Feature Oriented Optimal Sensor Selection and Arrangement for Perception Sensing System in Automated Driving

The recent proliferation of perception sensing and computing technologies has promoted the rapid development of automated driving. The design of the perception sensing system has nonnegligible influences both on the performances of various automated driving features and on the system costs. This paper proposes an automated driving feature oriented framework for automatic selection and arrangement of the sensors in the perception sensing system. An automated driving feature oriented optimization model is built considering the characteristics and requirements of the specific feature and a genetic algorithm based design method is provided to solve this optimization model. Furthermore, the Adaptive Cruise Control feature and the Automated Parking Assistance feature are selected as the simulation cases to verify the effectiveness of the proposed method. The proposed method has prospective potential to provide an automatic generation framework for the sensor selection and arrangement scheme of the perception sensing system, with different orientations in terms of the automated driving features and levels.