Congestion-aware routing and rebalancing of Autonomous Mobility-on-Demand systems in mixed traffic

Salomón Wollenstein-Betech; Arian Houshmand; Mauro Salazar; Marco Pavone; Christos G. Cassandras; Ioannis Ch. Paschalidis

doi:10.1109/ITSC45102.2020.9294258

Congestion-aware routing and rebalancing of Autonomous Mobility-on-Demand systems in mixed traffic

Salomón Wollenstein-Betech
, Arian Houshmand
, Mauro Salazar
, Marco Pavone
, Christos G. Cassandras
, Ioannis Ch. Paschalidis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

30 Citations (Scopus)

120 Downloads (Pure)

Abstract

This paper studies congestion-aware route-planning policies for Autonomous Mobility-on-Demand (AMoD) systems, whereby a fleet of autonomous vehicles provides on-demand mobility under mixed traffic conditions. Specifically, we first devise a network flow model to optimize the AMoD routing and rebalancing strategies in a congestion-aware fashion by accounting for the endogenous impact of AMoD flows on travel time. Second, we capture reactive exogenous traffic consisting of private vehicles selfishly adapting to the AMoD flows in a user-centric fashion by leveraging an iterative approach. Finally, we showcase the effectiveness of our framework with two case-studies considering the transportation sub-networks in Eastern Massachusetts and New York City. Our results suggest that for high levels of demand, pure AMoD travel can be detrimental due to the additional traffic stemming from its rebalancing flows, while the combination of AMoD with walking or micromobility options can significantly improve the overall system performance.

Original language	English
Title of host publication	2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020
Publisher	Institute of Electrical and Electronics Engineers
Number of pages	7
ISBN (Electronic)	9781728141497
DOIs	https://doi.org/10.1109/ITSC45102.2020.9294258
Publication status	Published - 20 Sept 2020
Event	23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020 - Rhodes, Greece Duration: 20 Sept 2020 → 23 Sept 2020 https://www.ieee-itsc2020.org/

Conference

Conference	23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020
Abbreviated title	ITSC2020
Country/Territory	Greece
City	Rhodes
Period	20/09/20 → 23/09/20
Internet address	https://www.ieee-itsc2020.org/

Funding

*This work was supported by NSF under grants ECCS-1509084, DMS-1664644, CNS-1645681, IIS-1914792, and CMMI-1454737, by AFOSR under grant FA9550-19-1-0158, by ARPA-E’s NEXTCAR grant DEAR0000796, by the MathWorks, by the ONR grant N00014-19-1-2571, by the NIH grant 1R01GM135930, and by the Toyota Research Institute (TRI). This article solely reflects the opinions and conclusions of its authors and not NSF, TRI, or any other entity. We thank D. Sverdlin-Lisker, Dr. I. New and Dr. K. Solovey for proofreading this paper.

Funders	Funder number
National Science Foundation	DMS-1664644, 1645681, 1914792, IIS-1914792, CNS-1645681, CMMI-1454737, 1664644, ECCS-1509084
National Institutes of Health	1R01GM135930
Air Force Office of Scientific Research (AFOSR)	FA9550-19-1-0158

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

eess.SY
cs.SY
math.OC

Access to Document

10.1109/ITSC45102.2020.9294258

Arxiv 2003.04335v1Final author version , 0.99 MB

Cite this

Wollenstein-Betech, S., Houshmand, A., Salazar, M., Pavone, M., Cassandras, C. G., & Paschalidis, I. C. (2020). Congestion-aware routing and rebalancing of Autonomous Mobility-on-Demand systems in mixed traffic. In 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020 Article 9294258 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ITSC45102.2020.9294258

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title = "Congestion-aware routing and rebalancing of Autonomous Mobility-on-Demand systems in mixed traffic",

abstract = " This paper studies congestion-aware route-planning policies for Autonomous Mobility-on-Demand (AMoD) systems, whereby a fleet of autonomous vehicles provides on-demand mobility under mixed traffic conditions. Specifically, we first devise a network flow model to optimize the AMoD routing and rebalancing strategies in a congestion-aware fashion by accounting for the endogenous impact of AMoD flows on travel time. Second, we capture reactive exogenous traffic consisting of private vehicles selfishly adapting to the AMoD flows in a user-centric fashion by leveraging an iterative approach. Finally, we showcase the effectiveness of our framework with two case-studies considering the transportation sub-networks in Eastern Massachusetts and New York City. Our results suggest that for high levels of demand, pure AMoD travel can be detrimental due to the additional traffic stemming from its rebalancing flows, while the combination of AMoD with walking or micromobility options can significantly improve the overall system performance. ",

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Wollenstein-Betech, S, Houshmand, A, Salazar, M, Pavone, M, Cassandras, CG & Paschalidis, IC 2020, Congestion-aware routing and rebalancing of Autonomous Mobility-on-Demand systems in mixed traffic. in 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020., 9294258, Institute of Electrical and Electronics Engineers, 23rd IEEE International Conference on Intelligent Transportation Systems, ITSC 2020, Rhodes, Greece, 20/09/20. https://doi.org/10.1109/ITSC45102.2020.9294258

Congestion-aware routing and rebalancing of Autonomous Mobility-on-Demand systems in mixed traffic. / Wollenstein-Betech, Salomón; Houshmand, Arian; Salazar, Mauro et al.
2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020. Institute of Electrical and Electronics Engineers, 2020. 9294258.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Salazar, Mauro

AU - Pavone, Marco

AU - Cassandras, Christos G.

AU - Paschalidis, Ioannis Ch.

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AB - This paper studies congestion-aware route-planning policies for Autonomous Mobility-on-Demand (AMoD) systems, whereby a fleet of autonomous vehicles provides on-demand mobility under mixed traffic conditions. Specifically, we first devise a network flow model to optimize the AMoD routing and rebalancing strategies in a congestion-aware fashion by accounting for the endogenous impact of AMoD flows on travel time. Second, we capture reactive exogenous traffic consisting of private vehicles selfishly adapting to the AMoD flows in a user-centric fashion by leveraging an iterative approach. Finally, we showcase the effectiveness of our framework with two case-studies considering the transportation sub-networks in Eastern Massachusetts and New York City. Our results suggest that for high levels of demand, pure AMoD travel can be detrimental due to the additional traffic stemming from its rebalancing flows, while the combination of AMoD with walking or micromobility options can significantly improve the overall system performance.

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ER -

Wollenstein-Betech S, Houshmand A, Salazar M, Pavone M, Cassandras CG, Paschalidis IC. Congestion-aware routing and rebalancing of Autonomous Mobility-on-Demand systems in mixed traffic. In 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020. Institute of Electrical and Electronics Engineers. 2020. 9294258 doi: 10.1109/ITSC45102.2020.9294258

Congestion-aware routing and rebalancing of Autonomous Mobility-on-Demand systems in mixed traffic

Abstract

Conference

Funding

UN SDGs

Keywords

Access to Document

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