Incorporating Reliability Performance Measures into Operations and Planning Modeling Tools (2014)

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TRANSPORTATION RESEARCH BOARD WASHINGTON, D.C. 2014 www.TRB.org The Second S T R A T E G I C H I G H W A Y R E S E A R C H P R O G R A M RepoRt S2-L04-RR-1 Incorporating Reliability Performance Measures into Operations and Planning Modeling Tools Hani S. MaHMaSSani, Jiwon KiM, and Ying CHen Northwestern University YanniS StogioS and andY BriJMoHan Delcan Corporation Peter VoVSHa Parsons Brinckerhoff

Subscriber Categories Highways Operations and Traffic Management Planning and Forecasting

SHRP 2 Reports Available by subscription and through the TRB online bookstore: www.TRB.org/bookstore Contact the TRB Business Office: 202-334-3213 More information about SHRP 2: www.TRB.org/SHRP2 The Second Strategic Highway Research Program America’s highway system is critical to meeting the mobility and economic needs of local communities, regions, and the nation. Developments in research and technology—such as advanced materials, communications technology, new data collection technologies, and human factors science—offer a new oppor- tunity to improve the safety and reliability of this important national resource. Breakthrough resolution of significant trans- portation problems, however, requires concentrated resources over a short time frame. Reflecting this need, the second Strategic Highway Research Program (SHRP 2) has an intense, large-scale focus, integrates multiple fields of research and technology, and is fundamentally different from the broad, mission-oriented, discipline-based research programs that have been the mainstay of the highway research industry for half a century. The need for SHRP 2 was identified in TRB Special Report 260: Strategic Highway Research: Saving Lives, Reducing Conges- tion, Improving Quality of Life, published in 2001 and based on a study sponsored by Congress through the Transportation Equity Act for the 21st Century (TEA-21). SHRP 2, modeled after the first Strategic Highway Research Program, is a focused, time- constrained, management-driven program designed to comple- ment existing highway research programs. SHRP 2 focuses on applied research in four areas: Safety, to prevent or reduce the severity of highway crashes by understanding driver behavior; Renewal, to address the aging infrastructure through rapid design and construction methods that cause minimal disruptions and produce lasting facilities; Reliability, to reduce congestion through incident reduction, management, response, and miti- gation; and Capacity, to integrate mobility, economic, environ- mental, and community needs in the planning and designing of new transportation capacity. SHRP 2 was authorized in August 2005 as part of the Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU). The program is managed by the Transportation Research Board (TRB) on behalf of the National Research Council (NRC). SHRP 2 is conducted under a memo- randum of understanding among the American Association of State Highway and Transportation Officials (AASHTO), the Federal Highway Administration (FHWA), and the National Academy of Sciences, parent organization of TRB and NRC. The program provides for competitive, merit-based selection of research contractors; independent research project oversight; and dissemination of research results. SHRP 2 Report S2-L04-RR-1 ISBN: 978-0-309-27377-0 Library of Congress Control Number: 2014946504 © 2014 National Academy of Sciences. All rights reserved. Copyright Information Authors herein are responsible for the authenticity of their materials and for obtaining written permissions from publishers or persons who own the copy- right to any previously published or copyrighted material used herein. The second Strategic Highway Research Program grants permission to repro- duce material in this publication for classroom and not-for-profit purposes. Permission is given with the understanding that none of the material will be used to imply TRB, AASHTO, or FHWA endorsement of a particular product, method, or practice. It is expected that those reproducing material in this document for educational and not-for-profit purposes will give appropriate acknowledgment of the source of any reprinted or reproduced material. For other uses of the material, request permission from SHRP 2. Note: SHRP 2 report numbers convey the program, focus area, project number, and publication format. Report numbers ending in “w” are published as web documents only. Notice The project that is the subject of this report was a part of the second Strategic Highway Research Program, conducted by the Transportation Research Board with the approval of the Governing Board of the National Research Council. The members of the technical committee selected to monitor this project and to review this report were chosen for their special competencies and with regard for appropriate balance. The report was reviewed by the technical committee and accepted for publication according to procedures established and overseen by the Transportation Research Board and approved by the Governing Board of the National Research Council. The opinions and conclusions expressed or implied in this report are those of the researchers who performed the research and are not necessarily those of the Transportation Research Board, the National Research Council, or the program sponsors. The Transportation Research Board of the National Academies, the National Research Council, and the sponsors of the second Strategic Highway Research Program do not endorse products or manufacturers. Trade or manufacturers’ names appear herein solely because they are considered essential to the object of the report.

