Current UMTC Research Projects
Route Choice in a Risky Traffic Network: Econometric vs. Process Modeling Paradigms

Dr. Song Gao, Principal Investigator
University of Massachusetts/Amherst

Abstract:
Unreliable travel times come from sources such as incidents, bad weather, special events, work zones and fluctuating demand, and are a major obstacle to an efficient and reliable transportation system. The accurate modeling of travelers. route choice decision-making when faced with unreliable (risky) travel times is necessary for the assessment of policies aimed at improving travel time reliability. Econometric (random utility) models are the generally accepted paradigm for choice modeling in transportation, and tackle the problem with various adjustments, ranging from simply adding a risk measure (e.g., travel time standard deviation) to the utility function, to a probabilistic version of the cumulative prospect theory that captures non-linear subjective perceptions of both probabilities and outcomes. However, one area in decision theory that is missing in travel behavior modeling is the process modeling paradigm, which aims to capture a decision maker.s actual decision process, usually with fast and frugal heuristics, rather than correlating the decisions with explanatory variables through complicated mathematical formula. The objectives of this study thus are to: 1) Provide a comprehensive literature review of decision theory under risk in economics and psychology and their applications in transportation; 2) Develop a process model for route choice decision with risky travel times and estimate such a model using previously collected SP (stated preference) data; 3) Conduct a comprehensive comparison of the econometric and process modeling paradigms, in terms of data fitting, prediction accuracy, and frugality. The study will contribute to the literature by operationalizing a process model for route choice in a risky network and informing the transportation community of the comparative values of either modeling paradigm.

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