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计算机工程

• 开发研究与工程应用 • 上一篇    下一篇

基于单目视觉的智能车路口实时定位方法

郑永荣 1,袁家政 1,2,刘宏哲 1,李超 1   

  1. (1.北京联合大学 北京市信息服务工程重点实验室,北京 100101; 2.首都师范大学 北京成像技术高精尖创新中心,北京 100048)
  • 收稿日期:2016-08-30 出版日期:2017-09-15 发布日期:2017-09-15
  • 作者简介:郑永荣(1991—),男,硕士研究生,主研方向为图像处理;袁家政(通信作者)、刘宏哲,教授、博士;李超,硕士。
  • 基金资助:
    国家自然科学基金(61271369,61372148,61571045);北京市自然科学基金(4152016,4152018);北京成像技术高精尖创新中心项目(BAICIT-2016002)。

Method of Real Time Intersection Location Based on Monocular Vision for Intelligent Vehicle

ZHENG Yongrong 1,YUAN Jiazheng 1,2,LIU Hongzhe 1,LI Chao 1   

  1. (1.Beijing Key Laboratory of Information Service Engineering,Beijing Union University,Beijing 100101,China; 2.Beijing Advanced Innovation Center for Imaging Technology,Capital Normal University,Beijing 100048,China)
  • Received:2016-08-30 Online:2017-09-15 Published:2017-09-15

摘要: 为解决智能车在路口的高精度实时定位问题,基于单目视觉,提出一种路口实时定位方法。对需要定位的路口进行编号并建立路口场景特征库,采用路口场景识别的方法进行路口粗定位,通过路口图像中的停止线检测与测距以及车道线检测计算车辆航向角和偏移距离,综合距离、航向角和偏移距离进行位置坐标计算。在真实道路环境的路口测试结果表明,提出的定位方法具有精度高、实时性好、鲁棒性强的优点,适合于智能车路口视觉导航。

关键词: 智能车, 路口定位, 场景识别, 停止线检测, 车道线检测

Abstract: In order to solve the problem of high accuracy real-time location of intelligent vehicles at the intersection,this paper proposes a real-time intersection location method based on monocular vision.The intersections that need to be located are numbered and an intersection scene feature library is created.The intersection scene recognition method is used for rough location.Through the stop-line detection and ranging of intersection images as well as the lane detection,the course angle and offset distance of the vehicle are calculated.Coordinate position is calculated by synthetic distance,heading angle and offset distance.The intersection test results in real road environment show that the proposed method has the advantages of high accuracy,real-time performance and robustness.It is suitable for the visual navigation of intelligent vehicles at the intersection.

Key words: intelligent vehicle, intersection location, scene recognition, stop-line detection, lane detection

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