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Optimizing Bus Operations at Autonomous Intersection With Trajectory Planning and Priority Control
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AI
DOI：10.1109/TITS.2024.3395280.png)
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Abstract
En 中文
Existing studies on Autonomous Intersection Management (AIM) primarily focus on regular vehicles (e.g., cars), while ignoring bus priority demands. This paper aims to optimize the bus operations at autonomous intersection with trajectory planning and priority control. First, an intersection trajectory planning approach is proposed for turning movements within the intersection considering significant passenger volume and large size of buses. A two-stage trajectory planning method is adopted that employs a combination of transition and circular curves to ensure the smooth turning movements for vehicles within the intersection. Next, a bus priority control model for autonomous intersection (AIM-BP) is developed to minimize weighted combinations of total bus delay and car delay. In particular, the model incorporates the introduction of the dynamic bus lane designed to clear the vehicles in front of buses, thereby creating a relatively exclusive space for the buses. The proposed model simultaneously optimizes the lane choice on the road section, the route choice within the intersection and the time to enter the intersection for each vehicle, while determining whether to deploy the dynamic bus lane and which lane serves as the dynamic bus lane in the approach. The model is formulated as a Mixed Integer Linear Programming (MILP) problem, compiled in AMPL (A Mathematical Programming Language) and solved by CPLEX. Results demonstrate significant reductions in average bus delay and passenger delay under the proposed model, and sensitivity analysis further examines its effectiveness.
Keywords:
Automobiles
Trajectory
Delays
Turning
Trajectory planning
Mathematical models
Vehicle dynamics
Autonomous intersection management
bus trajectory design
dynamic bus lane
bus priority control
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