Crash Risk Monitoring Method for Highways in Rain and Fog Conditions
DOI:
https://doi.org/10.54097/g70y7t84Keywords:
Collision risk, braking distance, python, HighDAbstract
As the volume of traffic on highways has increased, so too has the frequency of accidents. In particular, the risk of vehicular accidents is heightened in inclement weather conditions, such as precipitation and low visibility, due to the combined effect of reduced visibility and a slippery road surface. It is therefore of great significance to develop an effective method for monitoring the risk of collisions on highways in order to reduce the incidence of traffic accidents and ensure driving safety. This paper will examine the monitoring of highway collision risk in inclement weather conditions, namely rain and fog. The analysis will assess the collision risk in real time by evaluating the spacing and speed of vehicles. Furthermore, the utilisation of Python technology will facilitate the visualisation and characterisation of the risk situation.
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