| 基于激光雷达的纵向坡路动态可行驶性预测（双语出版） |
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| 引用本文： | 赵健,李雅欣,朱冰,孙博华,李至轩.基于激光雷达的纵向坡路动态可行驶性预测（双语出版）[J].中国公路学报,2019,32(6):147-157. |
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| 作者姓名： | 赵健 李雅欣 朱冰 孙博华 李至轩 |
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| 作者单位： | 1. 吉林大学 汽车仿真与控制国家重点实验室, 吉林 长春 130025;2. 吉林大学 汽车工程学院, 吉林 长春 130025 |
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| 基金项目： | 国家重点研发计划项目（2018YFB0105100）；国家自然科学基金项目（51575225，51775235）；吉林大学高层次科技创新团队项目（2017TD-20） |
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| 摘 要： | 为解决智能汽车在含有纵向坡路的环境中行驶时所涉及的环境感知与路面可行驶性理解问题，提出了一种基于激光雷达的动态、不确定性路面可行驶性预测方法。首先，利用PreScan，CarSim与MATLAB软件搭建虚拟行驶环境，并建立激光雷达物理模型提高虚拟点云的保真度。其次，进行基于激光雷达的动态可行驶性研究，利用路面激光雷达点云数据基于车辆未来行驶方向建立笛卡尔坐标系下的间隔栅格地图；在间隔内进行平面拟合得到路面的法向量，利用平面法向量计算路面纵向坡角并利用车辆姿态补偿得到大地坐标系下的间隔坡角和道路轮廓信息，并探讨天气对道路轮廓估计结果的影响；基于车辆纵向动力学特性和道路参数估计结果，计算可行驶性概率并预测可行驶性。为了快速仿真验证所提出的可行驶性预测方法，搭建相应的自动测试环境并设计测试方法。首先分析并测试车辆行驶过程中容易因失效造成预测失败的临界关键工况，接着在虚拟行驶环境中建立自动化测试流程，加强对关键工况区的采样，总计通过402组测试工况验证可行驶性预测算法，预测准确率达到87.81%。最后，在实车平台和真实测试道路上对算法流程进行验证。研究结果表明：该方法能够很好地对车辆在纵向坡路上的可行驶性进行动态的、基于概率性指标的预测。
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| 关 键 词： | 汽车工程 可行驶性预测 仿真测试方法 车辆动力学 智能汽车 激光雷达 |
| 收稿时间： | 2019-03-28 |
Dynamic Traversability Prediction on a Longitudinal Ramp Based on Lidar（in English） |
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| ZHAO Jian,LI Ya-xin,ZHU Bing,SUN Bo-hua,LI Zhi-xuan.Dynamic Traversability Prediction on a Longitudinal Ramp Based on Lidar（in English）[J].China Journal of Highway and Transport,2019,32(6):147-157. |
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| Authors: | ZHAO Jian LI Ya-xin ZHU Bing SUN Bo-hua LI Zhi-xuan |
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| Affiliation: | 1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, Jilin, China;2. School of Automotive Engineering, Jilin University, Changchun 130025, Jilin, China |
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| Abstract: | To implement environmental perception and understanding of road traversability in a variable off-road driving environment for intelligent vehicles, a lidar-based dynamic stochastic road traversability prediction method was proposed. First, a collaborative simulation platform using PreScan, CarSim, and MATLAB was established, on which a physical lidar model was then built to improve the fidelity of virtual point clouds. Then, lidar-based dynamic traversability was researched. An interval grid map on the proceeding vehicle trajectory was built based on Cartesian coordinates with point clouds on the road. Normal vectors at every interval were calculated by plane fitting, and interval slope angles were further calculated. Vehicle poses were applied to convert slope angles into a ground-fixed coordinate and to estimate the road profile. In addition, the effects of lidar physical features in different types of weather were discussed. Both the traversable possibility and traversability were derived based on vehicle dynamics and road estimation. An automated test environment and test criteria were designed for rapid simulation tests. Critical scenarios that were failure sensitive were analyzed and tested. Test automation procedures were designed to enhance sampling on critical scenarios. A total of 402 tests were conducted and the results indicate that the proposed traversability prediction method has an accuracy rate of 87.81%. Finally, the proposed method was field tested on a vehicle platform to verify its feasibility for use in a real driving environment. The proposed method was shown to work well under dynamic driving conditions and could stochastically calculate the traversability probability as well as predict traversability. |
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| Keywords: | automotive engineering traversability prediction simulation test method vehicle dynamics intelligent vehicle lidar |
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