A Scoring Method for Driving Safety Credit Using Trajectory Data
This work addresses traffic safety issues for urban drivers by providing a scoring system, but it appears incremental as it adapts financial credit scoring concepts to traffic data.
The paper tackles the problem of managing traffic safety by proposing a Driving Safety Credit scoring method based on trajectory data and violation records, and verifies its effectiveness through a 40-day traffic simulation.
Urban traffic systems worldwide are suffering from severe traffic safety problems. Traffic safety is affected by many complex factors, and heavily related to all drivers' behaviors involved in traffic system. Drivers with aggressive driving behaviors increase the risk of traffic accidents. In order to manage the safety level of traffic system, we propose Driving Safety Credit inspired by credit score in financial security field, and design a scoring method using trajectory data and violation records. First, we extract driving habits, aggressive driving behaviors and traffic violation behaviors from driver's trajectories and traffic violation records. Next, we train a classification model to filtered out irrelevant features. And at last, we score each driver with selected features. We verify our proposed scoring method using 40 days of traffic simulation, and proves the effectiveness of our scoring method.