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Aug 12, 2020
A Road Traffic Crash Risk Assessment Method Using Vehicle Trajectory Data and Surrogate Safety Measures
Authors: Lingfeng Peng [email protected], Nengchao Lyu [email protected], and Chaozhong Wu [email protected]Author Affiliations
Publication: CICTP 2020
ABSTRACT
The development of traffic sensing technology makes it possible to obtain high-precision microscopic traffic flow data; characteristic parameters based on microscopic traffic flow can be used for real-time crash risk assessment on roadways along with active safety control. The purpose of this paper is to study the relationship between surrogate safety measures (SSM) based on microscopic traffic parameters and road real-time crash risk. It is proposed to use the microwave radar detector to obtain real-time position and speed of the vehicle moving through the detection area. Vehicle trajectory data can be processed to extract the modified time-to-collision (MTTC), potential index for collision with urgent deceleration (PICUD), stopping headway distance (SHD), deceleration rate to avoid a crash (DRAC), and deceleration-based surrogate safety measure (DSSM). This can represent the three categories based on measuring attributes: temporal proximity, distance, and deceleration. Collectively, the time is divided into 30 s segments, and the traffic is divided into two states by the combination of TTC value, rapid deceleration rate and manual observation: no risk and risk. The Mann-Whitney U test is used to analyze the distribution difference of selected SSM under different traffic accident risks. Finally, the Fisher discriminant method is used to determine the road segment risk in real-time through the selected parameters. This study identified real-time microscopic traffic flow indicators that are significantly associated with road traffic crash risks and provides a basis for predictive models of road traffic crashes with proactive prevention and control technologies.
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© 2020 American Society of Civil Engineers.
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Published online: Aug 12, 2020
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1Intelligent Transportation Systems Research Center, Wuhan Univ. of Technology, P.O. Box 430063, Wuhan, China; National Engineering Research Center for Water Transport Safety, P.O. Box 430063, Wuhan, China. Email: [email protected]
2Intelligent Transportation Systems Research Center, Wuhan Univ. of Technology, P.O. Box 430063, Wuhan, China; National Engineering Research Center for Water Transport Safety, P.O. Box 430063, Wuhan, China. Email: [email protected]
3Intelligent Transportation Systems Research Center, Wuhan Univ. of Technology, P.O. Box 430063, Wuhan, China; National Engineering Research Center for Water Transport Safety, P.O. Box 430063, Wuhan, China. Email: [email protected]
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