2.1

10884 Gardeners Rd Exit, East of O'Riordan St

2421 2520 1.9


2856 3050 3.5

10907 O'Riordan St Exit, South of King St

3714 3620 1.5


726 730 0.1

10909 O'Riordan St , South of Robey St

1650 1700 1.2


2597.7 2810 4.1

10914 Coward St Exit, West of O'Riordan St

416 440 1.3

11905 Robey St Exit, West of O'Riordan St

1713 1730 0.5

14874 O'Riordan St Exit, South of Bourke St

2582 2790 3.9

21432 Bourke St , North of Church Ave

450.45 570 5.3


1154 1160 0.1

24516 Bourke St Exit, South of Coward St

1092 1070 0.6

24517 Coward St Exit, West of Bourke St

1204 1320 3.2

26071 O'Riordan St Exit, South of Gardeners Rd

2064 2210 3.1

26072 Kent Rd Exit, South of Ricketty St

933 940 0.2

26073 Kent Rd Exit, North of Coward St

1523 1620 2.3

26074 Bourke St Exit, North of Coward St

436 530 4.2

26075 Bourke St Exit, South of Church Ave

465 470 0.3

26076 O'Riordan St Exit, North of Coward St

2186 2140 0.9

40206 King St Exit, East of O'Riordan St

414 400 0.7

40212 Coward St Exit, East of Kent Rd

998.55 1190 5.7

43687 Church Ave Exit, East of Bourke St

349 350 0.0

56789 Coward St , East of O'Riordan St

664.65 770 3.8

56791 O'Riordan St , South of Coward St

1781.5 1710 1.7

56916 O'Riordan St , North of Gardeners Rd

2479 2590 2.2

63008 King St Exit, West of O'Riordan St

33 30 0.2

63010 Coward St Exit, West of Kent Rd

115 120 0.2

63089 Gardeners Rd , West of Bourke St

2136 2230 2.0

63215 Ricketty St , West of Kent Rd

2726.9 2910 3.4

63225 Coward St , East of Bourke St

547 600 2.2

63231 O'Riordan St , North of Robey St

3869 4040 2.8


Vehicle Flows

Modelled Vehicle

FlowsGEH

63233 Robey St , East of O'Riordan St

636 640 0.3

10876 Kent Rd , North of Ricketty St

3057 2960 1.8

10877 Bourke St , North of Gardeners Rd

843 890 1.7

10881 Gardeners Rd , East of Bourke St

2894.5 2940 0.8

10884 Gardeners Rd , East of O'Riordan St

2637 2740 2.0

10892 O'Riordan St Exit, North of Bourke St

1847 2030 4.1

10907 O'Riordan St , South of King St

2331 2450 2.4


365 380 0.9

10909 O'Riordan St Exit, South of Robey St

2653 2700 1.0

10910 O'Riordan St , North of King St

3494 3660 2.7

10914 Coward St , West of O'Riordan St

754 860 3.9

11905 Robey St , West of O'Riordan St

857 940 2.8


1934 2110 3.9

21432 Bourke St , South of Gardeners Rd

269.33 360 5.1


1260 1380 3.3

24516 Bourke St , South of Coward St

1170 1200 0.8

24517 Coward St , West of Bourke St

1160 1190 0.8

26071 O'Riordan St , South of Gardeners Rd

2540 2550 0.1

26072 Kent Rd , South of Ricketty St

1578 1620 0.9

26073 Kent Rd , North of Coward St

663 790 4.7

26074 Bourke St , North of Coward St

502 590 3.7

26075 Bourke St , South of Church Ave

405.3 510 5.0

26076 O'Riordan St , North of Coward St

2168 2300 2.7

40206 King St , East of O'Riordan St

488 530 2.0

40212 Coward St , East of Kent Rd

1254 1320 1.7

43687 Church Ave , East of Bourke St

3 0 2.4

56789 Coward St Exit, East of O'Riordan St

683 720 1.4


2351 2330 0.5

56916 O'Riordan St Exit, North of Gardeners Rd

2203 2320 2.6

63008 King St , West of O'Riordan St

217 230 0.8

63010 Coward St , West of Kent Rd

514 540 1.1

63089 Gardeners Rd , East of Kent Rd

2938 2990 1.0

63215 Ricketty St Exit, West of Kent Rd

4280 4560 4.3

63225 Coward St Exit, East of Bourke St

647 660 0.4

63231 O'Riordan St Exit, North of Robey St

2213 2450 4.9

63233 Robey St Exit, East of O'Riordan St

433 440 0.5

Mascot Town Centre Precinct TMAP

Appendix B

APPENDIX B

Working Paper 2# Micro-simulation Modelling

Calibration Report

Mascot TMAP, Micro-simulation Model Calibration Report (Rev A)

Page i of ii

MASCOT TMAP

Micro-simulation Model Calibration Report

2011 Base Case

Rev No.

