Optimal Multi-Sensor Selection for Driver Assistance Systems under Dynamical Driving Environment

This paper discusses the design and development of a multi-sensor selection algorithm for driver assistance systems. The multi-sensor selection problem is formulated as an optimization problem of integer linear programming. Both static and dynamic scenarios are considered in the formulation; where a static one denotes an off-line multi-sensor selection problem and a dynamic one denotes an on-line driving condition transformation problem. The objective for determining an optimal selection of sensors are in terms of guaranteed coverage, energy, bandwidth and reliability of sensors, etc. Based on a multi-sensor network architecture, different driving conditions, and driver commands, an optimal multi-sensor selection algorithm is developed for identifying the environment around the vehicle and warning the driver in real time. The selection algorithm and multiple-vehicle driving is implemented in a driving simulator software.