Stochastic driver speed control behavior modeling in urban intersections using risk potential-based motion planning framework
Stochastic driver speed control behavior modeling in urban intersections using risk potential-based motion planning framework
复制标题
使用基于潜在风险的运动规划框架对城市交叉路口的随机驾驶员速度控制行为进行建模
DOI：
--
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
P. Raksincharoensak
中科院分区：
文献类型：
--
作者：
Y. Akagi;P. Raksincharoensak
在能见度较差的无信号交叉口，需要进行危险预测的主动驾驶，以避免与死角的其他交通参与者发生碰撞。然而，对于老年驾驶员和新手驾驶员来说，很难识别潜在的危险区域，也很难选择合适的车速安全通过路口。为了帮助此类驾驶员，可以通过基于统计方法学习专家驾驶员的驾驶数据来推荐合适的速度的驾驶员模型对于驾驶员辅助系统是有用的。该方法通过定义代表穿过十字路口、迎面驶来的车辆和行人时的制动行为的潜在风险函数，从实际驾驶数据自动估计驾驶员模型的参数。为了评估所提出的方法，收集了驾驶学校教练的驾驶数据。结果表明，估计制动行为模型的准确度（RMSE）与实际数据相比为 2.5 km/h。
In unsignalized intersections with poor visibility, proactive driving with hazard anticipation is required in order to avoid collisions with other traffic participants from a blind corner. However, for elderly drivers and novice drivers, it is difficult to recognize potential hazardous area and difficult to select an appropriate speed to pass the intersections safely. To assist such drivers, a driver model which can recommend the appropriate speed by learning driving data of expert drivers based on a statistical approach is useful for a driver assistance system. The proposed method automatically estimates parameters of the driver model from the actual driving data by defining risk potential functions for representing braking behaviors while passing through intersections, oncoming vehicles and pedestrians. To evaluate the proposed method, the driving data of instructors of a driving school are collected. The results show that the accuracy (RMSE) of the estimated braking behavior model is 2.5 km/h against the actual data.
DOI：
10.1109/icra.2012.6224996
发表时间：
2012-05
期刊：
2012 IEEE International Conference on Robotics and Automation
影响因子：
--
作者：
Ian A. Baldwin;P. Newman
通讯作者：
Ian A. Baldwin;P. Newman