Design of Integrated Risk Management-Based Dynamic Driving Control of Automated Vehicles

Abstract

This paper describes the design of a fully automated driving algorithm for automated driving in complex urban scenarios and motorways with a satisfactory safety level. The proposed algorithm consists of the following three steps: surround recognition, motion planning, and vehicle control. The surround recognition system consists of three main modules: object classification, vehicle/non-vehicle tracking and dynamic drivable area determination. All system modules utilize information from potentially commercializable sensors such as vision sensors, radars, lidar and vehicle sensors. The objective of the motion planning module is to derive an optimal trajectory as a function of time and the surround recognition results. A dynamic drivable area is represented as a complete driving corridor that leads to the destination while making sure all objects are outside the left or right corridor bounds. In the case of moving objects such as other traffic participants, their behaviors are anticipated within the dynamic drivable area. The optimal trajectory planning uses the dynamic drivable area as a safety constraint and computes a trajectory in which the vehicle stays in its safe bounds considering the driver?s pattern and characteristics based on predicted risk potential. The developed algorithm has been evaluated by computer simulation and vehicle tests on urban roads and motorways.