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Jam-absorption driving strategy for improving safety near oscillations in connected vehicle environment considering secondary jam

Citation

Wang, S and Li, Z and Cao, Z and Jolfaei, A and Cao, Q, Jam-absorption driving strategy for improving safety near oscillations in connected vehicle environment considering secondary jam, IEEE Intelligent Transportation Systems Magazine ISSN 1939-1390 (In Press) [Refereed Article]

DOI: doi:10.1109/MITS.2021.3050889

Abstract

This study proposed an optimal jam-absorption driving (JAD) strategy which not only prevents the original traffic oscillation but also considers the avoidance of secondary jam. We first conducted a theoretical analysis to estimate the relationship between velocity and space headway in kinematic waves. Then an optimization function was formed to minimize the system delay. A procedure for specifying the absorbing vehicle was proposed. The performance of our JAD strategy was validated in a simulation model developed pacifically for the connected and automated driving environments. The result showed that by reaching a balance between the space headways in the "slow in" and "fast out" execution stage of the JAD strategy, our optimal JAD strategy can successfully eliminate the oscillation without causing a secondary jam. The collision risks measured by surrogate safety measures were reduced by 17.96% to 47.29% during the propagation of oscillation. Our strategies outperformed some previous ones in the same traffic condition. The JAD strategy effectively improves the safety situation on freeway by eliminating traffic oscillations.

Item Details

Item Type:Refereed Article
Keywords:traffic safety, oscillation; Jam-absorption driving, connected and automated vehicles (CAVs), collision risk, driving strategy
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Autonomous agents and multiagent systems
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Artificial intelligence
UTAS Author:Cao, Z (Dr Zehong Cao)
ID Code:141888
Year Published:In Press
Deposited By:Information and Communication Technology
Deposited On:2020-12-01
Last Modified:2021-09-09
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