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Technical Seminar on “ Modeling Heterogeneous Risk-Taking Behavior in Route Choice: A Stochastic Dominance Approach”
Department of Civil Engineering and Institute of Transport Studies, HKU and
Hong Kong Society for Transportation Studies
Date: 22 March 2011 (Tuesday)
Time: 6:00 pm to 7:00 pm
Venue: Room 6-12B, Haking Wong Building, The University of Hong Kong
Yu (Marco) Nie is Assistant Professor of Civil and Environmental Engineering at Northwestern University. He received his B.S. in Structural Engineering from Tsinghua University (Beijing) and his Ph.D. in Transportation Engineering from the University of California, Davis. Dr. Nie's research covers a variety of topics in the areas of transportation systems analysis, traffic simulation and traffic flow theory. He has extensive experience in developing software tools for various transportation applications. Currently Dr. Nie is a member of the TRB committee on Transportation Network Modeling (ADB30), TRB committee on Traffic Flow Theory and Characteristics (AHB45) and the Editorial Advisory Board of the Journal of Transportation Research Part B. He has also served as an ad-hoc reviewer for a variety of transportation journals, and as review panelists for National Science Foundation. Dr. Nie's research has been supported by National Science Foundation, US Department of Transportation, Federal Highway Administration (FHWA), and Illinois Department of Transportation.
Transportation systems are affected by uncertainties of various sorts. As a result, reliability has become a critical dimension in user experience of transportation services. On one hand, lack of reliability either encourages overly conservative risk-averse behavior or leads to uncomfortable, sometimes disastrous, disruptions to personal and business schedules. On the other hand, users' risk-taking behavior in presence of uncertainties may collectively affect the "equilibrium" of traffic in the system, and hence the design and operational decisions.
In this talk, a unified approach is proposed to model heterogonous risk-taking behavior in route choice based on the theory of stochastic dominance (SD), a tool widely used in finance and economics. We show that, the paths preferred by travelers of different risk-taking preferences can be obtained by enumerating the corresponding SD-admissible paths, and that general dynamic programming can be employed to generate these paths. The relationship between the SD theory and several route choice models found in the literature is also discussed. These route choice models employ a variety of indexes to measure reliability, which often makes the problem of finding optimal paths intractable. We show that the optimal paths with respect to these reliability indexes often belong to one of the three SD-admissible path sets. This finding offers not only an interpretation of risk-taking behavior consistent with the SD theory for these route choice models, but also a unified and computationally viable solution approach through SD-admissible path sets, which are usually small and can be generated without having to enumerate all paths.
We also introduce two applications of the stochastic dominance approach. In the first, the first-order SD is used to solve the percentile user-equilibrium traffic assignment problem, in which travelers are assumed to choose routes to minimize the percentile travel time, i.e. the travel time budget that ensures their preferred probability of on-time arrival. The second application considers the optimal path problems with second-order stochastic dominance constraints, which arise when travelers are concerned with the tradeoff between the risks associated with random travel time and other travel costs. Risk-averse behavior is embedded in such problems by requiring the random travel times on the optimal paths to stochastically dominate that on a benchmark path in the second order. For each application, we give a formulation and briefly discuss solution algorithms.
ALL ARE WELCOME.
Enquiries: No registration is required. For enquiries, please contact Dr Tony Sze, (T) 2859-2662, (F) 2517-0124, (E) email@example.com
Free parking is available at HKU. To be eligible for free parking, please bring along your parking ticket to the Lecture Venue for validation.
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