Dynamic lane management and multi-layered signal priority for autonomous-rail rapid transit
Abstract
Autonomous-rail Rapid Transit (ART) presents a novel solution to urban congestion, but its efficiency is often hindered by suboptimal signal priority and inflexible lane management. This paper addresses these challenges by developing a cooperative management framework that integrates dynamic lane allocation with a multi-layered signal priority system. The framework comprises four components: (1) a dynamic lane strategy switching ART lanes between dedicated and shared use; (2) a background signal timing reserving time for ART priority and adapting to dynamic lane configurations; (3) a passive priority model to co-optimise ART schedules and signal offsets; and (4) an active priority model for real-time adjustments. Simulation results demonstrate that the unified framework enhances ART efficiency and overall network performance. The dynamic lane strategy creates moving dedicated zones for ART while increasing shared lane availability. The synergistic priority strategies reduce ART delays and increase operating speeds with only minimal impacts on general vehicles.
