A safety evaluation of an Adaptive Traffic Signal Control system using Computer Vision

被引:0
作者
机构
[1] Department of Civil Engineering, University of British Columbia, Vancouver, BC V6T 1Z4
来源
| 1600年 / Aracne Editrice卷 / 02期
关键词
Computer Vision; ITS signal control; Safety evaluation; Traffic conflicts;
D O I
10.4399/97888548735379
中图分类号
学科分类号
摘要
The reliance on aggregate historical collision data as a sole technique in road safety analysis was proved challenging in the quest to better understand, predict, and improve road safety conditions. Therefore, surrogate safety measures such as the traffic conflict technique have been promoted as an alternative or complementary approach to assess and analyze road safety from a broader perspective than collision statistics alone. A primary focus of road safety analysis that could greatly benefit from vision-based road safety analysis is before-and-after (BA) evaluation of safety treatments. This study demonstrates the use of automated traffic conflict analysis in conducting a before-and-after (BA) safety study for an Adaptive Traffic Signal Control (ATSC) system. The objective of this study is to conduct a time-series (before-to-after) safety evaluation for two intersections in the City of Surrey where the ATSC system was implemented. The ATSC automatically makes real time adjustments to traffic signal timing based on actual observed traffic volumes to reduce vehicle delays and travel time. Overall, the study demonstrated the usefulness of using automated traffic conflicts in before-and-after safety evaluations of the ATSC system. Traffic conflicts occur more frequently than collisions so the desired sample size for analysis can be obtained in much shorter time periods. It was also demonstrated that the use of computer vision techniques to automate the extraction of traffic conflicts from video data can overcome the shortcomings of the traditional manual conflict observation methods. The results of the analysis showed considerable increase in the frequency and severity of conflicts following the implementation of the ATSC system. The increase of vehicle travel time following the implementation of the ATSC has likely contributed to the observed increase in conflict frequency and severity.
引用
收藏
页码:83 / 96
页数:13
相关论文
共 50 条
  • [22] Adaptive traffic light control using vision-based deep learning for vehicle density estimation
    Karoon, Weerasak
    Chuasuai, Peeranut
    Thipprasert, Pearploy
    Khongchu, Nachasa
    Kunakornjittirak, Piyaboon
    Siriborvornratanakul, Thitirat
    2024 6TH ASIA PACIFIC INFORMATION TECHNOLOGY CONFERENCE, APIT 2024, 2024, : 37 - 42
  • [23] Safety evaluation of right-turn smart channels using automated traffic conflict analysis
    Autey, Jarvis
    Sayed, Tarek
    Zaki, Mohamed H.
    ACCIDENT ANALYSIS AND PREVENTION, 2012, 45 : 120 - 130
  • [24] Automated shopping system using computer vision
    Odeh, Nemer
    Direkoglu, Cem
    MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (41-42) : 30151 - 30161
  • [25] Real-Time Traffic Sign Detection and Recognition System using Computer Vision and Machine Learning
    Patil, Rahul
    Ahire, Prashant
    Bamane, Kalyan
    Patankar, Abhijit
    Patil, Pramod D.
    Badoniya, Saomya
    Desai, Resham
    Bhandari, Gautam
    Dhami, Bikramjeet Singh
    JOURNAL OF ELECTRICAL SYSTEMS, 2024, 20 (02) : 2244 - 2254
  • [26] Computer Vision System for Food Quality Evaluation - A Review
    Nandhini, P.
    Jaya, J.
    George, Jaina
    2013 INTERNATIONAL CONFERENCE ON CURRENT TRENDS IN ENGINEERING AND TECHNOLOGY (ICCTET), 2013, : 85 - 87
  • [27] Automated shopping system using computer vision
    Nemer Odeh
    Cem Direkoglu
    Multimedia Tools and Applications, 2020, 79 : 30151 - 30161
  • [28] An automated system for dimensional control based on computer vision
    Borsellino, C
    Lo Valvo, E
    Ruisi, VF
    AMST 02: ADVANCED MANUFACTURING SYSTEMS AND TECHNOLOGY, PROCEEDINGS, 2002, (437): : 249 - 258
  • [29] A Novel Smart Household Control System by Computer Vision
    Wang Xianmei
    Deng Ti
    Liang Lingyan
    Wang Zhiliang
    MATERIALS SCIENCE AND ENGINEERING, PTS 1-2, 2011, 179-180 : 264 - 269
  • [30] Traffic Light Detection and Intersection Crossing Using Mobile Computer Vision
    Grewe, Lynne
    Lagali, Christopher
    SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXVI, 2017, 10200