GA-based Velocity Planning Using Jerk as the Encoding Method for Autonomous Vehicles
Jing Chao Hou, Junwei Yu, Sanqing Qu, Fa Wang, Yang Zi, Guang Chen · 2019
A technique for the optimal velocity planning using the genetic algorithm for autonomous vehicles is proposed in this paper. A distance-time graph where the dynamic obstacles occupy the corresponding space will be established. Through gene coding method using jerk of genetic algorithm, the feasible distance-time curve is obtained. A fitness function comprehensively evaluates the safety, smoothness, economy, and speed performance of the curve. Through the reproduction and natural selection of several generations, the best individual is selected as the final velocity curve result. The simulation results based on PreScan show that the final velocity curve has good performance. This paper provides an intelligent, convenient and reliable solution for autonomous vehicle velocity planning.