Work

A platoon-centric approach to the capacity analysis of mixed traffic comprising connected and autonomous vehicles

Year: 2025

Type: article

Abstract: The study of mixed traffic capacity, involving both Connected and Autonomous Vehicles (CAVs) and Human-driven Vehicles (HVs), remains a critical area of research. Traditional models have typically focused on individual vehicles, while this research shifts the focus to platoons as the fundamental units of analysis to better capture the platooning characteristics of CAVs. Specifically, we introduce a new metric, the Inter-Platoon Platooning Intensity (IPI), to facilitate the analysis of mixed traffic capacity. Through both mathematical and numerical investigations, we evaluate the impact of the proposed IPI and Maximum Platoon Size (MPS) on mixed traffic dynamics. Our findings indicate that: (1) the IPI effectively measures the clustering of CAVs in a single-lane mixed traffic environment; (2) the calculated mixed traffic capacity closely matches the actual traffic capacity, showing only minor deviations; (3) the marginal analysis demonstrates the conditions under which mixed traffic capacity correlates monotonically with either MPS or IPI; and (4) an optimal MPS is determined that maximizes mixed traffic capacity. These insights contribute significantly to the existing literature on the effects of platoon size and platooning intensity on mixed traffic flow.

Source: Transportation Research Part C Emerging Technologies

DOI: 10.1016/j.trc.2025.105170

Authors: Peilin Zhao, Yiik Diew Wong, Feng Zhu

Institution: Nanyang Technological University

Language: English

Topic: Traffic control and management

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $4,040