Volume 40 Issue 2
Apr.  2022
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TIAN Shun, TIAN Shanshan, YANG Wei, WEI Lang, CHEN Tao. A Model for Estimating Driving Sight Distances Based on Corner Point of Broken Line of Roadway[J]. Journal of Transport Information and Safety, 2022, 40(2): 30-37. doi: 10.3963/j.jssn.1674-4861.2022.02.004
Citation: TIAN Shun, TIAN Shanshan, YANG Wei, WEI Lang, CHEN Tao. A Model for Estimating Driving Sight Distances Based on Corner Point of Broken Line of Roadway[J]. Journal of Transport Information and Safety, 2022, 40(2): 30-37. doi: 10.3963/j.jssn.1674-4861.2022.02.004

A Model for Estimating Driving Sight Distances Based on Corner Point of Broken Line of Roadway

doi: 10.3963/j.jssn.1674-4861.2022.02.004
  • Received Date: 2021-05-23
    Available Online: 2022-05-18
  • A study of driving sight distances is critical for safety evaluation of highways, which makes it ideal for estimating driving sight distances using in-vehicle equipment. To address the low accuracy of the existing sight distance models using the feature points of lane marking images, a model for estimating driving sight distances with the dotted corner points as the important feature is proposed. Based on the images preprocessing obtained by an in-vehicle equipment, the contour tracking method is used to extract the contour of line markings, so that the initial screening of the corner points can be extracted by setting a threshold sharpness of the contour. After using the maximum and minimum distance methods to cluster and classify candidate corner points, the points with the largest sharpness in each category is determined as the"true"corner points. In addition, the accurate extraction of the diagonal points is achieved by using the trapezoidal features of the dashed line image of the lane marking. By considering the relationship between the global mapping coordinates and the pixel coordinates of the corner points, the transformation matrix between the two coordinates is settled and the estimation model of driving sight distance is developed. By comparing with estimated sight distance with the required distance at a given operation speed, the evaluation of driving sight distance of the alignment of current road segment is implemented. The dynamic and static detection accuracy of the proposed sight distance estimation model is verified by a field experiment. Study results show that the estimation errors under the static condition are less than 7%, which is lower than the traditional methods. In addition, under dynamic conditions, the errors of driving sight distance are consistent with the results of static conditions, indicating that the proposed estimation model has a good performance under dynamic conditions. Comprehensively, the model can be used to support safety evaluation of highway design and operation.

     

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  • [1]
    张卫华, 张鑫, 曹世全, 等. 适应能见度变化的道路线形诱导标志设置方法[J]. 中国安全科学学报, 2019, 29(7): 76-83. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201907017.htm

    ZHANG W H, ZHANG X, CAO S Q, et al. Road alignment induction sign setting method adapting to visibility change[J]. China Safety Science Journal, 2019, 29(7): 76-83. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201907017.htm
    [2]
    文森, 梁波, 肖尧, 等. 基于反应时间的公路隧道接近段停车视距研究[J]. 交通信息与安全, 2021, 39(2): 43-52. doi: 10.3963/j.jssn.1674-4861.2021.02.006

    WEN S, LIANG B, XIAO Y, et al. A stopping distance in access zone of highway tunnel based on reaction time[J]. Journal of Transport Information and Safety, 2021, 39(2): 43-52 (in Chinese) doi: 10.3963/j.jssn.1674-4861.2021.02.006
    [3]
    WANG Y, TEOH K, SHEN D G. Lane detection and tracking using B-Snake[J]. Image and Vision Computing. 2004, 22 (4): 269-280. doi: 10.1016/j.imavis.2003.10.003
    [4]
    郭磊, 李克强, 王建强, 等. 应用方向可调滤波器的车道线识别方法[J]. 机械工程学报, 2008(8): 214-218+226. doi: 10.3321/j.issn:0577-6686.2008.08.038

    GUO L, LI K Q, WANG J Q, et al. Lane detection method by steerable filters[J]. Chinese Journal of Mechanical Engineering, 2008(8): 214-218+226. (in Chinese) doi: 10.3321/j.issn:0577-6686.2008.08.038
    [5]
    ANDRDE C, BUENO F, FRANCO R, et al. A novel strategy for road lane detection and tracking based on a vehicle's forward monocular camera[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(4): 1497-1507.
    [6]
    XING Y, LYU C, WANG H J, et al. Dynamic integration and online evaluation of vision-based lane detection algorithms[J]. IET Intelligent Transport Systems, 2018, 13(1): 55-62.
    [7]
    ZHANG Z Y, QIAN W, PAN L, et al. Adaptive zoom distance measuring system of camera based on the ranging of binocular vision[J]. Modern Applied Science, 2012, 6(5): 43-47.
    [8]
    高波. 基于单目视觉的公路视距检测技术研究[D]. 西安: 长安大学, 2017.

