Journal of Computer Applications ›› 2016, Vol. 36 ›› Issue (12): 3511-3514.DOI: 10.11772/j.issn.1001-9081.2016.12.3511

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Multilane traffic flow detection algorithm based on adaptive virtual loop

GAN Ling, LI Rui   

  1. College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2016-06-12 Revised:2016-08-17 Online:2016-12-10 Published:2016-12-08
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61272195).


甘玲, 李瑞   

  1. 重庆邮电大学 计算机科学与技术学院, 重庆 400065
  • 通讯作者: 甘玲
  • 作者简介:甘玲(1964-),女,重庆人,教授,硕士,主要研究方向:智能信息处理、运动目标检测;李瑞(1991-),女,河南信阳人,硕士研究生,主要研究方向:车流量检测。
  • 基金资助:

Abstract: Aiming at such interferences as false detection and missed detection which can't be overcome by the existing virtual loop detection algorithm in multilane traffic flow detection, a novel traffic flow detection algorithm based on adaptive virtual loop was put forward. According to the image binarization principle, quadratic estimation was adopted in the foreground detection part of the Visual Background extractor (ViBe) algorithm, and the background updating mechanism was changed. A new improved ViBe algorithm was presented to achieve the purposes of rapidly eliminating the ghost and completing the foreground object extraction. Then, the fixed detection area was set on the road, and the mobile virtual loop was established or canceled according to the moving target trajectory of fixed detection area. The traffic flow algorithm based on virtual loop was further used to achieve traffic flow statistics. Three different scenarios:no vehicle lane change with 4 lanes, vehicle lane change with 2 lanes, vehicle lane change with 3 lanes and sudden environmental change, were chosen for experiments and the traffic flow detection accuracy of the proposed algorithm was 8.9, 25 and 16.6 percentage points higher than that of the traditional virtual loop detection algorithm. The experimental results show that the proposed algorithm is more suitable for multilane traffic flow detection.

Key words: intelligent transportation, traffic flow detection, background subtraction, Visual Background extractor (ViBe), virtual loop

摘要: 针对虚拟线圈检测算法在多车道车流量检测中存在误检或者漏检的问题,提出一种基于自适应虚拟线圈的车流量检测算法。根据图像二值化原理,对ViBe算法的前景检测部分进行二次判断,并改变背景更新机制,提出一种改进的ViBe算法,以达到快速消除鬼影的目的,更准确地完成前景目标提取。在道路上设置固定检测区域,根据运动目标在固定检测区域的运动轨迹来建立或者消除非固定虚拟线圈,再进一步使用虚拟线圈的车流量检测算法实现车流量统计。选择三个不同的场景4车道无车辆变道、2车道有车辆变道和3车道有车辆变道且环境突变进行实验,所提算法的车流量检测准确率比传统的虚拟线圈算法分别提高8.9、25和16.6个百分点,且所用时间相当。实验结果表明所提算法更适用于多车道的车流量检测。

关键词: 智能交通, 车流量检测, 背景差分, ViBe, 虚拟线圈

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