Driving strategy of connected and autonomous vehicles based on multiple preceding vehicles state estimation in mixed vehicular traffic

Heng Ding, Hao Pan, Haijian Bai, Xiaoyan Zheng, Jin Chen and Weihua Zhang

Physica A: Statistical Mechanics and its Applications, 2022, vol. 596, issue C

Abstract: In the near future, connected and autonomous vehicles (CAVs) will share road space with human-driven vehicles (HVs). In this mixed vehicular traffic, effective following cooperation among multiple vehicles is an important basis for improving traffic efficiency and safety. However, CAVs are unable to communicate with HVs to acquire information. Therefore, how to obtain HV information and realize cooperative car-following has become an urgent problem for CAVs. This paper proposes a CAV driving strategy that considers multiple preceding vehicles, including HVs. The strategy first uses a large amount of real car-following data to build an upgraded Elman neural network (ENN) model optimized with the sparrow search algorithm (SSA), which is utilized to obtain HV information. Then, we combine the SSA-ENN with the classical car-following model and use a time-varying weighting model to analyze the impact of the different states of multiple preceding cars at various moments on the host car, so as to achieve car-following driving control. Numerical simulations are carried out, and the results show that the driving strategy can improve road capacity and suppress traffic oscillations. With the increase in CAV penetration, traffic efficiency, safety, and driving comfort are improved accordingly.

Keywords: Mixed vehicular traffic; Car-following driving control; Connected and autonomous vehicles; Elman neural network; Sparrow search algorithm (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437122001686
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:596:y:2022:i:c:s0378437122001686

DOI: 10.1016/j.physa.2022.127154

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().