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 indicatorfain fog is much higher than normal weather when cellular occupancyρ<0.5. After taking intermittent release measures, the magnitude offawill drop from 10−4to 10−5under 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 intervalhtbetween adjacent fleets and the maximum number of vehicles𝒬maxwhich 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.
Highlights
Traffic accidents happen frequently in heavy fog weathers
Freeway intermittent release measures mainly include the vehicle number N of each fleet and the time interval ht Figure 8 shows the simulation results of the average probability of a car in a traffic accident when passing through the fog zone
To explore the impact of heavy fog on traffic, including speed, capacity, and safety, an improved cellular automaton model which considers specific driving behaviors was proposed in this paper
Summary
Traffic accidents happen frequently in heavy fog weathers. Freeways are frequently closed in heavy fog, which seriously affects travelers’ mobility, and brings a great deal of economic losses. To reduce losses and take into account the traffic safety, some areas start to use intermittent release measures instead of road closures in heavy fog weather. Previous studies show that low visibility and specific driving behaviors in heavy fog are the two key risk factors that impact on the measures [4,5,6,7]. The intermittent release measures can be simulated by using cellular automaton (CA) model of traffic. This paper proposes an improved cellular automaton model of traffic that considers driving behaviors in heavy fog, in order to study the freeway intermittent release measures and reduce the fog related traffic risk. A reasonable release number and time interval of the fleets are determined
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