A Comparative Study on Various Methodologies and Solutions for Evaluation of Short-Range Radar to Validate the Features of Autonomous Vehicle

Autonomous vehicle is a vehicle capable of sensing its environment and taking decisions automatically with no human interventions. To achieve this goal, ADAS (Advance Driving Assistance System) technologies play an important role and the technologies are improving and emerging. The sensing of environment can be achieved with the help of sensors like Radar and Camera. Radar sensors are used in detecting the range, speed and directions of multiple targets using complex signal processing algorithms. Radar with long range and short range are widely used in the autonomous vehicles. Radar sensors with long range can be used to realize features like Adaptive Cruise Control, Advance Emergency Brake Assist. The short-range radar sensors are used for Blind Spot Monitoring, Lane Change Assist, Rear/Front Cross Traffic Alert and Occupant Safe Exit. To realize the Autonomous vehicle functionalities four short range radar sensors are required, two on front and two on rear (left and right).

This paper presents a detailed study on different solutions and methodologies for simulating radar signals and validation of short-range radar-based features. The various methodologies involve simulating of radar signals using Radar Target Simulator, Bypassing the radar sensing and injecting the radar raw signals, Bypassing the radar sensing injecting the target objects and Field and track testing in the real time environment. This paper also describes the challenges and comparison of different solutions.