中国机械工程

• 机械基础工程 • 上一篇    下一篇

智能汽车环境感知算法测试评价系统开发

隗寒冰1;曹旭1;赖锋2   

  1. 1.重庆交通大学机电与车辆工程学院,重庆,400074
    2.东风汽车集团有限公司技术中心,武汉,430020
  • 出版日期:2018-10-10 发布日期:2018-10-08
  • 基金资助:
    国家自然科学基金资助项目(51305472);
    重庆市自然科学基金资助项目(cstc2014jcyjA6000)
    National Natural Science Foundation of China (No. 51305472)
    Natural Science Foundation of Chongqing(No. cstc2014jcyjA6000)

Development of Environmental Perception Algorithm Test Evaluation Systems for Intelligent Vehicles

WEI Hanbing1;CAO Xu1;LAI Feng2   

  1. 1.School of Mechatronics and Vehicle Engineering,Chongqing Jiaotong University,Chongqing,400074
    2.Dongfeng Motor Corporation Technical Center,Wuhan,430030
  • Online:2018-10-10 Published:2018-10-08
  • Supported by:
    National Natural Science Foundation of China (No. 51305472)
    Natural Science Foundation of Chongqing(No. cstc2014jcyjA6000)

摘要: 基于硬件在环仿真平台和六自由度驾驶模拟器,开发了智能汽车环境感知算法测试评价系统。为兼顾仿真测试的可重复性、可拓展性及道路测试的真实性,采用真实交通场景作为输入场景信息;针对现有检测算法评价依赖人工识取的不足,提出了基于机器学习的标准检测算法和基于数据关联的检测评价算法,并将系统测评结果与人工识取结果进行对比。实验结果表明,所开发的测试评价系统方案可行,测试精度较高,实时性较好,在模糊、遮挡、光照变化等复杂环境下均可实现对各种不同特性的车道线和车辆目标的准确测评,能较好地满足智能汽车环境感知算法测试评价的要求。

关键词: 硬件在环, 六自由度模拟器, 环境感知, 测试评价, 机器学习, 数据关联

Abstract: A detection and evaluation system of environment perception algorithm for intelligent vehicles was proposed on the basis of hardware-in-loop simulation platform and 6-DOF driving simulator. The real traffic scenario was implemented as the system inputs in order to take into account both the repeatability, scalability of virtual tests and the authenticity of road testing together.  Aiming at the shortcomings of the existing evaluation methods which relied on manual recognitions, a standard object detection algorithm based on machine learning and an evaluation algorithm based on data association were proposed. Consequently, the results of the system evaluation were compared with manual recognition ones. Experimental results show that the proposed evaluation system has strong reliability, high precision, and outstanding real-time performance. The accurate evaluation of lane and vehicle detection algorithm with different characteristics may be realized effectively under complicated road environments such as blur, occlusion and changing illumination. The test evaluation system may meet the requirements of intelligent vehicle environmental perception algorithm.

Key words: hardware-in-loop, 6-DOF simulator, environmental perception, test evaluation, machine learning, data association

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