    GAO B. Research on road slight distance detection technology based on monocular vision[D]. Xi'an: Chang'an University, 2017. (in Chinese)
    [9]
    白琛琛. 高等级公路弯道视距测算及安全评价方法研究[D]. 西安: 长安大学, 2020.

    BAI C C. Research on sight distance calculation and safety evaluation method for high-grade highway curves[D]. Xi'an: Chang'an University, 2020.(in Chinese)
    [10]
    CHEN Y, HE M Y. Sharp curve lane boundaries projective model and detection[C]. 10th International Conference on Industrial Informatics, Beijing, China: IEEE, 2012.
    [11]
    AGRAWAL S, DEO K, HALDAR S, et al. Off-road lane detection using superpixel clustering and ransac curve fitting[C]. 15th International Conference on Control, Automation, Robotics and Vision(ICARCV), Singapore: IEEE, 2018
    [12]
    SCHOMERUS V, ROSEBROCK D, WAHL M. Camera-based lane border detection in arbitrarily structured environments[C]. 2014 IEEE Intelligent Vehicles Symposium, Michigan, USA: IEEE, 2014.
    [13]
    PARK Y, HWANG Y. Robust range estimation with a monocular camera for vision-based forward collision warning system[J]. The Scientific World Journal, 2014(12): 1-9.
    [14]
    陈雨人, 付云天, 汪凡. 基于支持向量回归的视距计算模型建立和应用[J]. 中国公路学报, 2018, 31(4): 105-113. doi: 10.3969/j.issn.1001-7372.2018.04.013

    CHEN Y, FU Y T, WANG F. Establishment and application of slight distance computing model based on support vector regression[J]. China Journal of Highway and Transport, 2018, 31(4): 105-113. doi: 10.3969/j.issn.1001-7372.2018.04.013
    [15]
    LEBMANN S, MEUTER M, MULLER D, et al. Probabilistic distance estimation for vehicle tracking application in monocular vision[C]. 4th IEEE Intelligent Vehicles Symposium, Gothenburg, Sweden: IEEE, 2016.
    [16]
    JWP A, YWH A, YZY A, et al. Development of an embedded road boundary detection system based on deep learning[J]. Image and Vision Computing, 2020, 100(5), 82-95.
    [17]
    曹思佳, 代扬, 余洪山, 等. 基于机器视觉的机械表走时精度测量[J]. 湖南大学学报(自然科学版), 2020, 47(12): 86-94. https://www.cnki.com.cn/Article/CJFDTOTAL-HNDX202012011.htm

    CAO S J, DAI Y, YU H S, et al. Accuracy measurement of mechanical watch travel time based on machine vision[J]. Journal of Hunan University(Natural Science), 2020, 47 (12): 86-94. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HNDX202012011.htm
    [18]
    钱文光, 林小竹. 基于轮廓尖锐度的图像角点检测算法[J]. 计算机工程, 2008(6): 202-204. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJC200806075.htm

    QIAN W G, LIN X Z. Detection algorithm of image corner based contour sharp degree[J]. Computer Engineering, 2008 (6): 202-204.(in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSJC200806075.htm
    [19]
    刘燕. 基于抽样和最大最小距离法的并行K-means聚类算法[J]. 智能计算机与应用, 2018, 8(6): 37-39+43. doi: 10.3969/j.issn.2095-2163.2018.06.008

    LIU Y. Parallel K-means clustering algorithm based on sampling and maximum & minimum distance method[J]. Intelligent Computer and Applications, 2018, 8(6): 37-39+43. (in Chinese) doi: 10.3969/j.issn.2095-2163.2018.06.008
    [20]
    郑榜贵, 田炳香, 段建民. 基于交比不变量的摄像机标定方法[J]. 北京工业大学学报, 2008(5): 476-480. https://www.cnki.com.cn/Article/CJFDTOTAL-BJGD200805008.htm

    ZHEN B G, TIAN B X, DUAN J M. Camera calibration approach based on cross-ratio invariability[J]. Journal of Beijing University of Technology, 2008(5): 476-480. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-BJGD200805008.htm
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