Accommodating user preferences in the optimization of public transport travel

Q Wu · JK Hartley

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Transportation Planning and Optimization Vehicle Routing Optimization Methods Transportation and Mobility Innovations

Abstract

Traffic congestion is becoming a serious problem in more and more modern cities.Encouraging more private-vehicle drivers to use public transportation is one of the most effective and economical ways to reduce the ever increasing congestion problem on the streets (Hartley and Bargiela, 2001).To make public transport services more attractive and competitive, providing travellers with individual travel advice for journeys becomes crucial.However, with the massive and complex network of a modern city, finding one or several suitable route(s) according to user preferences from one place to another is not a simple task.In this paper, the author presents and compares two solutions to accommodate public transport users' preferences.The first approach is using three different single-purpose shortest path algorithms to accommodate three different user preferences.And the second approach is using the K-shortest paths algorithm to compute a reasonable number of ranked shortest paths, with the ultimate 'most optimal' path being selected by consideration of the preferences.Some experiments have been done based on the public transportation network of Nottingham City.

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References

2000Least Expected Time Paths in Stochastic, Time-Varying Transportation Networks 2000Seamless, accessible travel: users’ views of the public transport journey and interchange 1998Least possible time paths in stochastic,time-varying networks 2004Using K-Shortest Paths Algorithms to Accommodate User Preferences in the Optimization of Public Transport Travel 2002Object-Oriented Geographic Information System Data Model for Transit Trip-Planning Systems 2000Commuting with delay prone buses

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2005Time-dependent stochastic shortest path(s) algorithms for a scheduled transportation network 2010User-Specific Web-Based Route Planning 2010Evolutionary Algorithms Find Routes in Public Transport Network with Optimal Time of Realization 2010A New Evolutionary Algorithm for Routes Generation with Optimal Time of Realization in Public Transport Network 2008Two Methods of Quasi-Optimal Routes Generation in Public Transportation Network 2018Which Traffic Simulator is Suitable for Customized Behaviors in Multi-Modal Scenarios 2019A*-guided heuristic for a multi-objective bus passenger Trip Planning Problem

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