Modeling and analysis of car-following models incorporating multiple lead vehicles and acceleration information in heterogeneous traffic flow
Ziyu Cui,
Xiaoning Wang,
Yusheng Ci,
Changyun Yang and
Jia Yao
Physica A: Statistical Mechanics and its Applications, 2023, vol. 630, issue C
Abstract:
In the foreseeable future, a complex heterogeneous traffic environment will emerge as Connected and Autonomous Vehicles (CAVs) coexist with Human-driven Vehicles (HDVs). Consequently, understanding the impact of CAVs on car-following behavior and the operational characteristics of heterogeneous traffic flow becomes crucial before their widespread deployment. To tackle this challenge, this research proposes an improved car-following model based on the Intelligent Driver Model (IDM). The model incorporates the position, velocity, and acceleration information of both front and sub-front vehicles in the heterogeneous traffic flow. The impact of different types of information on the model's stability is verified through linear stability analysis while investigating the operational characteristics of traffic flow during vehicle start-up. Additionally, the car-following modes are classified based on the type of leading vehicle, and the corresponding following model is formulated. The results indicate that the improved model significantly improves traffic flow stability, particularly when considering acceleration information. Compared to the front vehicle, the influence of the sub-front vehicle on traffic flow stability is less significant, but their combined impact yields positive effects. Furthermore, the improved model reduces the start-up time of vehicles at signalized intersections by 7.9% and enables a smoother start-up process for vehicles. Moreover, CAVs can mitigate the impact of HDV's disturbances on the overall heterogeneous fleet operation by adjusting their spacing relative to the front vehicle. With an increasing penetration rate, the velocity fluctuation of the entire fleet decreases.
Keywords: Car-following model; Heterogeneous traffic flow; Acceleration information; Stability analysis; Penetration rate (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437123008142
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:630:y:2023:i:c:s0378437123008142
DOI: 10.1016/j.physa.2023.129259
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 ().