Abstract
With the development of intelligent vehicle technology, the demand for advanced driver assistant systems kept increasing. To improve the performance of the active safety systems, we focused on right-turning vehicle’s collision warning and avoidance. We put forward an algorithm based on Monte Carlo simulation to calculate the collision probability between the right-turning vehicle and another vehicle (or pedestrian) in intersections. We drew collision probability curves which used time-to-collision as the horizontal axis and collision probability as the vertical axis. We established a three-level collision warning system and used software to calculate and simulate the collision probability and warning process. To avoid the collision actively when turning right, a two-stage braking strategy is applied. Taking four right-turning collision conditions as examples, the two-stage braking strategy was applied, analysing and comparing the anteroposterior curve diagram simultaneously to avoid collision actively and reduce collision probability. By comparison, the collision probability 2 s before active collision avoidance was more than 80% and the collision probability may even reach 100% in certain conditions. To improve the active safety performance, the two-stage braking strategy can reduce the collision probability from exceeding 50% to approaching 0% in 2 s and reduce collision probability to less than 5% in 3 s. By changing four initial positions, the collision probability curve calculation algorithm and the two-stage braking strategy are validated and analysed. The results verified the rationality of the collision probability curve calculation algorithm and the two-stage braking strategy.
Highlights
With the development of vehicle active safety systems, ADAS can solve traffic safety problems in challenging crashes situations. e current ADAS focuses mainly on turning left, and studying the right-turning process was important for improving traffic safety
Considering that the driver in mainland China was sitting on the left side, there was a large blind spot in the process of turning right, and the algorithm was designed by taking the right turn as an example. e right-turning condition was special and relatively complex [1] because drivers needed to give attention to pedestrians crossing the road while avoiding vehicles coming from the left side and drivers had a visual blind spot during the right-turning [2]. erefore, the right-turning condition of an intelligent vehicle was studied and analysed
Most previous studies focused on the forward collision warning (FCW) system and active collision avoidance [7]; there was a lack of research on the collisions caused by right-turning vehicles
Summary
With the development of vehicle active safety systems, ADAS can solve traffic safety problems in challenging crashes situations. e current ADAS focuses mainly on turning left, and studying the right-turning process was important for improving traffic safety. Choi and Zhao et al adopted the autonomous emergency braking (AEB) system to avoid collisions [13, 14] These studies were not combined with the intelligent vehicle’s right-turning condition. (1) At present, most previous studies focused on the forward collision warning (FCW) system and autonomous emergency braking (AEB) system; there was a lack of research on the collisions caused by right-turning vehicles. According to the algorithm based on Monte Carlo simulation to calculate the collision probability, we have improved the performance of the active safety systems, which contributed to right-turning vehicle’s collision warning and avoidance. Erefore, we calculated the probability of collision, through the warning level and active intervention to improve the safety of the right-turning process and reduce the accident rate To avoid the collision actively when turning right, a two-stage braking strategy was applied. erefore, we calculated the probability of collision, through the warning level and active intervention to improve the safety of the right-turning process and reduce the accident rate
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