Assessment of Expressway Traffic Safety Using Gaussian Mixture Model based on Time to Collision

被引：0
作者：
Jin S. [1 ]
Qu X. [2 ]
Wang D. [1 ]
机构：
[1] College of Civil Engineering and Architecture, Zhejiang University, Hangzhou
[2] Department of Civil and Environmental Engineering, National University of Singapore
来源：
International Journal of Computational Intelligence Systems | 2011年 / 4卷 / 6期
关键词：
Expressway traffic safety; Gaussian mixture model; Time to collision;
D O I：
10.2991/ijcis.2011.4.6.4
中图分类号：
学科分类号：
摘要：
Traffic safety is of great significance, especially in urban expressway where traffic volume is large and traffic conflicts are highlighted. It is thus important to develop a methodology that is able to assess traffic safety. In this paper, we first analyze the time to collision (TTC) samples from traffic videos collected from Beijing expressway with different locations, lanes, and traffic conditions. Accordingly, some basic descriptive statistics of 5 locations’ TTC samples are shown, and it is concluded that Gaussian mixture model (GMM) distribution is the best-fitted distribution to TTC samples based on K-S goodness of fit tests. Using GMM distribution, TTC samples can be divided into three categories: dangerous situations, relative safe situations, and absolute safe situations, respectively. We then proceeds to introduce a novel concept of the percentage of serious traffic conflicts as the percentage of TTC samples below a predetermined threshold value in dangerous situation. After that, assessment results of expressway traffic safety are presented using the proposed traffic safety indictor. The results imply that traffic safety on the weaving segment is lower than that on mainlines and the percentage of serious traffic conflicts on median lane is larger than that on middle lane and shoulder lane. © 2017, Atlantis Press.
引用
收藏
页码：1122 / 1130
页数：8
相关论文
共 50 条
  • [41] A Harmonic Bandwidth Extension based on Gaussian Mixture Model
    Liu, Xin
    Bao, Chang-chun
    Jia, Mao-shen
    Sha, Yong-tao
    2010 IEEE 10TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS (ICSP2010), VOLS I-III, 2010, : 474 - 477
  • [42] Nonuniformity correction algorithm based on Gaussian mixture model
    Mou Xin-gang
    Zhang Gui-lin
    Hu Ruo-lan
    Zhou Xiao
    INTERNATIONAL SYMPOSIUM ON PHOTOELECTRONIC DETECTION AND IMAGING 2011: ADVANCES IN INFRARED IMAGING AND APPLICATIONS, 2011, 8193
  • [43] HEALTH ASSESSMENT OF WIND TURBINE GEARBOX BASED ON CONDITIONAL CONVOLUTION AUTOENCODING GAUSSIAN MIXTURE MODEL
    He Q.
    Li Y.
    Jiang G.
    Su N.
    Xie P.
    Wu X.
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2023, 44 (12): : 214 - 220
  • [44] Encrypted traffic classification based on Gaussian mixture models and Hidden Markov Models
    Yao, Zhongjiang
    Ge, Jingguo
    Wu, Yulei
    Lin, Xiaosheng
    He, Runkang
    Ma, Yuxiang
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2020, 166
  • [45] Enhanced Gaussian-mixture-model-based nonlinear probabilistic uncertainty propagation using Gaussian splitting approach
    Chen, Q.
    Zhang, Z.
    Fu, Chunming
    Hu, Dean
    Jiang, C.
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2024, 67 (04)
  • [46] A Gaussian Mixture Model Based Diagnosis of Alzheimer's Using Diffusion Tensor Imaging
    Patil, Ravindra B.
    Ramakrishnan, S.
    2013 39TH ANNUAL NORTHEAST BIOENGINEERING CONFERENCE (NEBEC 2013), 2013, : 137 - 138
  • [47] Image compression based on Gaussian mixture model constrained using Markov random field
    Sun, Jianjun
    Zhao, Yan
    Wang, Shigang
    Wei, Jian
    SIGNAL PROCESSING, 2021, 183
  • [48] Real-time detection algorithm of moving ground targets based on Gaussian mixture model
    Yang Weiping
    Zhang Zhilong
    Zhang Yan
    Li Jicheng
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING XX, 2014, 9244
  • [49] Content-based image retrieval using a Gaussian mixture model in the wavelet domain
    Yuan, H
    Zhang, XP
    Guan, L
    VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2003, PTS 1-3, 2003, 5150 : 422 - 429
  • [50] An image thresholding approach based on Gaussian mixture model
    Zhao, Like
    Zheng, Shunyi
    Yang, Wenjing
    Wei, Haitao
    Huang, Xia
    PATTERN ANALYSIS AND APPLICATIONS, 2019, 22 (01) : 75 - 88
12345