Exploring the impact of automated vehicles lane-changing behavior on urban network efficiency

TL;DR

This study investigates how automated lane-changing behavior in autonomous vehicles affects urban network efficiency, revealing modest performance declines as AV penetration increases due to more cautious lane-changing strategies.

Contribution

First to isolate and analyze the effects of automated lane-changing behavior on urban traffic efficiency using microsimulation with controlled AV characteristics.

Findings

Travel times increase with higher AV penetration.

Average speeds decrease as AVs adopt more cautious lane-changing.

Network capacity diminishes as AV penetration rises.

Abstract

While automated vehicle (AV) research has grown steadily in recent years, the impact of automated lane changing behavior on transportation systems remains a largely understudied topic. The present work aims to explore the effects of automated lane changing behavior on urban network efficiency as the penetration rate of AVs increases. To the best of the authors knowledge, this represents the first attempt to do so by isolating the effects of the lane changing behavior; this was obtained by considering AVs with automated lateral control, yet retaining the same longitudinal control characteristics of conventional vehicles (CV). An urban road network located in Hannover, Germany, was modeled with the microsimulation software SUMO, and several scenarios were analyzed, starting from a baseline with only CVs and then progressively increasing the AV penetration rate with 10% increments. Results highlight a modest, but statistically significant, decrease in system performance, with travel times increasing, and average speed and network capacity decreasing, as penetration rates increase. This was likely caused by a more prudent behavior of AVs, which accepted larger gaps than CVs when performing lane changing maneuvers.