Vehicle lane change behavior detection method based on machine learning

被引：0
|
作者：
Yan X.T. [1 ]
Shang Z.L. [2 ]
机构：
[1] School of Information Technology, Luoyang Normal University, Luoyang
[2] Engineering Trainning Center, Zhengzhou University of Light Industry, Zhengzhou
来源：
Advances in Transportation Studies | 2023年 / 1卷 / Special Issue期
关键词：
areas of interest; behavior detection; forced lane change of vehicles; grayscale; kalman filtering; machine learning;
D O I：
10.53136/97912218061513
中图分类号：
学科分类号：
摘要：
In this paper, a vehicle forced lane change behavior detection algorithm based on machine learning is proposed. Collect the vehicle's forward looking monocular video image and determine the reasonable region of interest: The intention and process of vehicle forced lane change are analyzed by video image features, and the vehicle forced lane change motivation model is established; Use Kalman filter in machine learning to track vehicles: Calculate the centroid coordinates of the target vehicle and the distance of the lane line, and determine whether the vehicle in front has a forced lane change behavior in combination with the lane change motivation model. The experimental results show that this method has higher accuracy in detecting vehicle lane change behavior. © 2023, Aracne Editrice. All rights reserved.
引用
收藏
页码：27 / 38
页数：11
相关论文
共 50 条
  • [31] A Study on Real-Time Detection Method of Lane and Vehicle for Lane Change Assistant System Using Vision System on Highway
    Nguyen, VanQuang
    Kim, Heungsuk
    Jun, SeoChang
    Boo, Kwangsuck
    ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH, 2018, 21 (05): : 822 - 833
  • [32] Motion trajectory planning method of lane change for intelligent vehicle
    Li, Aijuan
    Li, Shunming
    Shen, Huan
    Miao, Xiaodong
    Li, Xiao
    Journal of Theoretical and Applied Information Technology, 2012, 45 (01) : 297 - 302
  • [33] Learning-based method for lane detection using regionlet representation
    Chen, Yuxuan
    Chen, Wei-Gang
    Wang, Xun
    Yu, Runyi
    Tian, Yan
    IET INTELLIGENT TRANSPORT SYSTEMS, 2019, 13 (12) : 1745 - 1753
  • [34] Optimized deep extreme learning machine for traffic prediction and autonomous vehicle lane change decision-making
    Ma, Changxi
    Zhao, Mingxi
    Huang, Xiaoting
    Zhao, Yongpeng
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2024, 633
  • [35] A fast decision making method for mandatory lane change using kernel extreme learning machine
    Cheng, Senlin
    Xu, Yang
    Zong, Ruixue
    Wang, Chuanhai
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2019, 10 (12) : 3363 - 3369
  • [36] A fast decision making method for mandatory lane change using kernel extreme learning machine
    Senlin Cheng
    Yang Xu
    Ruixue Zong
    Chuanhai Wang
    International Journal of Machine Learning and Cybernetics, 2019, 10 : 3363 - 3369
  • [37] Crowd abnormal behavior detection based on machine learning
    Zhang, Dongping
    Peng, Huailiang
    Haibin, Yu
    Lu, Yafei
    Information Technology Journal, 2013, 12 (06) : 1199 - 1205
  • [38] Research on Lane Detection Based on Machine Vision
    Yang Xining
    Gao Dezhi
    Duan Jianmin
    Yang Lei
    2010 INTERNATIONAL COLLOQUIUM ON COMPUTING, COMMUNICATION, CONTROL, AND MANAGEMENT (CCCM2010), VOL I, 2010, : 528 - 531
  • [39] Research on Lane Detection Based on Machine Vision
    Yang, Xining
    Gao, Dezhi
    Duan, Jianmin
    Yang, Lei
    PROCEEDINGS OF THE 2011 INTERNATIONAL CONFERENCE ON INFORMATICS, CYBERNETICS, AND COMPUTER ENGINEERING (ICCE2011), VOL 1: INTELLIGENT CONTROL AND NETWORK COMMUNICATION, 2011, 110 (01): : 539 - 547
  • [40] Research on Trajectory Prediction of Vehicle Lane Change for Autonomous Driving Based on Inverse Reinforcement Learning
    Zhan, Ming
    Fan, Jingjing
    Jin, Linhao
    SEVENTH INTERNATIONAL CONFERENCE ON TRAFFIC ENGINEERING AND TRANSPORTATION SYSTEM, ICTETS 2023, 2024, 13064
12345