Date Prepared by Reviewed by

A 14/09/11 M Stephens C Wiafe

Contact for further information:

Matthew Stephens NSW Traffic & Transport Planning Manager

(02) 9925 5542 0414 236 130

[email protected]

© Snowy Mountains Engineering Corporation (SMEC Australia Pty Ltd)

The information within this document produced by SMEC Australia is solely for the use of the Client identified on the cover sheet for the purpose for which it has been prepared. SMEC Australia undertakes no duty to or accepts any responsibility to any third party who may rely upon this document. All rights reserved. No section or element of this document may be removed from this document, reproduced, electronically stored or transmitted in any form without the written permission of SMEC Australia.


Page ii of ii

TABLE OF CONTENTS

1 INTRODUCTION ............................1

2 MODEL SCOPE .............................1

3 NETWORK CODING ...................2

4 TRAVEL DEMAND .......................3

5 MODEL CALIBRATION ...............5

6 CONCLUSION ................................7

APPENDIX ‘A’ - Model Network Plot

APPENDIX ‘B’ - Road Categories File

APPENDIX ‘C’ - Calibration Results

Mascot TMAP, Micro-simulation Model Calibration Report (RevA)

Page 1 of 7

1 INTRODUCTION

Background

This working paper documents the development and calibration of 2011 AM and PM peak period micro-simulation models for the Mascot Town Centre Precinct.

These models will be used to assess the impacts of future land use and transport scenarios being developed as part of a Transport Management and Accessibility Plan (TMAP) for the precinct.

The Mascot Town Centre Precinct TMAP micro-simulation models were built using PARAMICS software.

These 2011 base-case models have been calibrated to reflect the road network and traffic demands present in July/August 2011.

Figure 1: TMAP Study Area

2 MODEL SCOPE

Study Area

For the purpose of the traffic modelling, the study area is bounded by Gardeners Road in the north, Alexandria Canal in the west, Sydney Airport in the south and Botany Road in the east.

The micro-simulation model focuses on the traffic performance along the main roads and arterials within the Mascot Town Centre Precinct. In particular, it focuses on O’Riordan Street, Bourke Road, Coward Street, Gardeners Road, Kent Street and Robey Street.

A detailed plot of the model network is provided in Appendix ‘A’.

Time Periods

The model was set up to simulate the following peak hour periods:

� AM peak (7am to 9am)

� PM peak (4pm to 6pm)

The first hour in each peak is a lead-in hour and will not contribute to model statistics.

Model Statistics

The Mascot Town Centre Precinct TMAP models contain:

� 26 Zones

� 23 Sets of signals

� 307 Nodes

� 772 Links

� 126 Intersections

� 50.5km of roadway

� 13 Bus Routes

The model has been coded with fixed time traffic signal control.


Page 2 of 7

3 NETWORK CODING

Software

The Mascot TMAP micro-simulation models were built using PARAMICS version 6.7.2 software. No additional plug-ins or add-ons were required.

Network Build

The models were coded using spatially accurate aerial photographs. This was supplemented by on-site inspections of the network. The road network includes the following details:

� Number of lanes on the carriageway, including parking lanes

� Turning bays

� Speed zones

� Clearways, and

� Bus routes (including stops)

Signal phasing, green-splits, inter-greens and offsets were coded based on SCATS IDM data collected by the RTA.

These signal timings were initially coded into PARAMICS and then fine-tuned, where necessary, to maximise the efficiency of individual intersections.

Zone Definition

The models include 26 zones which are the origin and destinations for all movements within the models. These are divided into:

� 15 external zones linking the models to the wider road network, and

� 11 internal zones which are loading points for major retail, commercial, educational and residential land uses in the study area

A listing of the zones is presented in Table 1.

Road Categories

The standard RTA road categories file was used to define the network. A copy of the standard RTA road categories file used is provided in the Appendix ‘B’.

Each link in the model area was assigned an RTA road category that matched its number of lanes and speed limit.

Speed limits were initially based on commercial available GIS based road centre line data and confirmed by site audit.

