A novel crash detection algorithm for two-wheeled vehicles

This paper presents a crash detection strategy for motorcycles, using GPS/GNSS and inertial measurements collected by telematic e-Boxes. The primary goal is to jointly minimize the access time of the emergency services and to accurately store the event dynamics for further investigation on accident's responsibilities. For motorcycles, unlike for cars, crash events cannot always be detected by monitoring abnormal longitudinal decelerations solely. Thus, this work proposes a novel method that detects and classifies the severity of crash-like situations. The proposed approach follows a new paradigm that improves the detection performance, better generalizing the motorcycle dynamics with respect to the specific vehicle and the driving style. The proposed approach has been tested and validated with experimental data, covering both motorsport and naturalistic scenarions, involving several riders, different road conditions and vehicles.