Traffic flow modeling in fog with cellular automata model

To explore the traffic flow characteristics in fog, a modified one-dimensional cellular automata model is developed considering the limited visual distance of drivers in low visibility. We suppose that drivers can be categorized into seven groups according to the radical degree, and the number of drivers follows the Gaussian distribution in general road system. Capacity shrinkage is confirmed, and there is a positive correlation between the speed limits and extent of capacity shrinkage. When on-ramp bottleneck is considered in open boundary condition, bottleneck capacity fluctuates greatly when enter probability of on-ramp is lower than the threshold, and the dependency between main lane capacity and distance away from on-ramp is weak in most cases. Besides, capacity phase diagrams of various test scenario show that the bottleneck capacity will not improve after the entry probability of the main lane reaches a certain value. This study can be an inspiration for traffic flow modeling in fog and other infrequent weather.

Automated summary

The study reveals that in foggy conditions, traffic flow characteristics include capacity shrinkage and weak dependency between the main lane capacity and the distance away from the on-ramp bottleneck. This provides insights for modeling traffic flow in fog and other infrequent weather conditions.