Impact of the spatial distribution of CAVs on stochastic traffic oscillations in mixed traffic flow

Zeqi Xu, Yi Wang, Ronghui Liu, Yunxia Wu, Yangsheng Jiang and Zhihong Yao

Physica A: Statistical Mechanics and its Applications, 2025, vol. 677, issue C

Abstract: Existing studies have demonstrated the potential of Connected and Automated Vehicles (CAVs) to optimise traffic flow and suppress disturbances. However, most current mixed traffic flow models adopt idealised deterministic approaches for modelling Human-Driven Vehicles (HDVs), and overlook the influence of the spatial distribution of CAVs on system performance. To address these limitations, this study introduces a novel metric (i.e., platoon intensity) to quantify the spatial clustering characteristics of CAVs within mixed traffic flow. This indicator enables a unified characterisation of CAV distribution patterns across various penetration rates, and theoretical bounds on pairwise vehicle probabilities under different traffic conditions are derived accordingly. A mixed traffic flow model is further developed, incorporating stochastic car-following behaviour of HDVs, behavioural degradation of CAVs, and a constraint on maximum platoon size. By introducing stochastic differential equations, the model successfully reproduces velocity fluctuations triggered by endogenous disturbances. Based on this framework, a series of systematic numerical experiments are conducted to comprehensively analyse traffic efficiency, stability, and energy consumption under varying CAV penetration rates and spatial distribution patterns. A quantitative relationship is established between platoon intensity and macroscopic traffic performance indicators. The main findings of this paper are as follows: (1) The spatial distribution of vehicles significantly impacts macroscopic traffic performance, with maximum differences of 9.70 %, 145.20 %, and 7.58 % observed in average speed, coefficient of variation of speed, and average energy consumption, respectively. (2) At a fixed CAV penetration rate, increasing platoon intensity enhances traffic efficiency and reduces average energy consumption, but exacerbates traffic instability. This research provides theoretical insights and practical implications for future CAV deployment strategies and traffic management measures.

Keywords: Mixed traffic flow; Connected automated vehicles; Stochastic car-following model; Spatial distribution of vehicles; Platoon intensity (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437125005928
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:677:y:2025:i:c:s0378437125005928

DOI: 10.1016/j.physa.2025.130940

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 ().