Can human drivers and connected autonomous vehicles co-exist in lane-free traffic? A microscopic simulation perspective

Recent advancements in connected autonomous vehicle (CAV) technology have sparked growing research interest in lane-free traffic (LFT). LFT envisions a scenario where all vehicles are CAVs, coordinating their movements without lanes to achieve smoother traffic flow and higher road capacity. This potentially reduces congestion without building new infrastructure. However, the transition phase will likely involve non-connected actors such as human-driven vehicles (HDVs) or independent AVs sharing the roads. This raises the question of how LFT performance is impacted when not all vehicles are CAVs, as these non-connected vehicles may prioritize their own benefits over system-wide improvements. This paper addresses this question through microscopic simulation on a ring road, where CAVs follow the potential lines (PL) controller for LFT, while HDVs adhere to a strip-based car-following model. The PL controller is also modified for safe velocities to prevent collisions. The results reveal that even a small percentage of HDVs can significantly disrupt LFT flow: 5% HDVs can reduce LFT’s maximum road capacity by 20% and a 40% HDVs nearly halves it, up until 100% HDVs where it drops by nearly 60%. The study also develops an adaptive potential line (APL) controller that forms APL corridors in the surroundings of HDVs. APL shows a peak traffic flow improvement of nearly 10% over the PL controller. The study indicates that a penetration rate of approximately 60% CAVs is required to start observing the major LFT benefits. These findings open a new research direction on minimizing the adverse effects of non-connected vehicles on LFT. • Even a small percentage of human driver vehicles (HDVs) significantly lowers the LFT flow. • The LFT traffic flow drops by 20% with just 5% HDV penetration rate. • 60% CAV Penetration rate is required before observing LFT’s major advantages. • Introduced Adaptive Potential Line (APL) controller to improve the LFT with HDVs. • A peak average improvement of nearly 10% was observed via the APL strategy over PL controller.

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Publication Details

Journal
Transportation Research Part C Emerging Technologies
Published
2025-09-23
DOI
https://doi.org/10.1016/j.trc.2025.105315
Citations
1
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
1.21
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article

Can human drivers and connected autonomous vehicles co-exist in lane-free traffic? A microscopic simulation perspective

Arslan Ali Syed, Majid Rostami-Shahrbabaki, Klaus Bogenberger
1 citations
Transportation Research Part C Emerging Technologies
Traffic control and management
1.21
article

Can human drivers and connected autonomous vehicles co-exist in lane-free traffic? A microscopic simulation perspective

Arslan Ali Syed, Majid Rostami-Shahrbabaki, Klaus Bogenberger
article en
1 citations

Abstract

Recent advancements in connected autonomous vehicle (CAV) technology have sparked growing research interest in lane-free traffic (LFT). LFT envisions a scenario where all vehicles are CAVs, coordinating their movements without lanes to achieve smoother traffic flow and higher road capacity. This potentially reduces congestion without building new infrastructure. However, the transition phase will likely involve non-connected actors such as human-driven vehicles (HDVs) or independent AVs sharing the roads. This raises the question of how LFT performance is impacted when not all vehicles are CAVs, as these non-connected vehicles may prioritize their own benefits over system-wide improvements. This paper addresses this question through microscopic simulation on a ring road, where CAVs follow the potential lines (PL) controller for LFT, while HDVs adhere to a strip-based car-following model. The PL controller is also modified for safe velocities to prevent collisions. The results reveal that even a small percentage of HDVs can significantly disrupt LFT flow: 5% HDVs can reduce LFT’s maximum road capacity by 20% and a 40% HDVs nearly halves it, up until 100% HDVs where it drops by nearly 60%. The study also develops an adaptive potential line (APL) controller that forms APL corridors in the surroundings of HDVs. APL shows a peak traffic flow improvement of nearly 10% over the PL controller. The study indicates that a penetration rate of approximately 60% CAVs is required to start observing the major LFT benefits. These findings open a new research direction on minimizing the adverse effects of non-connected vehicles on LFT. • Even a small percentage of human driver vehicles (HDVs) significantly lowers the LFT flow. • The LFT traffic flow drops by 20% with just 5% HDV penetration rate. • 60% CAV Penetration rate is required before observing LFT’s major advantages. • Introduced Adaptive Potential Line (APL) controller to improve the LFT with HDVs. • A peak average improvement of nearly 10% was observed via the APL strategy over PL controller.

Transportation Research Part C Emerging TechnologiesVol. 180
Technical University of Munich (DE)
Openalex Percentile: Top 16%
Traffic control and management
1.21
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