| 智能汽车对无信号交叉口行人的避撞控制 |
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| 引用本文： | 潘洺铭,孙宇波,刘强.智能汽车对无信号交叉口行人的避撞控制[J].交通信息与安全,2021,39(2):19-27. |
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| 作者姓名： | 潘洺铭 孙宇波 刘强 |
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| 作者单位： | 1.中山大学智能工程学院 广州 510006 |
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| 基金项目： | 国家自然科学基金项目51675540东莞市社会科技发展重点项目20185071551596 |
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| 摘 要： | 针对智能汽车在无信号交叉口对横穿行人的避撞问题，研究了主动转向避撞控制策略。基于多层模型预测控制方法，采用分层控制策略设计局部规划层控制器与全局跟踪层控制器，在此基础上根据交叉口处汽车与行人的轨迹特征计算人车碰撞剩余时间，改进传统人工势场法构造避撞函数，规划出既能规避交叉口内存在碰撞风险的行人又能使偏差最小的局部避撞路径，并使智能汽车在满足多项动力学约束时准确跟踪参考路径，通过搭建CarSim/Simulink联合仿真平台，结合广东省2006—2018年交通事故数据库选取对交叉口人车碰撞有显著影响的因素，设计仿真场景进行仿真分析。结果表明:智能汽车能在多个初始点完成对参考路径的跟踪，控制器对不同速度和附着条件有较高的鲁棒性，高速低附着场景中，智能汽车横向加速度小于0.4 g、质心侧偏角小于2°、前轮侧偏角小于2.5°，各约束量满足舒适性和平稳性条件；4个典型交叉口场景中，智能汽车以不同速度直行或转弯通过交叉口，均能识别横穿行人中存在碰撞风险的行人实现主动转向避撞。
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| 关 键 词： | 交通安全 智能汽车 主动转向避撞 多层模型预测控制 无信号交叉口 横穿行人 |
| 收稿时间： | 2020-05-23 |
Steering Collision Avoidance Control of Intelligent Vehicles for Crossing Pedestrians at Unsignalized Intersections |
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| PAN Mingming,SUN Yubo,LIU Qiang.Steering Collision Avoidance Control of Intelligent Vehicles for Crossing Pedestrians at Unsignalized Intersections[J].Journal of Transport Information and Safety,2021,39(2):19-27. |
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| Authors: | PAN Mingming SUN Yubo LIU Qiang |
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| Affiliation: | 1.School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510006, China2.Guangdong Province Key Laboratory of Intelligent Transportation System, Guangzhou 510006, China |
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| Abstract: | An active steering collision avoidance control strategy is proposed to cope with pedestrian-vehicle collision avoidance of intelligent vehicles at unsignalized intersections. Based on the multi-layer model predictive control method, the local planning layer controller and the global tracking layer controller are designed by the hierarchical control strategy. On this basis, the remaining time of pedestrian-vehicle collision is calculated according to the trajectory characteristics of vehicles and pedestrians at intersections, and the modified traditional artificial potential field method is employed to construct the collision avoidance function. The local collision avoidance path is planned to minimize the deviation of tracking the global reference path and avoid any pedestrian-vehicle collision at intersections. By CarSim/Simulink co-simulation platform, various scenarios are designed for simulation analysis. The factors that have significant effects on pedestrian-vehicle collision at intersections are selected from the traffic accident database of Guangdong Province from 2006 to 2018. The results show that intelligent vehicles can track the reference path at different initial points, and the controllers have good robustness subjected to different speeds and adhesions. In a high-speed and low-adhesion scenario, the lateral acceleration of intelligent vehicles is less than 0.4 g; the side-slip angle is less than 2°; the front wheel yaw angle is less than 2.5°. At the four typical unsignalized intersections, intelligent vehicles at different speeds can steer to avoid collision for crossing pedestrians when going straight or turning through the intersection. |
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