Adverse weather condition is an important factor threatening driving safety. This study mainly focuses on exploring rear-end collision risks of car-following vehicles under adverse weather conditions. Based on the observations of car following behaviors and weather conditions on a rural highway, some indicators are designed to measure rear-end collision risk. After the trails of each candidate indicator based on collected data, the indictor, namely the following risk (FRI), is selected to evaluate rear-end collision risk. A generalized linear model (GLM) is established to assess the impact of different weather conditions on the risk. The results show that in terms of the effect of a single factor, the light condition has the greatest influence on the risk, followed by weather condition or road condition. Meanwhile, interactive influence of the two factors is determined by specific car-following states. Cars and trucks are affected by weather condition and road condition in different way. The interaction between each factor and light condition always has the greatest impact on rear-end collision risk.

Adverse weather, Car following, Rear-end collision risk, generalized linear model