Use of Private Probe Data in Route Choice Analysis to Explore Heterogeneity in Drivers' Familiarity with Origin–Destination Pairs

An exploratory analysis about the effect on route choice of heterogeneity in driver familiarity with origin–destination (O-D) pairs was carried out. This analysis was based on probe data collected by private vehicles in Toyota, Japan. The hypothesis test results showed that route choice behavior changed in relation to the level of familiarity with O-D pairs. Two specifications of choice models were proposed to consider the effect of familiarity. The estimation results showed that the models that considered familiarity fit the data better and suggested that trips between more familiar O-D pairs had larger error variances and less sensitivity to explanatory variables. The estimated models were applied to a specific choice situation, and the prediction results showed the potential biases introduced by not considering the heterogeneity in the familiarity with O-D pairs. In addition, when traveling between more familiar O-D pairs, drivers were less sensitive to the intersection count than to the free travel time.

[1]  Takayuki Morikawa,et al.  Analysis of mode and walk-route choice in a downtown area considering heterogeneity in trip distance , 2012 .

[2]  Carlo G. Prato,et al.  Route choice modeling: past, present and future research directions , 2009 .

[3]  Piet H. L. Bovy,et al.  On Modelling Route Choice Sets in Transportation Networks: A Synthesis , 2009 .

[4]  T Lotan,et al.  Effects of familiarity on route choice behavior in the presence of information , 1997 .

[5]  Michael Scott Ramming,et al.  NETWORK KNOWLEDGE AND ROUTE CHOICE , 2002 .

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

[7]  Daniel McFadden,et al.  Modelling the Choice of Residential Location , 1977 .

[8]  Michel Bierlaire,et al.  Route choice modeling with network-free data , 2008 .

[9]  Moshe Ben-Akiva,et al.  Activity Based Travel Demand Model Systems , 1998 .

[10]  Shlomo Bekhor,et al.  Evaluation of choice set generation algorithms for route choice models , 2006, Ann. Oper. Res..

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

[12]  Tomio Miwa,et al.  Preliminary Analysis on Dynamic Route Choice Behavior Using Probe-Vehicle Data , 2005 .

[13]  Mark D. Uncles,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1987 .

[14]  S. Morris COWLES FOUNDATION FOR RESEARCH IN ECONOMICS , 2001 .

[15]  Jing Zhou,et al.  A decision-making rule for modeling travelers' route choice behavior based on cumulative prospect theory , 2011 .

[16]  Samer Madanat,et al.  ANALYSIS OF STATED ROUTE DIVERSION INTENTIONS UNDER ADVANCED TRAVELER INFORMATION SYSTEMS USING LATENT VARIABLE MODELING , 1995 .

[17]  Erel Avineri,et al.  A Cumulative Prospect Theory Approach to Passengers Behavior Modeling: Waiting Time Paradox Revisited , 2004, J. Intell. Transp. Syst..

[18]  Jeffrey L. Adler,et al.  IN-LABORATORY EXPERIMENTS TO INVESTIGATE DRIVER BEHAVIOR UNDER ADVANCED TRAVELER INFORMATION SYSTEMS (ATIS) , 1993 .

[19]  M. Bierlaire,et al.  Sampling of Alternatives for Route Choice Modeling , 2009 .

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

[21]  Jianhe Du,et al.  Modeling Stated and Revealed Route Choice: Consideration of Consistency, Diversion, and Attitudinal Variables , 2006 .

[22]  Chandra R. Bhat,et al.  Incorporating Observed and Unobserved Heterogeneity in Urban Work Travel Mode Choice Modeling , 2000, Transp. Sci..

[23]  C. Giacomo Latent variables and route choice behavior , 2012 .

[24]  J. Louviere,et al.  The Role of the Scale Parameter in the Estimation and Comparison of Multinomial Logit Models , 1993 .

[25]  T. Gärling,et al.  Spatial Behavior in Transportation Modeling and Planning , 2001 .

[26]  Dominik Papinski,et al.  Exploring the route choice decision-making process: A comparison of planned and observed routes obtained using person-based GPS , 2009 .

[27]  C. Chorus Regret theory-based route choices and traffic equilibria , 2012 .

[28]  Chandra R. Bhat,et al.  Accommodating variations in responsiveness to level-of-service measures in travel mode choice modeling , 1998 .

[29]  D. Hensher Handbook of Transport Geography and Spatial Systems , 2004 .