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It is necessary to examine the driver behavior in intersections since many traffic accidents occur in the area. During yellow light, drivers occasionally cause the dilemma either passing through the intersection or stopping at stop line. In this paper, using the drive recorder equipped vehicle, many incident data that occurred during yellow light has been investigated. Using the collected data, actual dangerous zone during yellow light was extracted. Because the zone is one of the targets for accident prevention, the obtained understandings are useful in considering measures for enhancing safety such as road-vehicle communications.

Although wandering phenomenon of passenger and commercial cars is often experienced on damaged and dented roads, this phenomenon has not been theoretically studied so far. The objectives of this paper are to show, using linear stability theory, how and why the wandering phenomenon occurs. Firstly, the fourth order characteristic equation of a car running on a damaged road surface, taking the cross profile into account, is derived to theoretically analyze the running stability. Secondly, according to root locus analysis of the characteristic equation, it is clearly found that the vehicle body fluctuation on dented roads is much influenced by the forward velocity, the wheel track depth, and the vehicle parameters. Thirdly, a first order preview driver model is introduced to discuss the performance of the closed-loop system of driver-vehicle during lane changes.

Highly-precise ego-localization and mapping techniques from the road shape features are key elements in order to realize an autonomous driving system for vehicle in urban area which has complex environments. The objective of this study is to develop an autonomous driving system based on mapping and ego-localization using a LIDAR. To handle curved path tracking scenario, this paper proposes a desired steering angle generator considering a constructed map using the LIDAR in real time combined with the feedback control of the preview lateral deviation. The effectiveness of the proposed control method is verified by simulation and test drives using the autonomous path tracking control system.

In Japan, the number of occupant fatalities has decreased at high ratio due to the development of passive and active safety technology in recent years. However, the pedestrian fatality is still the major proportion of fatalities according to the statistics of traffic accident. Therefore, it is important to study and develop active safety technologies which target to pedestrian. By analyzing the traffic accident statistics, narrow road in urban area is one of the dangerous parts for pedestrian. And the dangerous case that pedestrian often gets into an accident is while crossing road outside of crosswalk. This study focuses on accidents which are caused by pedestrians suddenly crossing narrow urban roads. In such cases, drivers need to drive carefully, preparing for sudden crossing or unexpected dangerous behavior of pedestrians. Therefore, it is important for drivers to predict the accident risk due to the crossing pedestrian behavior in such narrow roads.

Small size electric vehicles require active safety technology to prevent road accidents as well as protect drivers and passengers from severe damages. This paper proposes an intersection collision avoidance system by automatic electric braking utilizing in-wheel-motors of electric vehicles. The proposed vehicle control system focuses on the risk assessment in consideration of pedestrians. Consequently, a risk avoidance algorithm based on Potential Fields theory is described to handle the hazardous situations which change dynamically with pedestrian motion. Finally, the effectiveness of the autonomous driving system is verified by the experiments using the micro-scale electric vehicle. The results show that the proposed autonomous vehicle can accomplish the right turn with negotiating a moving pedestrian.