A Coordinated Routing Approach for Enhancing Bus Timeliness and Travel Efficiency in Mixed-Traffic Environment

TL;DR

The paper addresses preserving bus timeliness while leveraging connected and automated vehicles (CAVs) to improve overall travel efficiency in mixed-traffic urban networks. It introduces a real-time, coordinated rerouting framework that lets CAVs share existing bus-dedicated lanes (joint DLs) with buses, guided by BPR-based travel-time models and windowed, sensor-driven traffic flow estimates. A prediction-aware Dijkstra-based rerouting algorithm selects a minimal set of CAVs for route replanning to mitigate congestion without delaying buses, and SUMO-based simulations demonstrate substantial gains in bus reliability and reduced travel times for CAVs and HVs under various demand and penetration scenarios. The results highlight the practical potential of joint DL sharing and dynamic CAV routing for scalable, congestion-aware integration of automated mobility with public transit in urban settings.

Abstract

In this paper, we propose a coordinated routing strategy aimed at improving bus schedule adherence and enhancing travel efficiency for connected and automated vehicles (CAVs) operating within a mixed-traffic urban network. Our approach capitalizes on the existence of dedicated lanes for buses and CAVs, leveraging real-time traffic data to dynamically reroute CAVs in anticipation of congestion. By continuously monitoring traffic conditions on dedicated lanes and tracking the real-time positions of buses, we enable the system to proactively adjust CAV routes when potential interference with bus operations is detected. This coordination mitigates delays affecting transit services and reduces travel time for CAVs. We evaluate the proposed strategy through simulation studies conducted in the SUMO. The results demonstrate significant improvements in both transit reliability and CAV operational performance across a range of traffic conditions.

Figures (11)

• Figure 1: An example illustrating the road transportation network, where bus stations ($\mathcal{S}$) are shown by red nodes, intersections ($\mathcal{I}$) are shown in black, and the dedicated lanes are shown by red edges.
• Figure 2: Illustration of the general-purpose lane and dedicated lane.
• Figure 3: Illustration of the rerouting scheme at each intersection in DLs.
• Figure 4: Illustration of the SUMO simulation environment, where the bus is depicted in yellow, CAVs are shown in red, and HVs are shown in blue. DLs are highlighted in grey, with bus stops marked in yellow.
• Figure 5: The dynamics of the accumulated bus delay.

Theorems & Definitions (4)

• Remark 1
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• Remark 4