Exploiting Automated Planning for Efficient Centralized Vehicle Routing and Mitigating Congestion in Urban Road Networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

One of the pivotal challenges presented to urban traffic controllers is the effective utilization of the transport infrastructure, as a result of the growing urbanization and of the increasing number of vehicles. In response to this challenge, here we investigate the use of Automated Planning for reducing congestion and maximizing the exploitation of urban networks, by generating routes for the vehicles navigating through the controlled region. Empirical analysis is performed on four case studies (including maps of actual UK urban areas) with different complexities and volume of vehicles. The results demonstrate the potential of the presented approach, leading towards an intelligent navigation system, which shows to be able to provide effective personalized directions to vehicles.
Original languageEnglish
Title of host publicationProceedings of The 34th ACM/SIGAPP Symposium on Applied Computing (SAC-19)
PublisherAssociation for Computing Machinery (ACM)
Pages191-194
Number of pages4
ISBN (Print)9781450359337
DOIs
Publication statusPublished - 8 Apr 2019
EventThe 34th Association for Computing Machinery Special Interest Group on Applied Computing Symposium on Applied Computing - University of Cyprus, Limassol, Cyprus
Duration: 8 Apr 201912 Apr 2019
Conference number: 34
https://www.sigapp.org/sac/sac2019/ (Link to Conference Website)

Conference

ConferenceThe 34th Association for Computing Machinery Special Interest Group on Applied Computing Symposium on Applied Computing
Abbreviated titleSAC 2019
CountryCyprus
CityLimassol
Period8/04/1912/04/19
Internet address

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  • Cite this

    Chrpa, L., Vallati, M., & Parkinson, S. (2019). Exploiting Automated Planning for Efficient Centralized Vehicle Routing and Mitigating Congestion in Urban Road Networks. In Proceedings of The 34th ACM/SIGAPP Symposium on Applied Computing (SAC-19) (pp. 191-194). Association for Computing Machinery (ACM). https://doi.org/10.1145/3297280.3297539