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arXiv · 2602.18056

Effect of vehicle groups on heterogeneous disordered traffic flow

Akihito Nagahama·Nichika Asai·Claudio Feliciani·Xiaolu Jia·Katsuhiro Nishinari
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Abstract

In heterogeneous disordered traffic, where various vehicle types operate without strict lane discipline, self-organized vehicle groups often emerge, but their influence remains unclear. This study examines how group prevalence and composition affect flow-density relationships using real-world trajectory data. Three Passenger Car Unit (PCU) estimation methods construct flow-density diagrams accounting for heterogeneity. Group proportion, the share of vehicles classified in groups, has a nonlinear, traffic-situation-dependent impact on flow. Moderate group proportions (30-60%) were more clearly associated with peak-flow or high-flow cases under denser traffic conditions, rather than consistently producing the highest representative flow in the median-based analysis. Comparing vehicle-count-based and PCU-based group proportions shows that normalization affects interpretation, particularly when groups consist mainly of small-PCU vehicles such as motorcycles. Lower group proportions were associated with relatively favorable flow under free-flow conditions, while entropy-based analysis shows that the association between entropy alone and speed is not consistent across traffic situations. Contrasting representative trends and extreme high-flow cases suggests that traffic at similar density and group proportion can exhibit low-efficiency and high-efficiency modes. Overall, group prevalence is important in shaping macroscopic traffic dynamics, while linking internal group composition to performance may require richer structural descriptors beyond a single entropy measure. These results imply condition-dependent bottom-up traffic control: encouraging favorable vehicle formations in denser traffic and preserving fluid leader-follower relations in free-flow traffic may improve heterogeneous traffic flow, especially with minimal infrastructure or driver-assistance technologies.

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Akihito Nagahama, Nichika Asai, Claudio Feliciani, Xiaolu Jia, Katsuhiro Nishinari. 2026-02-20. Effect of vehicle groups on heterogeneous disordered traffic flow. https://doi.org/10.1016/j.physa.2026.131866

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