Table 1: Micro-simulation Model Travel Zones

Zone Description

01 Airport Drive (External)

02 General Holmes Drive (External)

03 Botany Road North (External)

04 Wentworth Avenue (External)

05 King Street (External)

06 Airport, Domestic Terminal (External)

07 Airport, Long Term Car Park (External)

08 Airport, Air Centre, Service Area (External)

09 Mascot Park, King Street

10 Coleman Reserve, Stamford Plaza

11 Botany Shops, O’Riordan Street

12 Cargo International, Coward Street

13 Gardeners Road (External)

14 Botany Road South (External)

15 O’Riordan Street (External)

16 Bourke Street (External)

17 Gardeners Road Extension

18 Qantas Flight Training Centre, Kent Road

19 Holiday Inn Hotel, Bourke Street

20 Qantas Centre, Coward Street

21 Mascot Railway Station, Church Avenue

22 Airlink Business Park, Church Street

23 Hollingshed Street (External)

24 Cowards Street (External)

25 Ricketty Street (External)

26 John Curtin Reserve, Robey Street


Page 3 of 7

4 TRAVEL DEMAND

Regional Patterns

The regional travel patterns contained within the models were derived from SMEC’s TRINITY Transport Model (TRINITY).

TRINITY is a strategic transport model of the Sydney, Newcastle and Wollongong metropolitan areas. It is a series of geospatial information layers, databases and spreadsheets embedded within a transport modelling software package. These elements combined create a mathematical representation of land use and travel patterns in the Sydney Greater Metropolitan Area (GMA).

TRINITY is a software tool for planning Sydney’s future road infrastructure needs. It is unique in its socio-economic approach to travel demand, its geographic scope and the number (21) of trip purposes (work, shopping, recreational etc) it models.

TRINITY covers an area of 2.5 million hectares and contains 21,000 kilometres of road network and 20,500 intersections.

Development and calibration of the broader strategic modelling inputs to the Mascot Town Centre Precinct TMAP is documented in a separate report.

Matrix Development

The travel demand matrices used in these micro-simulation models were derived from the following data:

� sub-area matrices extracted from the calibrated TRINITY strategic transport model of Sydney, Newcastle and Wollongong

� Manual counts at critical intersections within the town centre precinct. This was used to calibrate cordon and turn demands

The matrix development process involved:

� Refinement of the TRINITY zonal system in the study area

� Extraction of initial light and commercial vehicle sub-area matrices

� Sub-area matrix estimation to achieve a closer match to observed flows

Vehicle Profile

The following five vehicle matrices were developed for use in the micro-simulation models:

� A car, taxi and light commercial vehicle matrix containing up to 21 trip purposes (e.g. recreational, shopping and commuter)

� A rigid truck matrix derived from Bureau of Transport Statistics (BTS) commercial trip tables

� A semi-trailer matrix derived from BTS commercial trip tables

� A B-double matrix derived from BTS commercial trip tables and know b-double routes

� Bus trips represented by fixed route demands with observed frequencies

These five demand matrices have been distributed amongst 17 vehicle type categories. The categories, dimensions and proportions of each vehicle type are specified by the RTA and are meant to be representative of the average NSW vehicle fleet characteristics.

The standard RTA vehicle file includes the following categories:

� Car/taxi (6)

� Rigid Truck (3)

� Semi-trailer (3)

� B-Double (3)

� Bus (2)

Profile Specification

The model was set up to simulate the following peak hour periods:

� AM peak (7am to 9am)

� PM peak (4pm to 6pm)

The 15-minute demand release profiles for traffic entering the road network during the lead-in and peak hour are based on observed traffic flows collected at 12 sites in July 2011.

The adopted 15-minute profiles are presented below in Table 2.

Bus Routes

Bus services are explicitly coded into the models and treated as fixed route demands. There are 13 bus routes coded into the models. The service schedules used in the model are listed below in Tables 3 and 4 below.

Release times for bus services were estimated based on published time-table data for the stops closest to their entry point.

For the purposes of the simulation, the team adopted bus stop dwell times ranging between 7 and 12 seconds.


Page 4 of 7

Table 2: Demand Release Profiles

Peak

15-min

Period

Ending

15-min

Release

Profile

% Of

Strategic

Matrix

AM1 715 22.0% 48.6%

730 24.6%

745 25.5%

800 27.9%

AM2 815 26.3% 51.4%

830 27.7%

845 23.4%

900 22.6%

PM1 1515 - 31.8%

1530 -

1545 -

1600 -

PM2 1615 24.0% 33.6%

1630 25.6%

1645 25.3%

1700 25.1%

PM3 1715 25.4% 34.6%

1730 25.7%

1745 24.5%

1800 24.4%

Table 3: AM Peak Bus Route and Service Schedules

Notes:

1) Each service is broken down by direction (e.g. A=northbound, B= southbound)

2) The times quoted above are release times for bus services entering the models.

3) Bus Stops were coded based on GIS data supplied by Council and confirmed during site audits.

