Is stereo vision a suitable remote sensing approach for motorcycle safety? An analysis of LIDAR, RADAR, and machine vision technologies subjected to the dynamics of a tilting vehicle.

Tilting vehicles, such as electric bicycles, motorcycles, and scooters, are increasing in popularity as a means of personal transport. From a safety viewpoint, the development of Advanced Rider Assistance Systems (ARAS) for two-wheeled vehicles is lagging behind the Advanced Driver Assistance Systems (ADAS) of other road vehicles (e.g. autonomous emergency braking implemented for passenger cars and trucks). This study is the first analysis of three remote sensing technologies adopted by ADAS, such as RADAR, LIDAR and machine vision, but from a point of view significantly different to from that used in the car industry. Our findings motivated the development of a camera-based remote sensor by the reason of the lack of technology transfer from ADAS to ARAS, which can be explained by sensor design. These considerations limiting the application of the existing automotive remote sensors to tilting vehicles. We show how to tackle these limitations by introducing related experiments.