Freeway incident detection based on set theory and short-range communication

Abstract

Freeway accidents cause grave fatalities and economic losses. Further losses of life and property can be caused by secondary accidents or rear-end chain accidents. Therefore, a quick and accurate incident detection technique is vital to improve the road safety and traffic management system performance. Based on the set theory and data collected by smartphones, a low-cost incident detection algorithm is proposed, called set theory-based freeway incident detection algorithm (SFID). If a vehicle is involved in a traffic incident, the capacity of the road segment in one direction declines significantly, whereas there are no changes in the opposite direction. SFID uses this phenomenon to infer if an incident has occurred or not. To evaluate the performance of SFID, simulations are conducted under different conditions. The results show a high detection rate, low average detection time, and low false alarm rate. Furthermore, the proposed scheme is evaluated using real Wi-Fi data. The results are in concordance with those of simulations.