The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science and technology and to their use for the general welfare. On the authority of the charter granted to it by Congress in 1863, the Academy has a mandate that requires it to advise the federal government on scientific and technical matters. Dr. Ralph J. Cicerone is president of the National Academy of Sciences. The National Academy of Engineering was established in 1964, under the charter of the National Academy of Sciences, as a parallel organization of outstanding engineers. It is autonomous in its administration and in the selection of its members, sharing with the National Academy of Sciences the responsibility for advising the federal government. The National Academy of Engineering also sponsors engineering programs aimed at meeting national needs, encourages education and research, and recognizes the superior achieve- ments of engineers. Dr. C. D. (Dan) Mote, Jr., is president of the National Academy of Engineering. The Institute of Medicine was established in 1970 by the National Academy of Sciences to secure the services of eminent members of appropriate professions in the examination of policy matters pertaining to the health of the public. The Institute acts under the responsibility given to the National Academy of Sciences by its congressional charter to be an adviser to the federal government and, on its own initiative, to identify issues of medical care, research, and education. Dr. Victor J. Dzau is president of the Institute of Medicine. The National Research Council was organized by the National Academy of Sciences in 1916 to associate the broad community of science and technology with the Academy’s purposes of furthering knowledge and advising the federal government. Functioning in accordance with general policies determined by the Academy, the Council has become the principal operating agency of both the National Academy of Sciences and the National Academy of Engineering in providing services to the government, the public, and the scientific and engineering communities. The Council is administered jointly by both Academies and the Institute of Medicine. Dr. Ralph J. Cicerone and Dr. C. D. (Dan) Mote, Jr., are chair and vice chair, respectively, of the National Research Council. The Transportation Research Board is one of six major divisions of the National Research Council. The mission of the Transportation Research Board is to provide leadership in transportation innovation and progress through research and information exchange, conducted within a setting that is objective, interdisci- plinary, and multimodal. The Board’s varied activities annually engage about 7,000 engineers, scientists, and other transportation researchers and practitioners from the public and private sectors and academia, all of whom contribute their expertise in the public interest. The program is supported by state transportation departments, federal agencies including the component administrations of the U.S. Department of Transporta- tion, and other organizations and individuals interested in the development of transportation. www.TRB.org www.national-academies.org

ACKNOWLEDGMENTS This work was sponsored by the Federal Highway Administration in cooperation with the American Association of State Highway and Transportation Officials. It was conducted in the second Strategic Highway Research Program, which is administered by the Transportation Research Board of the National Academies. The project was managed by William Hyman, SHRP 2 Senior Program Officer, Reliability. SHRP 2 STAFF Ann M. Brach, Director Stephen J. Andrle, Deputy Director Neil J. Pedersen, Deputy Director, Implementation and Communications Cynthia Allen, Editor Kenneth Campbell, Chief Program Officer, Safety JoAnn Coleman, Senior Program Assistant, Capacity and Reliability Eduardo Cusicanqui, Financial Officer Richard Deering, Special Consultant, Safety Data Phase 1 Planning Shantia Douglas, Senior Financial Assistant Charles Fay, Senior Program Officer, Safety Carol Ford, Senior Program Assistant, Renewal and Safety Jo Allen Gause, Senior Program Officer, Capacity James Hedlund, Special Consultant, Safety Coordination Alyssa Hernandez, Reports Coordinator Ralph Hessian, Special Consultant, Capacity and Reliability Andy Horosko, Special Consultant, Safety Field Data Collection William Hyman, Senior Program Officer, Reliability Linda Mason, Communications Officer Reena Mathews, Senior Program Officer, Capacity and Reliability Matthew Miller, Program Officer, Capacity and Reliability Michael Miller, Senior Program Assistant, Capacity and Reliability David Plazak, Senior Program Officer, Capacity and Reliability Rachel Taylor, Senior Editorial Assistant Dean Trackman, Managing Editor Connie Woldu, Administrative Coordinator

