Statistical mechanics-inspired framework for studying the effects of mixed traffic flows on highway congestion

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

2 Citations (Scopus)

Abstract

Intelligent vehicles equipped with adaptive cruise control (ACC) technology have the potential to significantly impact the traffic flow dynamics on highways. Prior work in this area has sought to understand the impact of intelligent vehicle technologies on traffic flow by making use of mesoscopic modeling that yields closed-form solutions. However, this approach does not take into account the self-organization of vehicles into clusters of different sizes. Consequently, the predicted absence of a large traffic jam might be inadvertently offset by the presence of many smaller clusters of jammed vehicles. This study - inspired by research in the domain of statistical mechanics - uses a modification of the Potts model to study cluster formation in mixed traffic flows that include both human-driven and ACC-enabled vehicles. Specifically, the evolution of self-organized traffic jams is modeled as a non-equilibrium process in the presence of an external field and with repulsive interactions between vehicles. Monte Carlo simulations of this model at high vehicle densities suggest that traffic streams with low ACC penetration rates are likely to result in larger clusters. Vehicles spend significantly more time inside each cluster for low ACC penetration rates, as compared to streams with high ACC penetration rates.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5402-5407
Number of pages6
ISBN (Print)9781479932726
DOIs
StatePublished - Jan 1 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2014 American Control Conference, ACC 2014
CountryUnited States
CityPortland, OR
Period6/4/146/6/14

Fingerprint

Statistical mechanics
Adaptive cruise control
Intelligent vehicle highway systems
Potts model

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Jerath, K., Ray, A., Brennan, S. N., & Gayah, V. V. (2014). Statistical mechanics-inspired framework for studying the effects of mixed traffic flows on highway congestion. In 2014 American Control Conference, ACC 2014 (pp. 5402-5407). [6858835] (Proceedings of the American Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2014.6858835
Jerath, Kshitij ; Ray, Asok ; Brennan, Sean N. ; Gayah, Vikash Varun. / Statistical mechanics-inspired framework for studying the effects of mixed traffic flows on highway congestion. 2014 American Control Conference, ACC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 5402-5407 (Proceedings of the American Control Conference).
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Jerath, K, Ray, A, Brennan, SN & Gayah, VV 2014, Statistical mechanics-inspired framework for studying the effects of mixed traffic flows on highway congestion. in 2014 American Control Conference, ACC 2014., 6858835, Proceedings of the American Control Conference, Institute of Electrical and Electronics Engineers Inc., pp. 5402-5407, 2014 American Control Conference, ACC 2014, Portland, OR, United States, 6/4/14. https://doi.org/10.1109/ACC.2014.6858835

Statistical mechanics-inspired framework for studying the effects of mixed traffic flows on highway congestion. / Jerath, Kshitij; Ray, Asok; Brennan, Sean N.; Gayah, Vikash Varun.

2014 American Control Conference, ACC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 5402-5407 6858835 (Proceedings of the American Control Conference).

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

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Jerath K, Ray A, Brennan SN, Gayah VV. Statistical mechanics-inspired framework for studying the effects of mixed traffic flows on highway congestion. In 2014 American Control Conference, ACC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 5402-5407. 6858835. (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2014.6858835