Host: The Japanese Society for Artificial Intelligence
Name : The 39th Annual Conference of the Japanese Society for Artificial Intelligence
Number : 39
Location : [in Japanese]
Date : May 27, 2025 - May 30, 2025
In order to contribute to the reduction of traffic accidents, we are researching a method to capture the signs of a traffic accident and quantify the risk of an accident based on these conditions. Based on the quantified risk of accidents, we believe that this method will be useful in preventing traffic accidents by alerting drivers. Previous research has shown that traffic shockwave propagation caused by multiple vehicles braking in chain reaction is highly associated with the occurrence of traffic accidents. In this paper, we propose a risk quantification method using a marked Hawkes process with the coefficient of variation of speed as a mark, focusing on the fact that the speed in that space changes violently in a time series when traffic shockwave propagation occurs, and report the results of applying the proposed method to actual traffic probe data. As a result of evaluation on real data, we confirmed that our method can appropriately quantify accident risk according to the occurrence of traffic shockwave propagation. We also confirmed that in some cases where accidents actually occurred, the risk increased before the occurrence of the accident by capturing traffic shockwave propagation.