410_A

6:59

7:32

7:53

8:23

8:56

410_B

7:53

400_A

6:58

7:19

7:41

8:01

8:22

8:42

400_B

6:55

7:15

7:28

7:42

8:02

8:25

8:45

357_A

6:50

7:20

7:38

7:53

8:09

8:32

9:00

357_B

6:51

7:07

7:22

7:39

7:58

8:38

9:00

305_A

305_B

7:05

7:17

7:29

7:41

7:51

8:01

8:11

8:21

8:31

8:43

8:56

M20_A

7:03

7:13

7:23

7:33

7:43

7:53

8:03

8:13

8:23

8:33

8:43

8:53

M20_B

7:18

7:28

7:38

7:48

7:58

8:08

8:18

8:28

8:38

8:48

8:58

309_A

7:04

7:13

7:17

7:32

7:48

7:56

8:03

8:16

8:31

8:48

309_B

7:05

7:08

7:11

7:20

7:23

7:28

7:35

7:39

7:42

7:51

7:56

8:06

8:09

8:19

8:21

8:24

8:33

8:36

8:42

8:48

8:59

L09_A

L09_B

7:00

7:15

7:30

7:45

8:00

8:09

8:27

8:42

X09_A

7:21

7:35

7:54

8:07

8:20

X09_B

310_A

7:00

7:25

7:38

7:58

8:10

8:23

8:38

8:58

310_B

6:59

7:14

7:26

7:45

7:59

7:15

8:27

8:39

8:53

X10_A

7:13

7:44

8:01

8:13

X10_B

303_A

7:03

7:19

7:36

7:40

7:52

8:01

8:10

8:22

8:31

8:46

303_B

7:11

7:48

8:29

8:59

301_A

6:57

7:17

7:30

7:44

8:01

8:24

8:58

301_B

7:32

20:09

8:40

X03_B


Page 5 of 7

Table 4: PM Peak Bus Routes and Service Schedules

5 MODEL CALIBRATION

Data Sources

The principal data sources available for calibration were:

� SCATS detectors counts collected at 23 sites in August 2011

� Manual classified intersection counts collected at 12 key sites in August 2011

Model Adjustments

During the model calibration process, the following adjustments were made to the model, where appropriate:

� Link and node parameters adjusted

� Signal phase green-splits and offsets were revised

At both signalised and non-signalised intersections, the following features were applied to improve intersection operations, where appropriate:

� Node Blocking – Avoid vehicles staying at signalised intersections when congestion occurs

� Stacked Turns – Allow right-turning vehicles to move into the intersections and either wait for a suitable gap in the oncoming traffic before turning, or make the right-turn at the end of the green phase

� Force Merge / Across – Force right-turning vehicles to cross the oncoming traffic after they have been delayed for some time when oncoming traffic leaves a gap at non-signalised intersections.

Nextlanes was used to force vehicle to travel on the correct lane whenever there is a decision point (e.g. stop-lines) within the micro-simulation model. These decision points do not exist in real life and therefore Nextlanes was implemented in the model to ensure that modelled behaviour was realistic.

Signposting was implemented at some locations where immediate lane change just before the decision point has been identified. Signposting was used to encourage earlier lane changes to be made to prevent unrealistic congestion. Whenever the Signposting technique is not available due to the link attributes constraint, Lane Choice was used to force lane utilisation.

410_A

15:0915:2715:4516:0016:3416:5817:0917:3017:56

410_B

15:0015:2115:4116:0116:1316:2116:4117:0117:2017:3917:59

400_A

15:0215:2115:4116:0216:1716:3316:5217:1217:3217:3717:51

400_B

15:0915:2915:4916:0916:2916:4916:5917:0917:2817:47

357_A

15:5316:2316:5317:2317:53

357_B

15:2515:5516:2516:5617:26

305_A

15:3516:0016:2416:4817:1217:47

305_B

M20_A

15:0315:1315:2315:3315:4315:5316:0316:1316:2316:3316:4316:5317:0317:1317:2317:3317:4317:53

M20_B

15:0815:1815:2815:3815:4815:5816:0816:1816:2816:3816:4816:5817:0817:1817:2817:3817:4817:58

309_A

15:0215:0715:1515:2315:2715:3315:3815:4015:4315:4915:5316:0016:0316:0616:0916:1416:2116:2716:3416:4216:5016:5717:0417:1217:2117:3117:3817:4517:48

309_B

15:0015:1715:3715:5216:0716:2116:3216:3616:4517:0517:1017:1817:3217:3717:52

L09_A

15:1515:4716:1816:5017:17

L09_B

X09_A

X09_B

16:4717:1617:55

310_A

15:0015:1915:3015:4115:5016:0016:1216:2416:3816:5317:0817:2717:52

310_B

15:0715:2715:4516:0016:1416:2816:4016:5017:1617:2617:4717:57

X10_A

X10_B

17:0617:35

303_A

15:0616:0917:10

303_B

15:2815:5115:5916:1916:3816:5017:1017:2017:3517:4517:50

301_A

15:2515:5816:2816:5817:44

301_B

15:1015:4016:0516:2716:5817:2817:3817:5317:58

X03_B

17:50


Page 6 of 7

Seed Selection and Model Stability

The stability of the AM and PM peak models was tested using the first five seed values specified by the RTA (560, 28, 7771, 86524, 2849). The models were run and the results reported by link. The Co-efficient of Variance (CoV) was calculated for the link flows generated by the five model seeds. This coefficient represents ratio of the standard deviation to the mean of the five modelled flows for each link.

