Can Human Drivers and Connected Autonomous Vehicles Co-exist in Lane-Free Traffic? A Microscopic Simulation Perspective

Syed, Arslan Ali; Rostami-Shahrbabaki, Majid; Bogenberger, Klaus · 2025 · Crossref

DOI: 10.32388/tdmwhc

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study investigates the feasibility of Lane-Free Traffic (LFT) in mixed traffic environments containing both Connected Autonomous Vehicles (CAVs) and Human-Driven Vehicles (HDVs). While LFT promises higher road capacity and smoother flow by allowing CAVs to coordinate movements without fixed lanes, the transition phase will inevitably involve non-connected actors. The research addresses how the presence of HDVs, which prioritize self-interest over system-wide optimization, impacts LFT performance and determines the CAV penetration rate required to realize LFT benefits. The authors employ microscopic simulations on a 1 km ring road to model this interaction. HDVs are simulated using a strip-based car-following model adapted for lane-less traffic, which allows continuous lateral movement based on speed benefits. CAVs utilize a Potential Lines (PL) controller, which assigns virtual lateral paths based on desired speeds to organize traffic flow. To enhance safety, the PL controller is modified to include a safe acceleration constraint derived from the human driver model, preventing collisions that might occur if artificial repulsive forces cancel out. Additionally, the study introduces an Adaptive Potential Line (APL) controller, which dynamically forms modified PL corridors around HDVs to mitigate their disruptive effects. The results demonstrate that even a small presence of HDVs significantly degrades LFT efficiency. Specifically, a 5% penetration of HDVs reduces the maximum road capacity by 16%, while a 20% penetration nearly halves the flow compared to a fully connected scenario. The study finds that a CAV penetration rate of approximately 60% is necessary before LFT offers significant advantages over traditional all-HDV traffic. The proposed APL controller effectively mitigates these disruptions, achieving a peak traffic flow improvement of 23.6% over the standard PL controller. These findings highlight the critical challenge of mixed traffic in LFT systems and suggest that adaptive control strategies are essential for managing the adverse effects of non-connected vehicles during the transition to autonomous driving.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• traffic density