Risk Analysis for Cooperation Between the Driver and the Control System of an Autonomous Vehicle

Abstract

Autonomous vehicles will be a reality in our society shortly, first coming vehicle will come with level 3 of automation where the driver is expected to be available for occasional control either for pleasure or during critical situations. This article proposes a strategy that aims to predict the path desired by the driver through steering actions and the algorithms used by of the autonomous vehicle to utilize risk indicators. These risk indicators can be used to condition the cooperation and the transition from automatic to manual driving. This technique uses the data of a path model predictive controller and local path planning data based on a curvilinear space to predict the driver interaction and intention when he engages the steering wheel. Some results are presented in a processor-in-the-loop environment, which let to verify that driver intention can be integrated with the risk analysis of the autonomous vehicle with minimal computational cost. Some conclusions and future improvements to the system are proposed.