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

Ruoxi Jiang, Shunying Zhu, Hongguang Chang, Jingan Wu, Naikan Ding, Bing Liu and Ji Qiu
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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

Sustainability, 2021, vol. 13, issue 16, 1-30

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.

Keywords: traffic safety estimation; traffic conflict technique; traffic conflict indicator; highway; vehicle trajectory data; UAV (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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