Figures 2 and 3 illustrate that the pattern of the five seeds is similar. These results suggest that the models are operating in a stable manner in the AM and PM peak periods.

The demand release curves of the AM and PM peak models were estimated using the first five seed values normally specified by the RTA (560, 28, 7771, 86524, 2849). The results were analysed to determine which of the five release curves was most representative of an average demand scenario.

The demand curves for the AM and PM peaks are presented below in Figures 2 and 3, respectively.

0

200

400

600

800

1000

1200

1400

1600

1800

7:01

7:11

7:21

7:31

7:41

7:51

8:01

8:11

8:21

8:31

8:41

8:51

No. of Vehicles

Time(h:mm)

Seed 560 Seed 28

Seed 7771 Seed 86524

Seed 2849

Figure 2: AM Peak Demand Release Profiles

0

200

400

600

800

1000

1200

16:01

16:11

16:21

16:31

16:41

16:51

17:01

17:11

17:21

17:31

17:41

17:51

No. of Vehicles

Time(h:mm)

Seed 560

Seed 28

Seed 7771

Seed 86524

Seed 2849

Figure 3: PM Peak Demand Release Profiles

The analysis suggests that the following seeds produced release curves most representative of an average demand scenario:

� AM peak = 2,849

� PM peak = 2,849

Calibration Measures

The calibration (accuracy) of the micro-simulation models is determined by comparing observed (counted) traffic volumes and intersection queue lengths with modelled traffic volumes and queuing.

The RTA has generally adopted the UK’s DMRB standards for traffic flow calibration. These rely heavily on a measure called the GEH statistic. The GEH statistic is a self-scaling empirical statistic with similarities to a chi-squared test.

The following RTA acceptability targets were adopted for the micro-simulation model calibration assessments:

� Individual flows within 100vph (flows <700vph)

� Individual flows within 15% (flows between 700 and 2,700vph)

� Individual flows within 400vph (flows > 2,700vph)

� Individual flows achieve a GEH value less than 5.0 at more than 85% of sites

A review of observed and modelled queue lengths was also undertaken during the calibration process.


Page 7 of 7

Calibration Results

The calibration results for the AM and PM peak models, using the selected average seed values, are presented in Tables C1 and C2 of Appendix ‘C’.

A summary of results is presented in Table 5.

Table 5: Summary of AM and PM Peak Link and Turn-Flow Calibration

GEH Values

AM PM

No. Links

% No. Links

%

< 5.0 97 92% 98 92%

5.0 to 7.5 6 6% 6 6%

7.5 to 10 3 2% 2 2%

10 to 15 0 0% 0 0%

TOTALS 106 100% 106 100%

The model achieved the following level of calibration:

� In AM peak, 92% of sites achieved a GEH statistic less than 5.0

� In PM peak, 92% of sites achieved a GEH statistic less than 5.0

6 CONCLUSION

Given the match between observed and modelled flows, the stability of the models, favourable comparisons between the modelled and observed behaviour, it is concluded that the Mascot Town Centre Precinct TMAP micro-simulation models are sufficiently calibrated and replicate existing conditions to a level of accuracy acceptable for its intended use.


APPENDIX A

Plot of Model Network

Mascot TMAP, M

icro-simulation Model Calibration Report (Rev A)

Zone Description

01

Airport Drive (External)

02

General Holmes Drive (External)

03

Botany Road North (External)

04

Wentworth Avenue (External)

05

King Street (External)

06

Airport, Domestic Term

inal (External)

07

Airport, Long Term Car Park (External)

08

Airport, Air Centre, Service Area

(External)

09

Mascot Park, King Street

10

Coleman Reserve, Stamford Plaza

11

Botany Shops, O’Riordan Street

12

Cargo International, Coward Street

13

Gardeners Road (External)

14

Botany Road South (External)

15

O’Riordan Street (External)

16

Bourke Street (External)

17

Gardeners Road Extension

18

Qantas Flight Training Centre, Kent

Road

19

Holiday Inn Hotel, Bourke Street

20

Qantas Centre, Coward Street

21

Mascot Railway Station, Church

Avenue

22

Airlink Business Park, Church Street

23

Hollingshed Street (External)

24

Cowards Street (External)

