An Enabling Trajectory Planning Scheme for Lane Change Collision Avoidance on Highways

This paper presents a hierarchical three-layer trajectory planning framework to realize real-time collision avoidance under complex driving conditions. This is mainly ascribed to the generation of a collision-free trajectory cluster based on the speed and the path re-planning. The upper-layer controller is to generate a reference quintic polynomial trajectory based on the Sequential Quadratic Programming by assuming mild speed and acceleration variations of the surrounding vehicles. The waypoints and time stamps can be obtained via the reference trajectory. When the assumption is invalid under complex driving conditions, the middle-layer controller would generate a Quadratic Programming-based trajectory cluster to assign different time stamps to each waypoint through time-based sampling methods. The lower-layer controller would be triggered to create a new feasible trajectory based on the path sampling if the collision avoidance requirements are not satisfied. The host vehicle will return to its original lane if no feasible time window is available to perform a lane change maneuver under the vehicle kinematics and lane change time/displacement constraints. The effectiveness of the proposed scheme is verified under various scenarios through comprehensive simulations.

I. Introduction

Autonomous vehicles (AVs) exhibit enormous potential for increasing road capacity, promoting transport safety and reducing fuel consumption [1]–[3]. Lane change is a typical and nontrivial maneuver. Inappropriate lane change maneuvers are a major cause of road accidents in highway driving environments [4], [5]. Recently, the development of Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication technologies enables the real-time acquisition of the information of all traffic participants in vicinity [6]. This can facilitate safe and feasible lane change maneuvers.