Trajectory Planning for Autonomous Vehicles on Ramp Scenarios with Gradual Curves Based on Risk Modeling

Abstract:

Ramp scenarios with gradual curves challenge the autonomous vehicles because of their irregular curvatures， diverse planar layouts， and multidimensional vehicle conflicts. This paper presents an algorithm based on the coupled "vehicle-road" risk to increase the safety of lane-changing on ramps with gradual curves. The quintic polynomial is adopted to construct a set of candidate lane-changing trajectories. The cost function is developed by risk， efficiency， and comfort indicators. Simulation tests under parallel continue curved and tapered continue curved ramps show that the proposed model improved safety performance by 13.9 % and 12.6 % under the two ramp configurations compared to earlier lane-changing algorithms based on collision detection and rule-based risk evaluation. These results showed the proposed algorithm can be applied to complicated driving scenarios to increase the trajectory safety of autonomous vehicles.