An advanced pre-trip planner with personalized information on transit networks with ATIS

The paper presents the first results of a research aiming to develop a transit trip planner to support the user with personalized pre-trip information. The first part describes the user needs and the architecture of the system. The second part deals with the modeling framework implemented to provide the best path alternatives from the traveler's utility point of view according to real-time data and personal user preferences. Finally, considerations on operative aspects based on some experimental evidences are presented.

[1]  Alan Borning,et al.  Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders , 2011 .

[2]  Brian Caulfield,et al.  An Examination of the Public Transport Information Requirements of Users , 2005, IEEE Transactions on Intelligent Transportation Systems.

[3]  Umberto Crisalli,et al.  Transit services and user information: an application of schedule-based path choice and assignment models , 2005 .

[4]  Wei-bin Zhang,et al.  Design and Implementation of a Traveler Information 1 Tool with Integrated Real-time Transit Information and 2 Multi-modal Trip Planning , 2010 .

[5]  T. Arentze,et al.  Travelers’ Preferences in Multimodal Networks: Design and Results of a Comprehensive Series of Choice Experiments , 2013 .

[6]  Jordan J. Louviere,et al.  Simple ways to estimate choice models for single consumers , 2014 .

[7]  Lei Tang,et al.  Will Psychological Effects of Real-Time Transit Information Systems Lead to Ridership Gain? , 2011 .

[8]  John M. Rose,et al.  Allowing for intra-respondent variations in coefficients estimated on repeated choice data , 2009 .

[9]  Michael Florian,et al.  Optimal strategies: A new assignment model for transit networks , 1989 .

[10]  Umberto Crisalli,et al.  Advanced trip planners for transit networks: some theoretical and experimental aspects of pre-trip path choice modeling , 2014 .

[11]  Theo A. Arentze,et al.  Adaptive Personalized Travel Information Systems: A Bayesian Method to Learn Users' Personal Preferences in Multimodal Transport Networks , 2013, IEEE Transactions on Intelligent Transportation Systems.

[12]  Mohamed Abdel-Aty,et al.  Using ordered probit modeling to study the effect of ATIS on transit ridership , 2001 .

[13]  Stefano Pallottino,et al.  Equilibrium traffic assignment for large scale transit networks , 1988 .

[14]  Alan Borning,et al.  OneBusAway: results from providing real-time arrival information for public transit , 2010, CHI.

[15]  Umberto Crisalli,et al.  A Doubly Dynamic Schedule-based Assignment Model for Transit Networks , 2001, Transp. Sci..

[16]  David A. Hensher,et al.  The Mixed Logit Model: the State of Practice and Warnings for the Unwary , 2001 .

[17]  Umberto Crisalli,et al.  The Schedule-Based Approach in Dynamic Transit Modelling: A General Overview , 2004 .

[18]  Randall G. Chapman.  An Approach to Estimating Logit Models of a Single Decision Maker's Choice Behavior , 1984 .

[19]  安川 文明,et al.  予防歯科プログラムの選考に関する Discrete Choice Analysis , 2002 .

[20]  Piet Rietveld,et al.  The Desired Quality of Integrated Multimodal Travel Information in Public Transport: Customer Needs for Time and Effort Savings , 2007 .

[21]  Umberto Crisalli,et al.  A schedule-based assignment model with explicit capacity constraints for congested transit networks , 2012 .

[22]  Kun Zhou,et al.  Traveler Information Tool with Integrated Real-Time Transit Information and Multimodal Trip Planning , 2011 .

[23]  Karl Kottenhoff,et al.  Dynamic at-stop real-time information displays for public transport: effects on customers , 2007 .