Systematic methodology of multi-source information fusion for improving older drivers' safety

Drivers over the age of 65 are increasing rapidly in numbers and they are inclined to be involved in accidents frequently. In this paper, a multi-source information fusion model to improve the driving safety for older drivers is proposed. First, the influences of surrounding features, such as traffic and weather, on the driving safety are analyzed and the surrounding driving safety degree (SDSD) is proposed to represent it. Second, we analyze the effect of driving behavior characters on the driving safety and name it as the driving behavior safety degree (DBSD). Then we propose a fuzzy information fusion method to evaluate the driver safety degree (DSD) based on the evaluation results of SDSD and DBSD. The fuzzy reasoning rules can be adjusted to satisfy different drivers through analyzing the driving behavior and history traffic accident logs collected. We test our methods based on the data sets collected from the American National Highway Traffic Safety Administration (NHTSA) and the experimental results show that the proposed method is more efficient in improving the older driver's safety.