Analysis on driver's eye glance behavior and application to car-following model

Abstract

With increasing traffic deaths around the world, many efforts are being made to reduce traffic accidents. Most of the efforts to solve the problem are focused on the installation of road safety facilities and legislations. However, conducting on-road experiment for the purpose of evaluating the effectiveness of the proposed policy is almost impossible due to the limited resources. One of the most popular alternatives to on-road experiment is traffic simulations that can describe real traffic situations in a similar way. The problem is that conventional traffic simulations cannot describe unsafe situations, including crash or near-crash. This leads to the problem that the policies that may cause more accidents are not properly evaluated. On the other hand, one of the biggest causes of traffic accident is driver’s distraction. According to previous research, approximately 40% of accidents were caused by driver’s recognition error. Another study found that about 15% to 80% of accidents were directly or indirectly related to driver distraction. Driver’s eye glance is one of the mainly used for measure the distraction. Various researches already have proved the relationship between distraction and eye glance pattern. Based on these background, this study aims to propose a framework to combine the driver's eye glance behavior in car-following model in order to describe unsafe situation. Especially, this study focuses on the rear-end collision, which accounts for about 48% of all accidents. As a first step, factors affecting driver's eye glance behavior are selected among the assorted factors related to the driving environment. Based on these results, driving scenarios according to the eye glance pattern are derived through the decision tree analysis. The eye glance module is constructed by analyzing the driving behavior according to the eye glance behavior for each scenario. This study has contribution in suggesting a new concept of car-following model capable of describing unsafe situations. Continuous further studies are needed to develop and expand the proposed concept, which can be Used for various purposes such as policy safety evaluation.