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Fog is a critical external factor that threatens traffic safety on freeways.Variable speed limit (VSL) control can effectively harmonize vehicle speed andimprove safety. However, most existing weather-related VSL controllers arelimited to adapt to the dynamic traffic environment. This study developedoptimal VSL control strategy under fog conditions with fully consideration offactors that affect traffic safety risks. The crash risk under fog conditionswas estimated using a crash risk prediction model based on Bayesian logisticregression. The traffic flow with VSL control was simulated by a modified celltransmission model (MCTM). The optimal factors of VSL control were obtained bysolving an optimization problem that coordinated safety and mobility with thehelp of the genetic algorithm. An example of I-405 in California, USA wasdesigned to simulate and evaluate the effects of the proposed VSL controlstrategy. The optimal VSL control factors under fog conditions were comparedwith sunny conditions, and different placements of VSL signs were evaluated.Results showed that the optimal VSL control strategy under fog conditionschanged the speed limit more cautiously. The VSL control under fog conditionsin this study effectively reduced crash risks without significantly increasingtravel time, which is up to 37.15% reduction of risks and only 0.48% increaseof total travel time. The proposed VSL control strategy is expected to be ofgreat use in the development of VSL systems to enhance freeway safety under fogconditions.

Optimal Variable Speed Limit Control Strategy on Freeway Segments under Fog Conditions