F o r e w o r d William Hyman, SHRP 2 Senior Program Officer, Reliability The Incorporating Reliability Performance Measures into Operations and Planning Mod- eling Tools project explored how to address reliability using micro- and mesosimulation models. In addition, it provided guidance on how to address reliability in other modeling systems, namely in traditional demand forecasting models and with activity-based models coupled with dynamic traffic assignment models. Substantial advances were made in this project, both conceptually and in terms of practical products produced. This research should be of interest to those concerned with modeling travel time reliability and using the results for transportation system management and operations. The audience for the reports and products resulting from this research includes researchers, planners, traffic engineers, vendors of simulation models, consultants who work hand in hand with transportation agencies, and decision makers concerned with highway operations. Early in the project the researchers set out a framework for incorporating reliability into plan- ning and operation models that distinguishes between the demand and supply side. Travel demand may be static, as in typical planning models; dynamic for planning and operational models; or activity-based. Supply—in other words, the capacity of each part of the network— may be fixed, stochastic, or systematically varying. The SHRP 2 Reliability focus area identified seven sources of nonrecurring congestion: incidents, weather, work zones, special events, traffic control devices not working properly, unusual fluctuations in demand, and bottlenecks that can exacerbate these sources of unre- liability. These nonrecurring sources of congestion can affect supply, demand, or both; for example, work zones affect supply; special events, demand; and incidents and weather, both. These supply and demand factors influence the travel time for origin–destination (O-D) pairs across the network and, in turn, the distribution of travel time from which various reliability measures can be derived. To explain how to address reliability when using micro- and mesosimulation models, the framework was extended to distinguish between sources of nonrecurring congestion exter- nal (exogenous) to a simulation model and internal (endogenous) to it. Exogenous factors include incidents, weather, and work zones, whereas endogenous factors include heteroge- neity of driver behavior and vehicle type on the demand side and breakdown of flow, traffic control, and differences in car-following behavior on the supply side. Microsimulation models are widely used in the transportation field to understand how vehicles behave in detailed settings, such as a series of traffic signals along an arterial street, freeway onramps, or a small network of roads. Mesosimulation models are suitable for higher-resolution analysis and can be applied to networks of varying sizes, including an entire region. Both micro- and mesosimulation models are based on some form of traffic physics, in contrast to a standard four-step demand model. This project focused considerable attention on how micro- and mesosimulation models could address travel time reliability. The essence of the approach is to sandwich a simulation model between a pre- and post-processor such that together, all three components can portray travel time reliability on a network or part of it.

