Decentralized Optimization of Vehicle Route Planning - A Cross-City Comparative Study

Brionna Davis; Grace Jennings; Taylor Pothast; Ilias Gerostathopoulos; Evangelos Pournaras; Raphael E. Stern

doi:10.1109/MIC.2021.3058928

Decentralized Optimization of Vehicle Route Planning - A Cross-City Comparative Study

Brionna Davis, Grace Jennings, Taylor Pothast, Ilias Gerostathopoulos, Evangelos Pournaras, Raphael E. Stern

Civil, Environmental, and Geo- Engineering

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

The introduction of connected and autonomous vehicles enables new possibilities in vehicle routing: Knowing the origin and destination of each vehicle in the network can allow for coordinated real-time routing of the vehicles to optimize network performance. However, this relies on individual vehicles being altruistic, i.e., willing to accept alternative less-preferred routes. We conduct a study to compare different levels of agent altruism in decentralized vehicles coordination and the effect on the network-level traffic performance. This work introduces novel load-balancing scenarios of traffic flow in real-world cities for varied levels of agent altruism. We show evidence that the new decentralized optimization router is more effective with networks of high load.

Original language	English (US)
Article number	9354553
Pages (from-to)	34-42
Number of pages	9
Journal	IEEE Internet Computing
Volume	25
Issue number	3
DOIs	https://doi.org/10.1109/MIC.2021.3058928
State	Published - May 1 2021

Bibliographical note

Funding Information:
This material was based upon work supported by the National Science Foundation under Grant No. OISE-1743772.

Publisher Copyright:
© 1997-2012 IEEE.

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10.1109/MIC.2021.3058928

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Decentralized Optimization of Vehicle Route Planning - A Cross-City Comparative Study

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