Object Detection Probability for Highly Automated Vehicles: An Analytical Sensor Model

Modern advanced driver assistance systems (ADAS) increasingly depend on the information gathered by the vehicle’s on-board sensors about its environment. It is thus of great interest to analyse the performance of these sensor systems and its dependence on macroscopic traffic parameters. The work at hand aims at building up an analytical model to estimate the number of objects contained in a vehicle’s environmental model. It further considers the exchange of vehicle dynamics and sensor data by vehicle-to-vehicle (V2X) communication to enhance the environmental awareness of the single vehicles. Finally, the proposed model is used to quantify the improvement in the environmental model when complementing sensor measurements with V2X communication.