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Determining an Improved Traffic Conflict Indicator for Highway Safety Estimation Based on Vehicle Trajectory Data

Author

Listed:
  • Ruoxi Jiang

    (School of Transportation, Wuhan University of Technology, 1178 Heping Avenue, Wuhan 430063, China)

  • Shunying Zhu

    (School of Transportation, Wuhan University of Technology, 1178 Heping Avenue, Wuhan 430063, China)

  • Hongguang Chang

    (School of Transportation, Wuhan University of Technology, 1178 Heping Avenue, Wuhan 430063, China)

  • Jingan Wu

    (School of Transportation, Wuhan University of Technology, 1178 Heping Avenue, Wuhan 430063, China)

  • Naikan Ding

    (School of Civil Engineering and Architecture, Wuhan Institute of Technology, Wuhan 430205, China)

  • Bing Liu

    (School of Transportation, Wuhan University of Technology, 1178 Heping Avenue, Wuhan 430063, China)

  • Ji Qiu

    (School of Transportation, Wuhan University of Technology, 1178 Heping Avenue, Wuhan 430063, China)

Abstract

Currently, several traffic conflict indicators are used as surrogate safety measures. Each indicator has its own advantages, limitations, and suitability. There are only a few studies focusing on fixed object conflicts of highway safety estimation using traffic conflict technique. This study investigated which conflict indicator was more suitable for traffic safety estimation based on conflict-accident Pearson correlation analysis. First, a high-altitude unmanned aerial vehicle was used to collect multiple continuous high-precision videos of the Jinan-Qingdao highway. The vehicle trajectory data outputted from recognition of the videos were used to acquire conflict data following the procedure for each conflict indicator. Then, an improved indicator T i was proposed based on the advantages and limitations of the conventional indicators. This indicator contained definitions and calculation for three types of traffic conflicts (rear-end, lane change and with fixed object). Then the conflict-accident correlation analysis of TTC (Time to Collision)/PET (Post Encroachment Time)/DRAC (Deceleration Rate to Avoid Crash)/T i indicators were carried out. The results show that the average value of the correlation coefficient for each indicator with different thresholds are 0.670 for TTC, 0.669 for PET, and 0.710 for DRAC, and 0.771 for T i , which T i indicator is obviously higher than the other three conventional indicators. The findings of this study suggest TTC often fails to identify lane change conflicts, PET indicator easily misjudges some rear-end conflict when the speed of the following vehicle is slower than the leading vehicle, and PET is less informative than other indicators. At the same time, these conventional indicators do not consider the vehicle-fixed objects conflicts. The improved T i can overcome these shortcomings; thus, T i has the highest correlation. More data are needed to verify and support the study.

Suggested Citation

  • Ruoxi Jiang & Shunying Zhu & Hongguang Chang & Jingan Wu & Naikan Ding & Bing Liu & Ji Qiu, 2021. "Determining an Improved Traffic Conflict Indicator for Highway Safety Estimation Based on Vehicle Trajectory Data," Sustainability, MDPI, vol. 13(16), pages 1-30, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:9278-:d:616906
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    Citations

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    Cited by:

    1. Tong Liu & Chang Wang & Rui Fu & Yong Ma & Zhuofan Liu & Tangzhi Liu, 2022. "Lane-Change Risk When the Subject Vehicle Is Faster Than the Following Vehicle: A Case Study on the Lane-Changing Warning Model Considering Different Driving Styles," Sustainability, MDPI, vol. 14(16), pages 1-20, August.
    2. Piotr Szagala & Andrzej Brzezinski & Mariusz Kiec & Marcin Budzynski & Joanna Wachnicka & Sylwia Pazdan, 2022. "Pedestrian Safety at Midblock Crossings on Dual Carriageway Roads in Polish Cities," Sustainability, MDPI, vol. 14(9), pages 1-13, May.

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