Analysis of the Impact of Fog-Related Reduced Visibility on Traffic Parameters

There are few research studies that addressed the impact of reduced visibility due to fog using real-time data. It is thus meaningful to conduct further investigation that can clearly describe the changes in driving behavior and traffic parameters under foggy conditions using real-time traffic and weather data. Field traffic and weather data were collected in this research and fog cases were selected and analyzed by comparing them with clear cases to identify the differences in traffic characteristics under the two different situations. Moreover, vehicles were classified into two types (i.e., passenger cars and trucks) to identify whether the impact of reduced visibility due to fog on traffic varies depending on vehicle types. Afterward, the traffic parameters under different visibility classes and the effects of reduced visibility on different lanes were analyzed using ANOVA. Finally, a matched case–control logistic regression model was applied to further confirm the relationship between traffic parameters and reduced visibility due to fog. It was concluded that the impact of fog on traffic varies by vehicle types and lanes. The impact was also different by visibility classes. The impact of reduced visibility on passenger cars is more significant compared with that on trucks. The effect of reduced visibility on traffic parameters is more significant on inner lanes than outer lanes. Under these weather conditions, drivers should pay more attention to the traffic because higher headway variance is more likely to result in the crash occurrence. The matched case–control logistic regression modeling results indicate that larger average headway, speed variance, headway variance, and occupancy were related to the increase of the likelihood of a reduced visibility. The results would be helpful to understand the change of traffic status and investigate the potential factors for higher crash frequency under foggy conditions.