Merging Facility and Process

Pedestrian Planning with Simulation Modeling

Gloria Bender

January 7, 2009

Outline

• Introduction and Background

• General Modeling Approach and Considerations

• Simulation Modeling Examples

• Benefits of Simulation in Planning

• Conclusions

Introduction

• Transportation terminals, shopping, entertainment and sport venues require special planning considerations to– Accommodate growing and highly-peaked activity schedules– Support the complex interactions of processes within the

facility– Adapt to changes in market preferences– Fulfill consumers’ increasing expectations

• Complexity, cost and time are causing owners to look for tools to evaluate performance of facilities prior to program selection or construction.

• This presentation focuses on the use of computer simulation and animation to better plan large pedestrian service facilities.

Our History

1986 1989 1998

First airside simulation project

First landside simulation project

Worked as the Airport Consulting Group within AA Decision Technologies,an AMR firm, SABRE Decision Technologies, and The SABRE Group

Management buy-out from SABRE

2004

Initiated buy/sell discussions with SABRE

Management restructure 100% WBE

1997

Our Projects

Worked in Over 20 Countries

• Worked at 24 of the 25 largest airports

• Completed over 200 simulation projects over 10 years

Typical Planning Approachs

• Advantages– Easy and quick to apply– Inexpensive– Historically-accepted

approach

• Disadvantages– Do not account for system

dynamics– Many projects require more

sophisticated analyses– May require limiting assumptions– Limited performance measures

available -- averages without statistical confidence

– Many systems cannot be modeled by analytical techniques

– Cannot consider dependencies– Requires mathematical

sophistication

Rules of Thumb / Design Standards

Simulation - Advantages

• Once model is built, it can be used repeatedly for “what if” scenarios).

• Analyze a proposed system even though the input data are somewhat sketchy

• Simulation data less costly to obtain than similar data from the real system.

• Analytical models usually require many simplifying assumptions to make them mathematically tractable; simulation models have no such restrictions

• Any conceivable performance measure can be obtained, including detailed, custom “Level of Service” standards.

• Simulation is occasionally the only means of deriving a viable solution to a problem - builds consensus

Simulation Disadvantages

• May be costly, requiring more time to construct and validate than other methods

• Need trained staff, software, and fast computer• Need continuous focus to complete projects• Sometimes used when analytic techniques will

suffice

Calculation vs. Simulation Analysis

• Simulation accounts for process distribution in assessing performance of the system.

• Assumptions:– Customers arrive to a server according to uniform [.1,4.1]

distribution with a 2.1 minute average– The server has a constant service time of 2.0 minutes

• Simple analysis– Parameters such as arrival rates are described by averages– Using the average arrival rate (2.1 minutes), no queue will

occur because the service time is less than the inter-arrival time

Calculation vs. Simulation Analysis

• Simulation Analysis– Allows for parameters to be described by the actual

distributions observed• Arrival rate is not uniform!

– Based on five independent runs • The maximum queue before the server is 15 customers• The average queue before the server is 1.1 customers

• Conclusion– When distributional information is available, using

simulation analysis provides more accurate results– Sufficient detail should be included in a model to

accurately portray the dynamics of the system

Animation Example – Middle School

Animation Example – Light Rail

Caution: Simulation vs. Animation

• Simulation– Mathematical representation of the system over time– Expected demand on facility– Statistical output of system performance– Multiple replications/runs must be performed to ensure confidence

in results– May or may not include animation

• Animation (or single-run simulation)– Graphical picture of system demand– Good idea of facility performance but not statistically-sound results

• Architectural walk-through models– Depicts ‘look and feel’ of facility– Does not include realistic demand

Why Simulate?

• Illustrate dynamic operations vs. static facility plan

• System-wide evaluation—minimizes unintended consequences

• Granularity of planning early-on saves design costs

• Captures the effects of process variability• Explicitly models interactions• Accounts for patron and tenant differences• Provides detailed performance metrics for

decision support – Any metrics required—no limitations– For the entire planning day as well as peak

hour• Enables “what if” analyses

When to Simulate?

