Effect Analysis of Intermittent Release Measures in Heavy Fog Weather with an Improved CA Model

Abstract

Heavy fog may easily cause traffic accidents; thus freeway closures are frequently taken in order to ensure traffic safety in China, which not only seriously affect the travel of people, but also bring great economic losses. This paper studies the fog related risk of rear-end collisions and the intermittent release measures taken to reduce such risk; meanwhile, an improved cellular automaton model considering driving behaviors in heavy fog is proposed. The simulation results indicate that the risk indicator fa in fog is much higher than normal weather when cellular occupancy ρ<0.5. After taking intermittent release measures, the magnitude of fa will drop from 10−4 to 10−5 under the same fog condition, which greatly enhances the safety. In addition, this paper concludes the appropriate vehicle number released for each time and the time interval ht between adjacent fleets and the maximum number of vehicles 𝒬max which can be released per hour. These results can be used as theoretical basis and reference for the traffic management departments to develop intermittent release measures.