Identification of Human Failures in the Lane Changing Process on Expressways Based on Cepstral Analysis

Accidents can be seen as the result of an unsuccessful interplay between drivers, vehicles, traffic environments, and organizations. Human actions are an important source of vulnerability for road transportation. Current research about lane changing focuses on driving intentions. Few studies are focused on human failures during lane changing processes. In this paper, based on cepstral analysis, the characteristics of steering operation are studied to research driving failure characteristics during the lane changing processes. Then, a BP neural network model of lane changing is established to identify driving failures in lane changing processes. The identification rate of this model is 70%, which can be used to improve driving safety.