• Programming/planning phase• Concept development

– Evaluate competing alternatives based on performance• Schematic design validation• Detail design• Construction phasing• Post implementation

– Operational changes– Renovations/expansions

• Illustrate new operations

Modeling Philosophy

• Involve stakeholders (users and decision makers) throughout entire process– Owner– Applicable government regulators– Tenants– Other users

• Develop unique model to answer stakeholder’s specific question• Establish the performance metrics necessary for decision

support up front• Model the total system of integrated operational components

– Realistic demand– Realistic environmental constraints– Interdependencies between functions

Validation Example

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Field Test

Calibrated Model

Prediction Model

Simulation Model Considerations

• Mathematical-logical representation • Physical layout—CAD drawing• Operating rules• Modeling language doesn’t matter, so long as . . .

– Random Number Streams - Ensure variables of interest have separate random number streams

– Simulation Replications - Place confidence intervals around your most variable output measure and ensure replications produce statistically significant differences

• “Linking” models

Simulation Output

• Report Results - Graphs and animation can present a wealth of data at one glance

• Animation• Model delivery/GUI

Travel to INS42%

INS5%

Baggage17%

Checkpoint2%

Recheck2%

Security8%

Travel to Gate20%

FIS Exit4%

Int’l Pax Connect Time

Level of Service Concept

• In buildings, typically expressed as space requirement– Will pedestrians be able to move freely?– Will people be comfortable?

• Two aspects– Physical capacity– Varying demand

• Measures– Time-based

• Waiting time• Walking distance and time

– Space• Square feet/person

Airport Simulation Modeling Examples

Ontario International Airport

DFW Terminal D Parking Garage

Roadway and Curbside

• Evaluate roadway design and operation

• Performance metrics– Vehicles double- and

triple-parked– Effective system

capacity– Waiting time for shuttles,

etc.– Congestion—max

queues and total delay– Impact of ConRAC and

consolidated bussing

George Bush Intercontinental/Houston

• Objective– Assess roadway and

curbside capacity during various construction projects

• Areas Modeled– Terminal curbsides– Airport access roads

to 25-mile square area• Performance Criteria

– Roadway throughput– Vehicle delays

----> Enter Terminal C Parking GarageTerminal BTerminal A

Terminal D

Terminal C

TRACS Model

CORSIM Model

IAH Construction Phasing

IAH Roadway (CORSIM)

• System Components– Regional Freeways

• Beltway 8• US 59• Hardy Toll Road

connector– Airport Access

Roadways • JFK Blvd• Will Clayton Pkwy

IAH Roadway (TRACS)

Airport Security Changes – Explosive Detection of Checked Bags

• 100% explosive detection of checked bags• Quantify screening requirements• Quantify BHS requirements• Quantify impact of system control logic• Systems meet requirements of the Planning

Guidelines and Design Standards (PGDS) for Checked Baggage Inspection Systems (October 2007)

Baggage Operations Performance

• Critical performance measurements– Baggage connection time– Belt and system capacities– Queuing/congestion of tractors at bag room input belts– Staging requirement for baggage carts– Bottleneck operations in bag processing

Sacramento Inline BHS

Pedestrian Flow Simulation Examples

Stadium Operations

Office Campus – Construction

Office Campus – Freedom Tower

Benefits for Facility Planning

• Measure performance of proposed facility design prior to construction

• Increased granularity of planning early reduces design costs• Provide performance measures that reflect the impact of

various factors• Explicitly model interactions• Evaluate many alternatives quickly and inexpensively• Identify unexpected results and change the design before

implementation• Evaluate new approaches without risk• Integrate facilities and systems/operations effectively• Avoids embarrassing situations - helps to “GET IT RIGHT THE

FIRST TIME”

Conclusions

• Simulation analysis provides benefits to decision makers:– Very detailed, quantitative comparisons of competing

alternatives– Evaluation of hard-to-measure qualitative performance, such as

customer “Levels of Service”– Opportunity to identify and correct design flaws prior to

construction• Modeling helps owners save time and money on the

planning and implementation of facility and system design projects

• Pedestrian simulation models can be linked with other tools to analyze entire system to ensure balanced facilities

Merging Facility and Process

Thank you.

Gloria Bender Managing Principal817.359.2954 gbender@transsolutions.com