Strategic Thinking and Risk Attitudes in Route Choice

This research investigates route choice behavior in networks with risky travel times and real-time information. A stated preference survey is conducted. In it subjects use a PC-based interactive map to choose routes link by link in various scenarios. The scenarios include two types of maps: the first map presents a choice between one stochastic route and one deterministic route, and the second contains real-time information and an available detour. The first type of map measures the basic risk attitude of the subject. The second type allows for strategic planning and measures the effect of this opportunity on subjects’ choice behavior. Results from each subject are analyzed to determine whether the subject planned strategically for the en route information or simply selected fixed paths from origin to destination. The full data set is used to estimate several choice models with expected travel times and standard deviations as explanatory variables. Estimation results are used to assess whether models that incorporate strategic behavior more accurately reflect route choice than do simpler path-based models.

[1]  Srinivas Peeta,et al.  A Hybrid Model for Driver Route Choice Incorporating En-Route Attributes and Real-Time Information Effects , 2003 .

[2]  Joachim Wahle.  Advanced Traveler Information Systems , 2008, Künstliche Intell..

[3]  Adaptive least-expected time paths in stochastic, time-varying transportation and data networks , 2001 .

[4]  Randolph W. Hall,et al.  The Fastest Path through a Network with Random Time-Dependent Travel Times , 1986, Transp. Sci..

[5]  Michel Bierlaire,et al.  BIOGEME: a free package for the estimation of discrete choice models , 2003 .

[6]  Moshe Ben-Akiva,et al.  Adaptive Route Choice Models in Stochastic Time-Dependent Networks , 2008 .

[7]  John N. Tsitsiklis,et al.  Stochastic shortest path problems with recourse , 1996, Networks.

[8]  Route Choice Behavior in Risky Networks with Real-Time Information , 2010 .

[9]  Song Gao,et al.  Optimal routing policy problems in stochastic time-dependent networks , 2006 .

[10]  Donald L. Fisher,et al.  The Framing of Drivers' Route Choices when Travel Time Information Is Provided under Varying Degrees of Cognitive Load , 2000, Hum. Factors.

[11]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[12]  Mohamed A. Abdel-Aty,et al.  Examination of Multiple Mode/Route-Choice Paradigms Under ATIS , 2006, IEEE Transactions on Intelligent Transportation Systems.

[13]  Elise Miller-Hooks,et al.  Adaptive least-expected time paths in stochastic, time-varying transportation and data networks , 2001, Networks.

[14]  Song Gao,et al.  Optimal adaptive routing and traffic assignment in stochastic time-dependent networks , 2005 .

[15]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[16]  Serge P. Hoogendoorn,et al.  Joint Modeling of Advanced Travel Information Service, Habit, and Learning Impacts on Route Choice by Laboratory Simulator Experiments , 2005 .

[17]  Hani S. Mahmassani,et al.  Least Expected Time Paths in Stochastic, Time-Varying Transportation Networks , 1999, Transp. Sci..

[18]  J. Prashker,et al.  Violations of Expected Utility Theory in Route-Choice Stated Preferences: Certainty Effect and Inflation of Small Probabilities , 2004 .

[19]  Hani S. Mahmassani,et al.  DYNAMICS OF COMMUTING DECISION BEHAVIOR UNDER ADVANCED TRAVELER INFORMATION SYSTEMS , 1999 .

[20]  I. Erev,et al.  Small feedback‐based decisions and their limited correspondence to description‐based decisions , 2003 .

[21]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[22]  Patrice Marcotte,et al.  Hyperpath Formulations of Traffic Assignment Problems , 1998 .

[23]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

[24]  Eran Ben-Elia,et al.  The combined effect of information and experience on drivers’ route-choice behavior , 2008 .

[25]  Hani S. Mahmassani,et al.  Analyzing heterogeneity and unobserved structural effects in route-switching behavior under ATIS: a dynamic kernel logit formulation , 2003 .

[26]  Daniele Pretolani,et al.  A directed hypergraph model for random time dependent shortest paths , 2000, Eur. J. Oper. Res..

[27]  Mohamed Abdel-Aty,et al.  Modeling drivers' diversion from normal routes under ATIS using generalized estimating equations and binomial probit link function , 2004 .

[28]  S. Travis Waller,et al.  On the online shortest path problem with limited arc cost dependencies , 2002, Networks.

[29]  Asad J. Khattak,et al.  Modeling Revealed and Stated En-Route Travel Response to Advanced Traveler Information Systems , 1996 .

[30]  A. Young.  Prospect Theory: An Analysis of Decision Under Risk (Kahneman and Tversky, 1979) , 2011 .

[31]  I. Erev,et al.  On adaptation, maximization, and reinforcement learning among cognitive strategies. , 2005, Psychological review.

[32]  Moshe Ben-Akiva,et al.  Adaptive route choices in risky traffic networks: A prospect theory approach , 2010 .