An Artificial-Neural-Network-Based Model for Real-Time Dispatching of Electric Autonomous Taxis

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dc.contributor.author Hu, Liang
dc.contributor.author Dong, Jing
dc.contributor.author Dong, Jing
dc.contributor.department Civil, Construction and Environmental Engineering
dc.date 2021-05-09T02:57:45.000
dc.date.accessioned 2021-08-14T02:55:01Z
dc.date.available 2021-08-14T02:55:01Z
dc.date.copyright Wed Jan 01 00:00:00 UTC 2020
dc.date.issued 2020-10-22
dc.description.abstract <p>This paper presents a real-time dispatching model for electric autonomous vehicle (EAV) taxis that combines mathematical programming and machine learning. The EAV taxi dispatching problem is formulated and solved as an integer linear program that maximizes the total reward for serving customers. The optimal dispatch solutions are generated by simulating electric autonomous taxis that are dispatched by the optimization model. The artificial-neural-network-(ANN)-based model was trained using the optimization model's dispatch solutions to learn the optimal dispatch strategies. Although the dispatch decisions made by the ANN-based model are not optimal, the system's performance is very close to the optimization dispatch model in terms of customer service and taxis' operational efficiency. In addition, the ANN-based dispatch model runs much faster. By comparing with current taxis, it was found that the EAV taxis dispatched by our ANN-based model can improve operational efficiency by reducing empty travel distance. EAV taxis can also reduce fleet size by 15% while maintaining a comparable level of service with the current taxi fleet.</p>
dc.description.comments <p>This is a manuscript of an article published as Hu, Liang, and Jing Dong. "An Artificial-Neural-Network-Based Model for Real-Time Dispatching of Electric Autonomous Taxis." <em>IEEE Transactions on Intelligent Transportation Systems</em> (2020). DOI: <a href="https://doi.org/10.1109/TITS.2020.3029141" target="_blank">10.1109/TITS.2020.3029141</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/ccee_pubs/291/
dc.identifier.articleid 1295
dc.identifier.contextkey 22852927
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath ccee_pubs/291
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/JvNVQ1mv
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/ccee_pubs/291/2020_DongJing_ArtificialNeural.pdf|||Fri Jan 14 23:14:22 UTC 2022
dc.source.uri 10.1109/TITS.2020.3029141
dc.subject.disciplines Transportation Engineering
dc.subject.keywords Artificial neural network
dc.subject.keywords electric and autonomous vehicle
dc.subject.keywords integer linear program
dc.subject.keywords simulation
dc.subject.keywords taxi dispatch
dc.title An Artificial-Neural-Network-Based Model for Real-Time Dispatching of Electric Autonomous Taxis
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 02eacfea-376d-45b0-a048-1b6d00cfbf26
relation.isOrgUnitOfPublication 933e9c94-323c-4da9-9e8e-861692825f91
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