A Hybrid Tree Approach to Modeling Alternate Route Choice Behavior With Online Information

Chanyoung Lee · Bin Ran · Wei‐Yin Loh

25 citations0/0 files storedJournal of Intelligent Transportation Systems

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Transportation Planning and Optimization Traffic and Road Safety Traffic control and management

Abstract

One popular intelligent transportation systems (ITS) element that has been deployed in various areas of the United States is variable-message signs (VMSs). Such signs are part of advanced traveler information systems, and they can help drivers make better en route decisions regarding their trips. Unlike most other ITS elements (e.g., ramp metering, advanced signals), VMSs are not supported by mandatory regulations. Consequently, the expected benefit from implementing VMSs largely depends on the response of drivers. This study explored the factors affecting alternative route choices of car drivers with VMSs on the interstate highway system. This study adopted a method called LOTUS to analyze driver-compliance behavior with VMSs. Driver behavior under information provision through VMS data has been collected using the stated-preference approach. The study showed that travel-time saving is not the single dominant factor for driver route choice under information provision. This article explores variables that are associated with driver compliance.

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References

1997Using stated preference data for studying the effect of advanced traffic information on drivers' route choice 2003Work Travel Mode Choice Modeling with Data Mining: Decision Trees and Neural Networks 2000Content of Variable Message Signs and On-Line Driver Behavior 1996Modeling Revealed and Stated En-Route Travel Response to Advanced Traveler Information Systems 1993Exploration of route choice behavior with advanced traveler information using neural network concepts 1996Modeling Revealed and Stated Pretrip Travel Response to Advanced Traveler Information Systems 1999Drivers’ Learning and Network Behavior: Dynamic Analysis of the Driver-Network System as a Complex System 1999Effect of Information Quality on Compliance Behavior of Commuters Under Real-Time Traffic Information

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2016Extraction of attribute importance from satisfaction surveys with data mining techniques: a comparison between neural networks and decision trees 2022Influence of smartphone traffic application information on drivers’ route choice behaviours 2020Decision-making on Public Transportation Services Based on the Socio-economic, Psychological, and Environmental Concern Factors 2021Adaptive routing behavior with real-time information under multiple travel objectives

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