吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (3): 756-763.doi: 10.13229/j.cnki.jdxbgxb201603012

• Orginal Article • Previous Articles     Next Articles

Intersection queue length estimation with single magnetic sensor

JIA Li-min1, CHEN Na1, LI Hai-jian1, 2, DONG Hong-hui1, 3   

  1. 1.State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China;
    2.Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China;
    3.Beijing Engineering Research Center of Urban Traffic Information Intelligent Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China
  • Received:2014-08-26 Online:2016-06-20 Published:2016-06-20

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Abstract: To estimate the intersection queue length, a magnetic sensor is deployed near the stop line at the intersection. Through the vehicle queue mechanism modeling, the evolution of vehicle occupancy sensor time and the departure interval can be obtained. Eventually, the queue length of the last signal cycle can be estimated. This paper analyzes the variance of vehicle occupancy sensor time and the departure interval with the increase in queued vehicle number, thereby proposes departure interval model, vehicle occupancy sensor time model and comprehensive model to estimate the queue length. The accuracies of the proposed models are compared using field experiments. Results show that the proposed queue length estimation method can accurately get the queue length of the last signal cycle. The method costs low and can be deployed easily, and thus, it can facilitate large-scale popularization and application. It can provide intersection queue length information for signal cycle optimization and traffic service level evaluation in road signal intersections.

Key words: engineering of transportation and communication system, magnetic sensor, signal intersection, queue length estimation, queued vehicle numbers

CLC Number: 

  • U491
[1] 庄立坚,何兆成,叶伟佳,等. 基于浮动车数据的排队长度检测方法研究[J]. 交通运输系统工程与信息,2013,13(3):78-84.
Zhuang Li-jian,He Zhao-cheng,Ye Wei-jia,et al. Queue length estimation based on floating car data[J]. Journal of Transportation System Engineering and Information Technology,2013,13(3):78-84.
[2] 时彦洞. 基于视频的车辆排队长度检测技术研究[D]. 江门:五邑大学信息工程学院,2009.
Shi Yan-dong. Queue detection based on video technology[D]. Jiangmen: School of Information Engineering, Wuyi University,2009.
[3] 刘喆. 基于计算机视觉的运动车辆检测与跟踪算法研究[D]. 北京:北京工业大学电子信息与控制工程学院,2009.
Liu Zhe. Moving vehicle detection based on computer vision[D]. Beijing: College of Electronic Information and Control Engineering, Beijing University of Technology,2009.
[4] 史元超. 基于新型传感器的交通状态获取技术的研究[D]. 北京:北京交通大学交通运输学院, 2009.
Shi Yuan-chao. Traffic condition acquirement technology based on New-type sensor[D]. Beijing: School of Traffic and Transportation, Beijing Jiaotong University,2009.
[5] Zheng J, Ma X, Wu Y J, et al. Measuring signalized intersection performance in real-time with traffic sensors[J]. Journal of Intelligent Transportation Systems,2013,17(4):304-316.
[6] Negri P. Estimating the queue length at street intersections by using a movement feature space approach[J].IET Image Processing, 2014,8(7):406-416.
[7] Vigos G, Papageorgiou M, Wang Y. Real-time estimation of vehicle-count within signalized links[J]. Transportation Research Part C: Emerging Technologies,2008,16(1):18-35.
[8] 买艳辉. 基于出租车GPS数据的速度分布和排队长度估计研究[D]. 长沙:长沙理工大学交通运输工程学院,2013.
Mai Yan-hui. The study on an estimation of speed distribution and queue length traffic state based on taxi GPS data[D]. Changsha:School of Traffic and Transportation Engineering, Changsha University of Science & Technology, 2013.
[9] Comert G, Cetin M. Queue length estimation from probe vehicle location and the impacts of sample size[J]. European Journal of Operational Research,2009,197(1): 196-202.
[10] Cai Q, Wang Z, Guo X, et al. New calculating method for HCM 2000 queue length estimation procedures with the application of floating car data[J]. Procedia-Social and Behavioral Sciences,2013,96:2201-2210.
[11] Comert G. Simple analytical models for estimating the queue lengths from probe vehicles at traffic signals[J]. Transportation Research Part B: Methodological,2013,55:59-74.
[12] Badillo B E, Rakha H, Rioux T W, et al. Queue length estimation using conventional vehicle detector and probe vehicle data[C]∥15th International IEEE Conference on Intelligent Transportation Systems (ITSC2012). United States: Institute of Electrical and Electronics Engineers Inc,2012:1674-1681.
[13] Comert G. Effect of stop line detection in queue length estimation at traffic signals from probe vehicles data[J]. European Journal of Operational Research,2013,226(1):67-76.
[14] 夏发钦. 利用地感应线圈检测机动车辆的原理与实现[D]. 武汉:武汉科技大学信息科学与工程学院,2011.
Xia Fa-qin. Vehicle detection using induction coil detector[D]. Wuhan: School of Information Science and Engineering, Wuhan University of Science and Technology,2011.
[15] Li H, Dong H, Jia L, et al. Some practical vehicle speed estimation methods by a single traffic magnetic sensor[C]∥14th International IEEE Conference on Intelligent Transportation Systems. United States:Institute of Electrical and Electronics Engineers Inc,2011:1566-1573.
[16] Li Hai-jian,Dong Hong-hui,Jia Li-min, et al. Vehicle classification with single multi-functional magnetic sensor and optimal MNS-based CART[J]. Measurement,2014,55: 142-152.
[17] 李海舰. 道路交通信息获取多参量感知与传感器网络优化[D]. 北京: 北京交通大学交通运输学院, 2014.
Li Hai-jian. Multi-parameter sensing and sensor network optimization for road traffic information acquisition[D]. Beijing: School of Traffic and Transportation, Beijing Jiaotong University,2014.
[18] Sanchez R O, Horowitz R, Varaiya P. Analysis of queue estimation methods using wireless magnetic sensors[J]. Transportation Research Record: Journal of the Transportation Research Board,2011,2229(1):34-45.
[19] 代磊磊,姜桂艳,裴玉龙,等. 饱和信号交叉口排队长度预测[J].吉林大学学报:工学版,2008,38(6):1287-1290.
Dai Lei-lei,Jiang Gui-yan,Pei Yu-long,et al. Prediction of queue length at saturate signalized intersection[J]. Journal of Jilin University (Engineering and Technology Edition),2008,38(6):1287-1290.
[20] 施晓芬. 城市信号交叉口驾驶员速度控制和视觉搜索行为研究[D]. 西安:长安大学公路学院,2011.
Shi Xiao-fen. Speed control and visual search of driving behavior at the intersection[D]. Xi'an: School of Highway, Chang'an University,2011.
[21] 王晶. 基于驾驶员性别的城市快速路跟驰模型研究[D].北京:北京工业大学城市交通学院,2008.
Wang Jing. A car following model in urban expressway based on driver's gender[D]. Beijing: College of Metropolitan Transportation, Beijing University of Technology,2008.
[22] 刘影. 基于机器视觉的交叉路口车速和车辆排队长度检测[D]. 天津:天津工业大学电子信息与工程学院,2012.
Liu Ying. Vehicle speed and vehicle queue length detection based on video at plane intersection[D]. Tianjin: School of Electronic and Information Engineering, Tianjin Polytechnic University,2012.
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