Analysis of Network and Non-Network Factors on Traveler Choice Toward Improving Modeling Accuracy for Better Transportation Decisionmaking

EXECUTIVE SUMMARY

This study, collaboratively identified and prioritized by Federal Highway Administration (FHWA) Analysis, Modeling, and Simulation (AMS) experts from across the agency during three AMS research symposia, focuses on identifying accurate traveler choice data in network and non-network conditions. It seeks to address the important gap in modeling capability to support initiatives aimed at improving traffic conditions, system safety, and sustainability by targeting user choices before and during travel. The traveler choice focus area targets travelers’ higher-level, predictive, strategic choices influenced by a range of variables such as travel time reliability; congestion (recurrent and non-recurrent); environmental factors such as weather that affects both system performance as well as activity engagement opportunities, availability, and accessibility to alternative modes; quality of the walking environment; and measures such as pricing, information supply, and dynamic traffic management.

A comprehensive conceptual framework was articulated to highlight the principal behavior dimensions and how these interrelate with network performance to determine the impact and effectiveness of a wide range of demand-side and supply-side measures. Because no single modeling platform can have the scale, appropriate level of detail, and focus to address all questions and interventions, this study demonstrates improvements in modeling capability through selected case study applications. For each case study, specific modeling tools were elaborated by integrating traveler choice models in system simulation tools and applied to evaluate the effectiveness of the relevant interventions.

The case studies range from long-term policy influences of non-network interventions (namely walkability and crime) on mode choice to short-term en-route behavior of speed compliance as part of intelligent network flow optimization (INFLO) speed harmonization measures. All cases model and treat individual behavior in a completely disaggregated manner. However, depending on the focus of the intervention, scale of application, and resulting size of the problem, the case study models range from macroscopic to microscopic representation of the system. Six case studies were developed: (1) a medium-to-long-term application of urban design policy and non-network interventions, (2) active transportation and demand management (ATDM) with an emphasis on the role of non-network factors and urban policies in promoting active transportation and the use of bicycles as an alternative mode, (3) an exploratory Applications for the Environment: Real-Time Information Synthesis (AERIS)-related agent-based model of social networks and their influence on green attitudes, (4) a second AERIS case study using a microscopic traffic behavior model to evaluate the emissions benefits of an intelligent network flow application of speed harmonization in a connected vehicle environment, (5) weather responsive advanced traffic and demand management, demonstrating integration of traveler choices are integrated in a mesoscopic network wide dynamic traffic assignment (DTA) model using the Chicago, IL, network, and (6) an integrated corridor management (ICM) case study focused on characterizing travel adjustments using loop detector flow data from an integrated corridor managed site in the Seattle, WA, area.

This multifaceted research initiative cuts across several FHWA programs such as the Office of Planning, Environment, and Realty; Office of Operations; Office of Safety; and the Office of Research, Development, and Technology. This study will facilitate the implementation of a balanced, cross-cutting effort to better understand traveler choice and builds on current activities related to modeling and analysis across FHWA, professional associations, and academia.