25

Ricketty Street (External)

26

John Curtin Reserve, Robey Street

Figure A1: Mascot TMAP Micro-simulation Model Network


APPENDIX B

Road Category File


categories 1 to 78

category 1 lanes 1 speed 110 kph width 3.3 m colour 0x0000ff00 type urban major

headway factor 1.000 curve speed factor 1.0 toll 0.000 cost factor 0.80

signpost 750.0 m,1.0 m













category 6 lanes 1 speed 100 kph width 3.3 m colour 0x0000aa00 type urban major
















category 11 lanes 1 speed 100 kph width 3.3 m colour 0x0000ee00 type urban major















category 16 lanes 1 speed 100 kph width 3.3 m colour 0x0000ffff type urban major















category 21 lanes 1 speed 90 kph width 3.3 m colour 0x0000eeee type urban major
















category 26 lanes 1 speed 80 kph width 3.3 m colour 0x0000cdcd type urban major















category 31 lanes 1 speed 70 kph width 3.3 m colour 0x00008b8b type urban major










category 34 lanes 4 speed 70 kph width 13.2m colour 0x00008b8b type urban major































category 44 lanes 1 speed 80 kph width 3.3 m colour 0x00dddd00 type urban minor


















category 50 lanes 1 speed 70 kph width 3.3 m colour 0x00dd0000 type urban minor









category 53 lanes 1 speed 60 kph width 3.3 m colour 0x008d0000 type urban major










category 56 lanes 1 speed 60 kph width 3.3 m colour 0x008b0000 type urban minor









category 59 lanes 1 speed 60 kph width 3.3 m colour 0x0000a5ff type urban major









category 62 lanes 1 speed 60 kph width 3.3 m colour 0x00009aee type urban minor









category 65 lanes 1 speed 50 kph width 3.3 m colour 0x000085cd type urban major










category 68 lanes 1 speed 50 kph width 3.3 m colour 0x000000ff type urban minor









category 71 lanes 1 speed 40 kph width 3.3 m colour 0x000000ee type urban major









category 74 lanes 1 speed 40 kph width 3.3 m colour 0x000000cd type urban minor










category 77 lanes 1 speed 40 kph width 3.3 m colour 0x00ffffff type urban minor



category 78 lanes 2 speed 40 kph width 6.6 m colour 0x00ffffff type urban minor




APPENDIX C

Model Calibration Results


Table C1: Comparison of AM Peak Hour Modelled and observed flows

Junction Dir Link ref: observed Modelled GEH

Gardeners Road and Kent Road

R 1232:1227:1241 112 100 1.2

T 1140:1231:1139 903 894 0.3

L 1241:1227:1238 47 45 0.3

R 1241:1227:1230 23 26 0.6

T 1139:1227:1238 1083 1044 1.2

L 1138:1139:1228 81 72 1.0

Bourke Street and Gardeners Road

T 1281:1136:1134 138 129 0.8

L 1281:1136:1282 106 106 0.0

R 1281:1136:1226 132 133 0.1

T 1134:1136:1281 44 27 2.9

L 1134:1136:1226 18 8 2.8

R 1134:1136:1282 26 31 0.9

T 1321:1136:1226 865 856 0.3

L 1321:1136:1134 94 102 0.8

R 1282:1136:1281 140 139 0.1

T 1140:1136:1282 895 840 1.9

L 1140:1136:1281 235 250 1.0

O'Riordan Street and Gardeners Road

T 1213:1144:1212 583 610 1.1

L 1213:1144:1218 79 68 1.3

R 1214:1144:1323 139 134 0.4

T 1285:1144:1214 1152 1118 1.0

L 1285:1144:1323 119 121 0.2

R 1212:1144:1218 216 261 2.9

T 1217:1144:1323 841 853 0.4

L 1217:1144:1212 218 221 0.2

R 1218:1144:1214 32 29 0.5

T 1323:1144:1218 902 864 1.3

L 1323:1144:1214 124 119 0.5

Ricketty Streetand Kent Road

R 1137:1087:1088 743 773 1.1

