Determination of Freeway Recommended Speed Based on Safety Risk Under Adverse Weather Conditions

Abstract:

To improve the safety of freeway traffic in adverse weather， a method for determining the freeway recommended speed under adverse weather based on safety risk is proposed. Considering the influencing factors of traffic safety risk， a traffic risk assessment model is established based on Bayesian logistic regression， while the fuzzy C-means clustering algorithm is used to classify the traffic risk and obtain the risk threshold. A two-step calculation method for safe vehicle speed under different weather conditions is proposed. Firstly， the 85 %th vehicle speed of the vehicle running speed in the traffic flow state where the risk is less than the threshold is selected as the initial safe driving speed. Then， the principle of parking line of sight is used to correct the speed， in order to obtain the final recommended speed of the freeway in adverse weather. Taking G15 Shenhai Expressway （Shanghai section） as an example， the recommended speed of the freeway under different visibility conditions in foggy days is given.