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Operation analysis of freeway mixed traffic flow based on catch-up coordination platoon
Tongji University, China.
Tongji University, China.
RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.ORCID iD: 0000-0001-9808-1483
2022 (English)In: Accident Analysis and Prevention, ISSN 0001-4575, E-ISSN 1879-2057, Vol. 175, article id 106780Article in journal (Refereed) Published
Abstract [en]

As one of the innovative technologies of intelligent transportation systems (ITS), Connected and Autonomous Vehicles (CAVs) have been deployed gradually. Given that there will be a long transition period before reaching a fully CAVs environment, it is crucial to assess the potential impacts of CAVs on mixed traffic flow. Considering platoon formation process, this study develops a platoon cooperation strategy based on “catch-up” mechanism, and then analyzes the impact on fundamental diagram, traffic oscillation, and traffic safety within mixed traffic. Simulation results show that with an increasing market penetration rate (MPR) of CAVs, road capacity shows an increasing trend. Compared with base scenario, a clear increase in road capacity is also observed under platoon scenario. With an increasing MPR, traffic oscillation is shown to reduce largely. Furthermore, the proposed platoon strategy could dampen frequent shockwaves and shorten the propagation range of waves. Regarding traffic safety, multiple surrogate safety measures (SSMs) are used to evaluate the traffic risk: including Criticality Index Function (CIF), Potential Index for Collision with Urgent Deceleration (PICUD), and Deceleration Rate to Avoid a Crash (DRAC). With increasing MPR, collision risk identified by CIF and DRAC shows an increase tendency, while that identified by PICUD has no apparent trend. Furthermore, the platoon strategy is shown to increase the severity of traffic conflicts significantly. Overall, this study provides novel insights into CAVs deployment through the analysis of platoon strategy. 

Place, publisher, year, edition, pages
Elsevier Ltd , 2022. Vol. 175, article id 106780
Keywords [en]
Autonomous and connected vehicles, Fundamental diagram, Microscopic simulation, Traffic oscillation, Traffic safety, Accident prevention, Autonomous vehicles, Intelligent systems, Motor transportation, Risk assessment, Autonomous and connected vehicle, Market penetration, Mixed traffic flow, Penetration rates, Road capacity, Roads and streets
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:ri:diva-60054DOI: 10.1016/j.aap.2022.106780Scopus ID: 2-s2.0-85135533304OAI: oai:DiVA.org:ri-60054DiVA, id: diva2:1701089
Note

 Funding details: National Natural Science Foundation of China, NSFC, 71971160; Funding details: Science and Technology Commission of Shanghai Municipality, STCSM, 19210745700; Funding details: China Scholarship Council, CSC; Funding details: Fundamental Research Funds for the Central Universities, 22120220013; Funding text 1: This research was funded by the National Natural Science Foundation of China (Grant No. 71971160 ), the Shanghai Science and Technology Committee (Grant no. 19210745700) and the Fundamental Research Funds for the Central Universities (Grant no. 22120220013). The first author would like to thank the China Scholarship Council (CSC) for financial support and Prof. Xiaobo Qu for his supervision on the manuscript.

Available from: 2022-10-04 Created: 2022-10-04 Last updated: 2023-05-25Bibliographically approved

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