T 1250:1087:1138 1064 1013 1.6

L 1088:1087:1137 351 442 4.6

R 1088:1087:1138 100 112 1.2

T 1138:1087:1137 791 809 0.6

L 1249:1087:1088 135 163 2.3

Kent Road and Coward Street

T 1088:1083:1035 80 84 0.4

L 1088:1083:1072 434 443 0.4

R 1088:1083:1081 166 158 0.6

T 1035:1083:1088 29 40 1.9

L 1035:1083:1081 19 18 0.2

R 1035:1083:1072 76 77 0.1

T 1072:1083:1081 199 201 0.1

L 1072:1083:1035 42 57 2.1

R 1072:1083:1088 418 453 1.7

T 1081:1083:1072 69 61 1.0

L 1081:1083:1088 54 63 1.2

R 1081:1083:1035 9 6 1.1

Bourke Street and Coward Street

T 1333:1089:1091 140 135 0.4

L 1333:1089:1092 52.25 18 5.8

R 1095:1089:1270 91 74 1.9

T 1330:1089:1095 110 157 4.1

L 1330:1270:1072 457 446 0.5

R 1091:1089:1092 58.8 108 5.4

Junction Dir Link ref: observed Modelled GEH

T 1092:1089:1270 192 213 1.5

L 1092:1089:1091 47 47 0.0

R 1092:1089:1095 56 41 2.2

T 1072:1089:1092 177 195 1.3

L 1072:1089:1095 4 2 1.2

R 1072:1089:1091 320 316 0.2

O'Riordan Street and Coward Street

T 1210:1115:1272 756 703 2.0

L 1210:1208:1117 64 49 2.0

T 1206:1115:1210 1088 1079 0.3

L 1206:1209:1207 30 17 2.7

R 1272:1115:1208 157.7 75 7.7

T 1208:1115:1209 282 277 0.3

L 1208:1115:1272 84 63 2.4

R 1208:1115:1210 27.55 0 7.4

T 1209:1115:1208 203 205 0.1

L 1209:1115:1210 52.5 95 4.9

R 1209:1115:1272 29 31 0.4

O'Riordan Street and Bourke Street

R 1113:1107:1106 145 167 1.8

T 1114:1107:1108 356 419 3.2

L 1106:1113:1114 9 3 2.4

R 1106:1107:1108 442 440 0.1

T 1108:1107:1113 1050 1014 1.1

L 1108:1336:1119 953 967 0.5

O'Riordan Street and King Street

T 1109:1110:1203 746 805 2.1

L 1109:1110:1204 52 58 0.8

T 1202:1110:1109 1842 1811 0.7

L 1202:1110:1016 49 52 0.4

R 1203:1110:1204 129 104 2.3

T 1204:1110:1016 49.4 18 5.4

L 1204:1110:1203 51 58 0.9

R 1204:1110:1109 110 117 0.7

T 1016:1110:1204 11 11 0.0

L 1016:1110:1109 17 36 3.7

R 1016:1110:1203 36 49 2.0

O'Riordan Street and Robey Street

T 1038:1197:1024 609.9 434 7.7

L 1038:1028:1030 116 85 3.1

R 1017:1197:1198 350 382 1.7

T 1298:1197:1017 1374 1422 1.3

T 1029:1197:1198 160 155 0.4

L 1029:1024:1037 46 73 3.5

T 1198:1197:1028 144 204 4.5

L 1201:1197:1017 661 691 1.2

Bourke Street and Church Avenue

T 1133:1131:1094 220 224 0.3

L 1133:1131:1120 30.4 6 5.7

T 1094:1131:1133 62.7 15 7.7

T 1132:1131:1120 34 66 4.5

L 1132:1131:1133 17.85 51 5.6

R 1132:1131:1094 47 34 2.0

Botany Road and Robey Street

R 1010:1008:1032 173 140 2.6

T 1010:1008:1196 624 748 4.7

L 1032:1008:1010 205 192 0.9

R 1032:1008:1196 125 97 2.7

T 1196:1008:1010 1334 1358 0.7

L 1005:1196:1032 79 76 0.3


Table C2: Comparison of PM Peak Hour Modelled and Observed flows

Junction Dir Link ref: Observed Modelled GEH

Gardeners Road and Kent Road

R 1232:1227:1241 28 10 4.1

T 1140:1231:1139 1442 1488 1.2

L 1241:1227:1238 76 75 0.1

R 1241:1227:1230 81 84 0.3

T 1139:1227:1238 1056 976 2.5

L 1138:1139:1228 8 4 1.6

Bourke Street and Gardeners Road

T 1281:1136:1134 133 122 1.0

L 1281:1136:1282 105 120 1.4

R 1281:1136:1226 140 148 0.7

T 1134:1136:1281 83 82 0.1

L 1134:1136:1226 20 26 1.3

R 1134:1136:1282 33 10 5.0

T 1321:1136:1226 1310 1335 0.7

L 1321:1136:1134 65.1 128 6.4

R 1282:1136:1281 120 118 0.2

T 1140:1136:1282 961 896 2.1

L 1140:1136:1281 171 151 1.6

