Autonomous Vehicle front steering control computation saving

TL;DR

This paper proposes a control computation saving method for autonomous vehicle steering, using interlacing implementation to reduce processing load while maintaining effective lane keeping and path tracking.

Contribution

It introduces an interlacing implementation technique to reduce controller computation load in autonomous vehicle steering control systems.

Findings

Real path tracking demonstrates the method's viability.

Controller computation load is effectively reduced.

The approach maintains lane keeping performance.

Abstract

For autonomous vehicles lane keeping purposes it is crucial to control the vehicle yaw rate. As it is known a vehicle yaw rate control can be achieved handling the steering angle. One option is to consider a robust controller and depending of the requirements the synthesis can drive to a high order controller. Nowadays this kind of vehicles needs a networked based control (IVN -Intelligent Vehicle Network-)with a considerable amount of control loops for different vehicle components. Therefore, in this environment the controllers computation saving could be a good option for unload the network and digital processors. That is the main target of this contribution; in order to accomplish this goal a interlacing implementation technique is considered. Results in a real path tracking illustrates viability of this procedure.