The researchers developed two software prototypes that were tested with both a widely used mesosimulation model and a widely used microsimulation model. The first software prototype, the Scenario Manager, consisted of the pre-processor for either type of simula- tion model. The Scenario Manager produces random scenarios involving various sources of nonrecurring congestion such as traffic incidents, weather, and work zones. It can also address scenarios based on historical data or scenarios previously constructed for planning purposes. The other software prototype is the Trajectory Processor. This post-processor determines the distribution of travel time for every O-D pair on a network. Nearly all the travel time reliability metrics, including standard deviation and the Planning Time Index, can be derived from the travel time distribution. For information about how to use the two prototypes, see their user guides. This report provides more information about the Scenario Manager and the Trajectory Processor, as well as the research. The research also produced SHRP 2 Report S2-L04-RR-1: Incorporating Reliability Perfor- mance Measures into Operations and Planning Modeling Tools: Application Guidelines, about a micro- or mesosimulation model with pre- and post-processors. Private sector software vendors may wish to closely examine the prototype software to determine the merits of incorporating similar capability into the products they have on the market. The application guidelines and user guides should help private vendors make informed decisions. It is worth noting that a similar scenario manager and procedures for compiling the dis- tribution of travel time were also developed and applied in the SHRP 2 L02 project, Incor- poration of Travel Time Reliability into the Highway Capacity Manual. The Transportation Research Board Committee on Highway Capacity and Quality of Service approved a motion to incorporate this new approach into the Highway Capacity Manual. The SHRP 2 L04 project also drew on earlier work performed in the SHRP 2 Capacity focus area under a project titled Improving our Understanding of How Highway Congestion and Pricing Affect Travel Demand (SHRP 2 C02). Reliability was introduced into succes- sively richer utility functions, beginning with the traditional variables of out-of-pocket costs and travel time, and progressively adding other variables including travel time reliability. The researchers describe how to place a value on travel time reliability given other relevant terms in the utility function and emphasize that the value of reliability is not a constant; rather, it varies with such factors as vehicle occupancy and household income. This project on incorporating reliability into planning and operation models absorbed important aspects of the earlier research performed within the SHRP 2 Capacity focus area. Finally, a substantial effort was undertaken within this project to provide guidance on how to integrate reliability into a modeling system that uses activity-based models on the demand side and a fine-grained, time-sensitive model on the supply side (e.g., a mesosimulation model). This guidance appears in the project’s reference material report (SHRP 2 Report S2-L04-RR-1: Incorporating Reliability Performance Measures into Operations and Planning Modeling Tools: Reference Material).

C O N T E N T S 1 Executive Summary 4 CHAPTER 1 Introduction 4 Objectives 4 Approach 4 Report Organization 7 PART 1 RESEARch BAckgRouNd 8 CHAPTER 2 Fundamental Issues of Incorporating Travel Time Reliability into Modeling Tools 8 Introduction 10 Incorporating Reliability into Planning and Operation Models 18 Systematic and Random Fluctuations in Travel Demand and Network Supply: Impact on Recurrent and Nonrecurrent Congestion 20 Approaches to Incorporating Travel Time Variability into Network Simulation Tools 22 CHAPTER 3 Integrating Travel Time Reliability into Planning Models 22 Specifics of ABM-DTA Equilibration Versus Aggregate Models 23 ABM-DTA Integration Principles 29 Approaches to Quantifying Reliability and Its Impacts 31 Incorporating Reliability into Demand Model 35 Incorporating Reliability into Network Simulation 36 Single-Run Versus Multiple-Run Approach 42 Technical Aspects of Scenario Formation 45 Recommendations for Future Research 47 CHAPTER 4 Functional Requirements of Stochastic Network Simulation Models 47 Introduction 47 Framework 49 Functional Requirements 51 Quantifying Travel Time Variability 52 Constructing Travel Time Distributions 54 Trajectories: A Unifying Framework 58 Model Variability and Its Sources in Traffic Simulation Tools 61 PART 2 FRAMEwoRk ANd ToolS FoR TRAvEl TIME RElIABIlITy ANAlySIS 62 CHAPTER 5 Model and data Requirements 62 Scenario Manager 63 Trajectory Processor 63 Data Requirements

66 CHAPTER 6 Scenario Manager 66 Introduction 68 Methodology for Scenario-Based Reliability Analysis Using Simulation Tools 72 Implementation of Scenario Manager 82 CHAPTER 7 Trajectory Processor 82 Introduction 83 Software Description 83 Integration with Selected Models (DYNASMART and Aimsun) 90 Travel Time Reliability Indices 93 PART 3 APPlIcATIoNS 94 CHAPTER 8 Analysis Process: Mesoscopic Models 94 Defining Scenarios 94 Generating Scenarios Using the Scenario Manager 96 Simulating Scenarios Using DYNASMART-P 96 Obtaining Reliability Statistics Using the Trajectory Processor 114 CHAPTER 9 Analysis Process: Microscopic Models 114 Study Area Description 114 Microsimulation Approach and Objective 114 Scenario Description 114 Microsimulation Travel Time Reliability Results 128 CHAPTER 10 Study Findings and conclusions 130 Implementation Steps 131 Agency Adoption 131 Developers 131 Success Factors 131 Recommendations for Further Research 133 References