Agent-Oriented Software Engineering Challenges for Ubiquitous and Pervasive Computing Workshop

Research Article

Urban Transport planning for ubiquitous environments

  • @INPROCEEDINGS{10.1109/PERSER.2007.4283950,
        author={Mahjoub  Dridi},
        title={Urban Transport planning for ubiquitous environments},
        proceedings={Agent-Oriented Software Engineering Challenges for Ubiquitous and Pervasive Computing Workshop},
        publisher={IEEE},
        proceedings_a={AUPC},
        year={2007},
        month={8},
        keywords={},
        doi={10.1109/PERSER.2007.4283950}
    }
    
  • Mahjoub Dridi
    Year: 2007
    Urban Transport planning for ubiquitous environments
    AUPC
    IEEE
    DOI: 10.1109/PERSER.2007.4283950
Mahjoub Dridi1,*
  • 1: Laboratoire Systèmes et Transports (SET), Université de Technologie de, Belfort-Montbéliard (UTBM), 90010, Belfort Cedex, France
*Contact email: mahjoub.dridi@utbm.fr

Abstract

The main objective of Ubiquitous Computing (UC) is to provide users information and service accesses anytime and irrespective to their location. In transportation functioning, many approaches based on optimization algorithms are being employed in the development of intelligent transport systems. In particular in public transport, to guarantee a high quality of intelligent transportation planning, timetable must be optimized in order to reduce the transit time of passengers in connections and to provide users real-time and appropriate information that suits their locations and contexts. In this paper, we consider public transportation planning and especially tranfer optimization problem where the goal is to minimize the total expected waiting time of riders by coordinating transfers in the network. The methodology adopted in this work is structured in two phases: the first one consists on optimizing the transit durations in connections with consideration of fixed duration trip between consecutives stations and illimited vehicle capacity. In the second phase, we prove that the considered problem becomes difficult to solve and give a resolution approach based on genetic algorithms.