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 road crash risk assessment and 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 the real-time position and speed of the vehicle in the detection area. Through the vehicle trajectory data processing, to extract the Modified Time-to-Collision (MTTC), the Potential Index for Collision with Urgent Deceleration (PICUD), the Stopping Headway Distance (SHD), Deceleration Rate to Avoid a Crash (DRAC) and Deceleration-based Surrogate Safety Measure (DSSM), which can represent the three categories based on measuring attributes: temporal proximity, distance and deceleration. At the same time, the time is divided into 30s 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 and proactive prevention and control technologies.

CICTP