Analysis and development of an automatic eCall for motorcycles: a one-class cepstrum approach
This addresses the safety challenge of reducing false alarms in automatic eCall systems for motorcycles, which is an incremental improvement in a domain-specific application.
The paper tackled the problem of automatically triggering emergency calls for motorcycles after accidents by developing an algorithm that detects anomalies in time series data using cepstral analysis. The result was an algorithm tested on real driving data from ten drivers, including seven real crashes, with performance compared to existing methods.
The automatic dial of an emergency call - eCall - in response to a road accident is a feature that is gaining interest in the intelligent vehicle community. It indirectly increases the driving safety of road vehicles, but presents the technical challenge of developing an algorithm which triggers the emergency call only when needed, a non-trivial task for two-wheeled vehicles due to their complex dynamics. In the present work, we propose an eCall algorithm that detects these anomalies in the data time series, thanks to the cepstral analysis. The main advantage of the proposed approach is the direct focus on the data dynamics, solving the limits of approaches based on the analysis of the instantaneous value of some signals combination. The algorithm is calibrated and tested against real driving data of ten different drivers, including seven real crash events, and performance are compared with known methods.