Development of a Mixed Multi-Nomial Logit Model to Capture the Impact of Information Systems on Travelers' Switching Behavior

The continuous growth of road traffic increases the delays that road users face and negatively affects the overall transportation system performance. Advanced Traveler Information Systems (ATIS) may offer significant benefits in terms of improving the travel experience of individuals, but their impact on individuals' travel behavior and on the whole transportation system mainly depends on how travelers respond to the acquired traffic information. This article presents a case study on travelers' response to traffic information for the Puget Sound Region (PSRC). The data used come from travel diaries (collected in 2000), in which individuals were asked about the traveler information sources consulted on each trip and how the information was used. Traveler information sources, available in the region, encompass both conventional forms of information, such as radio traffic reports and advanced traveler information systems, for example, variable message signs (VMS) and websites. The objective of this study is to examine the impact of information acquisition on switching travel behavior. Two models have been estimated: a multinomial logit model (MNL) and a mixed multinomial logit model (MMNL) that accounts for correlation among observations from the same individuals in the data set. The estimated models show that travel pattern characteristics, the time of information acquisition (pretrip vs. en-route), the source, and the content of provided information significantly affect commuters' response to information.

[1]  Isam Kaysi,et al.  INFLUENCE OF TRAFFIC INFORMATION ON DRIVERS' ROUTE CHOICE BEHAVIOR , 1994 .

[2]  K. G. Goulias,et al.  A decade of longitudinal travel behavior observation in the Puget Sound region: sample composition, summary statistics, and a selection of first order findings , 2003 .

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

[4]  F. Koppelman,et al.  Stated preferences for investigating commuters' diversion propensity , 1993 .

[5]  Gary Chamberlain,et al.  Analysis of Covariance with Qualitative Data , 1979 .

[6]  J Lappin,et al.  UNDERSTANDING AND PREDICTING TRAVELER RESPONSE TO INFORMATION: A LITERATURE REVIEW , 2001 .

[7]  Peter Bonsall,et al.  A COMPUTER SIMULATION GAME TO DETERMINE DRIVERS' REACTIONS TO ROUTE GUIDANCE ADVICE , 1990 .

[8]  Michel Bierlaire,et al.  Capturing correlation with subnetworks in route choice models , 2007 .

[9]  E. Molin,et al.  Use and Effects of Advanced Traveller Information Services (ATIS): A Review of the Literature , 2006 .

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

[11]  Mohamed Abdel-Aty,et al.  USING STATED PREFERENCE DATA FOR STUDYING THE EFFECT OF ADVANCED TRAFFIC INFORMATION ON DRIVERS' ROUTE CHOICE , 1997 .

[12]  D. McFadden,et al.  MIXED MNL MODELS FOR DISCRETE RESPONSE , 2000 .

[13]  M. Taniguchi,et al.  Incorporating an information acquisition process into a route choice model with multiple information sources , 1999 .

[14]  K G Goulias A DYNAMIC ANALYSIS OF ACTIVITY AND TRAVEL PATTERNS , 1999 .

[15]  Moshe Ben-Akiva,et al.  TRAVEL SIMULATORS FOR DATA COLLECTION ON DRIVER BEHAVIOR IN THE PRESENCE OF INFORMATION , 1995 .

[16]  Hussein Dia,et al.  An agent-based approach to modelling driver route choice behaviour under the influence of real-time information , 2002 .

[17]  Jane Lappin,et al.  Advanced Traveler Information Service (ATIS): Who are ATIS Customers? , 2000 .

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

[19]  L. Stalker,et al.  Does Travel Information Influence Commuter and Noncommuter Behavior?: Results from the San Francisco Bay Area TravInfo Project , 1999 .

[20]  Jeffrey L. Adler,et al.  A conflict model and interactive simulator (FASTCARS) for predicting enroute driver behavior in response to real-time traffic condition information , 1993 .

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

[22]  Serge P. Hoogendoorn,et al.  Making of Travel Choices Under Uncertainty and Information: Validation of Travel Simulator , 2006 .

[23]  Yu-Hsin Liu,et al.  Route switching behavior on freeways with the provision of different types of real-time traffic information , 2005 .

[24]  Joan L. Walker Extended discrete choice models : integrated framework, flexible error structures, and latent variables , 2001 .

[25]  Mohamed Abdel-Aty,et al.  EXPERIMENTAL ANALYSIS AND MODELING OF SEQUENTIAL ROUTE CHOICE UNDER AN ADVANCED TRAVELER INFORMATION SYSTEM IN A SIMPLISTIC TRAFFIC NETWORK , 1993 .

[26]  A. Khattak,et al.  Comparative Analysis of Spatial Knowledge and En Route Diversion Behavior in Chicago and San Francisco: Implications for Advanced Traveler Information Systems , 1998 .

[27]  Peter Bonsall,et al.  USING AN INTERACTIVE ROUTE-CHOICE SIMULATOR TO INVESTIGATE DRIVERS' COMPLIANCE WITH ROUTE GUIDANCE ADVICE , 1991 .

[28]  Michel Bierlaire,et al.  Development of Swiss models for transportation demand prediction in response to real-time traffic information , 2005 .

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

[30]  Antti Talvitie,et al.  Things planners believe in, and things they deny , 1997 .

[31]  Asad J. Khattak,et al.  Commuters' enroute diversion and return decisions: Analysis and implications for advanced traveler information systems , 1993 .

[32]  Jun Ma,et al.  A dynamic analysis of person and household activity and travel patterns using data from the first two waves in the Puget Sound Transportation Panel , 1997 .

[33]  Cheng Hsiao,et al.  Analysis of Panel Data , 1987 .

[34]  H. Mahmassani,et al.  Tripmaker choice behavior for shopping trips under real-time information: model formulation and results of stated-preference internet-based interactive experiments , 2003 .

[35]  Ian Palmer,et al.  Validating the results of a route choice simulator Transportation Research C 5 , 1997 .

[36]  Tomer Toledo,et al.  Evaluation of the Potential Benefits of Advanced Traveler Information Systems , 2006, J. Intell. Transp. Syst..

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

[38]  Peter Bonsall,et al.  Traveller Behavior: Decision-Making in an Unpredictable World , 2004, J. Intell. Transp. Syst..