Predictive Lane-Change and Routing Coordination in Bus-Priority Mixed Traffic Corridors

TL;DR

This paper presents a network coordination framework for mixed-traffic corridors that optimizes lane-change and routing decisions for connected and automated vehicles, improving bus priority and traffic efficiency.

Contribution

It introduces a predictive, utility-driven lane-change and routing optimization method that explicitly couples network and lane-level decisions in mixed traffic environments.

Findings

Enhances bus schedule adherence in simulations.

Reduces average travel times for all vehicle types.

Maintains stable lane-change behavior without increasing maneuver frequency.

Abstract

In this paper, we investigate the coordination of vehicle maneuvers in mixed-traffic corridors where connected and automated vehicles, human-driven vehicles, and buses interact under dedicated bus lane operations. We develop a segment-based network coordination framework that jointly optimizes lane-change and routing decisions of connected and automated vehicles to improve dedicated lane utilization while preserving bus priority. The proposed framework incorporates a predictive bus-protection mechanism that restricts vehicle access to protected lane segments within a monitoring horizon, together with a utility-driven lane-change strategy that accounts for anticipated travel time gains, downstream routing feasibility, and lane-change stability. By explicitly coupling network-level routing decisions with lane-level interaction control, the method proactively mitigates conflicts on dedicated lanes before congestion effects materialize. The proposed approach is evaluated through microscopic traffic simulations in SUMO using a realistic urban corridor. Simulation results demonstrate that the framework enhances bus schedule adherence and reduces average travel times for both automated and human-driven vehicles, while maintaining stable lane-change behavior without increasing maneuver frequency.