O'Riordan Street and Gardeners Road

T 1213:1144:1212 962 958 0.1

L 1213:1144:1218 121 129 0.7

R 1214:1144:1323 221 222 0.1

T 1285:1144:1214 897 895 0.1

L 1285:1144:1323 107 76 3.2

R 1212:1144:1218 292 306 0.8

T 1217:1144:1323 1159 1178 0.6

L 1217:1144:1212 92 129 3.5

R 1218:1144:1214 66 61 0.6

T 1323:1144:1218 802 905 3.5

L 1323:1144:1214 116 111 0.5

Ricketty Streetand Kent Road

R 1137:1087:1088 400 412 0.6

T 1250:1087:1138 929 897 1.1

L 1088:1087:1137 760 769 0.3

R 1088:1087:1138 128.3 79 4.8

T 1138:1087:1137 1490 1488 0.1

L 1249:1087:1088 34.65 71 5.0

Kent Road and Coward Street

T 1088:1083:1035 26 15 2.4

L 1088:1083:1072 283 363 4.5

R 1088:1083:1081 16 4 3.8

T 1035:1083:1088 99 107 0.8

L 1035:1083:1081 6 2 2.0

R 1035:1083:1072 73 75 0.2

T 1072:1083:1081 19 13 1.5

L 1072:1083:1035 53.2 23 4.9

R 1072:1083:1088 636 638 0.1

T 1081:1083:1072 132 137 0.4

L 1081:1083:1088 123 130 0.6

R 1081:1083:1035 10 11 0.3

Bourke Street and Coward Street

T 1333:1089:1091 167 176 0.7

L 1333:1089:1092 44 26 3.0

R 1095:1089:1270 47.5 4 8.6

T 1330:1089:1095 144 201 4.3

L 1330:1270:1072 383 375 0.4

R 1091:1089:1092 66 79 1.5

T 1092:1089:1270 169 171 0.2

L 1092:1089:1091 54 24 4.8

R 1092:1089:1095 48 76 3.6

T 1072:1089:1092 233 279 2.9

L 1072:1089:1095 37.05 13 4.8

R 1072:1089:1091 334 319 0.8

O'Riordan Street and

T 1210:1115:1272 1037 1087 1.5

L 1210:1208:1117 44 47 0.4

Junction Dir Link ref: Observed Modelled GEH

Coward Street

T 1206:1115:1210 968 958 0.3

L 1206:1209:1207 13 22 2.2

R 1272:1115:1208 82 73 1.0

T 1208:1115:1209 194 248 3.6

L 1208:1115:1272 109 106 0.3

R 1208:1115:1210 27.55 0 7.4

T 1209:1115:1208 251 291 2.4

L 1209:1115:1210 132.1 55 8.0

R 1209:1115:1272 42 32 1.6

O'Riordan Street and Bourke Street

R 1113:1107:1106 35 40 0.8

T 1114:1107:1108 1128 1076 1.6

L 1106:1113:1114 7 0 3.7

R 1106:1107:1108 591 587 0.2

T 1108:1107:1113 703 753 1.9

L 1108:1336:1119 547 493 2.4

O'Riordan Street and King Street

T 1109:1110:1203 1638 1589 1.2

L 1109:1110:1204 81 75 0.7

T 1202:1110:1109 1009 1030 0.7

L 1202:1110:1016 12.35 0 5.0

R 1203:1110:1204 117 96 2.0

T 1204:1110:1016 4 4 0.0

L 1204:1110:1203 132 87 4.3

R 1204:1110:1109 114.5 169 4.6

T 1016:1110:1204 32.3 5 6.3

L 1016:1110:1109 15.75 43 5.0

R 1016:1110:1203 77 98 2.2

O'Riordan Street and Robey Street

T 1038:1197:1024 1247 1170 2.2

L 1038:1028:1030 97.85 45 6.3

R 1017:1197:1198 565 545 0.8

T 1298:1197:1017 788 772 0.6

T 1029:1197:1198 291 291 0.0

L 1029:1024:1037 60 61 0.1

T 1198:1197:1028 90 114 2.4

L 1201:1197:1017 334 377 2.3

Bourke Street and Church Avenue

T 1133:1131:1094 146 175 2.3

L 1133:1131:1120 62 73 1.3

T 1094:1131:1133 113 82 3.1

T 1132:1131:1120 51 30 3.3

L 1132:1131:1133 16 43 5.0

R 1132:1131:1094 58 58 0.0

Botany Road and Robey Street

R 1010:1008:1032 264 257 0.4

T 1010:1008:1196 1227 1234 0.2

L 1032:1008:1010 61 41 2.8

R 1032:1008:1196 127 112 1.4

T 1196:1008:1010 892 890 0.1

L 1005:1196:1032 132 93 3.7

Mascot Town Centre Precinct TMAP - City of Botany Bay · Mascot Town Centre Precinct TMAP Appendix...

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Transcript of Mascot Town Centre Precinct TMAP - City of Botany Bay · Mascot Town Centre Precinct TMAP Appendix...