Low visibility conditions can inhibit a driver's ability to perceive appropriate operating speeds, particularly during foggy conditions in which the characteristics of the fog can vary spatiotemporally. By reducing visibility and contrast in the visual field, fog obscures crucial driving cues essential for perceiving depth and speed. Studies have shown that fog-related crashes are more likely to involve multiple vehicles and severe injuries than crashes during clear conditions. Numerous agencies have installed countermeasures such as weather advisory systems and variable speed limits (VSLs) to mitigate these conditions, but not many studies have quantitatively analyzed the results of these countermeasures. In October 2016, the Virginia Department of Transportation (VDOT) activated a VSL system on a 12-mile section of I-77 that runs through mountainous terrain in southwestern Virginia. The area is known to have severe, recurring fog events, so the VSL system was installed to reduce the quantity and severity of crashes in the corridor. This study assessed how the I-77 VSL system has affected speeds and crash characteristics since its activation. Before the installation of the VSL, drivers frequently drove much faster than the safe speed based on the stopping sight distance during fog. The purpose of the VSL system was to influence drivers to travel closer to the safe speed during reduced visibility events by posting appropriate reduced speed limits. The analysis examined the effect of the VSL system on driver speeds before and after activation at a single site and after activation across the corridor. Effects on crashes for the entire corridor were also examined. The results showed statistically significant reductions in mean speeds and variances after the VSL was activated, and drivers drove closer to the safe speed based on available visibility. Models developed to understand how the VSL system affected speed as a function of visibility showed that speeds were reduced by a statistically significant amount when VSLs were active. Trends in speed by posted speed limit were examined across the corridor, and it was found that compliance generally improved once drivers encountered reduced visibilities. Speeds did not change as much in transition areas leading into the area where the fog was present, however. Crash analysis revealed only two fog-related crashes in the after period, yielding reduced crash rates during low visibility conditions and indicating improved safety. These safety results are considered preliminary, however, because of limited after data. The results of this VSL implementation may be used to refine the current VSL control algorithm to improve compliance even further and could also serve as a reference for other agencies contemplating alternatives to improve safety at fog-prone areas. Given the results, it is recommended that VDOT's Southwest Region Operations convene a group to modify the VSL control algorithm. It is further recommended that the Virginia Transportation Research Council re-evaluate the safety effects of the system after at least 3 years of after data are available to make a more definitive determination of the safety effects of the system and to determine its return on investment. Implementation of these recommendations could further improve the efficacy of the system and result in a better quantification of the full benefits of the system.

In Virginia, sections of I-77 and I-64 in mountainous parts of the state have significant recurring fog events. These locations have also been the sites of several chain reaction crashes involving more than 50 vehicles during fog. These crashes were typically caused by drivers traveling too fast for the visibility conditions. To improve safety on the I-77 corridor, the Virginia Department of Transportation constructed a variable speed limit (VSL) system that posts dynamic speed limits based on the visibility condition. As of April 2016, the system was undergoing pre-deployment testing. Before the system was activated, it was important to understand existing driver speed choice behavior during low visibility conditions. It was possible that posting a VSL speed based only on the stopping sight distance (SSD) could create significant speed variance and decrease safety if drivers were driving much faster than conditions would warrant. In this study, crash, speed, and visibility data were examined at several locations on I-64 and I-77 where there were recurring fog events. The crash history for I-77 revealed that crashes during low visibility conditions were more likely to be severe and involve more than two vehicles than crashes during clear conditions. Mean speed analysis found that observed mean speeds exceeded safe speeds for all low visibility conditions and at all sites. In the worst visibility conditions, drivers often exceeded the safe speed by more than 20 mph. Standard deviation analysis found that speed variance did not increase as visibility decreased on I-77, but for several locations on I-64, the standard deviation was different during low visibility when compared to clear conditions. Models were developed to allow a better understanding of the relationship between speed and visibility. The models showed that although motorists reduce their speeds in low visibility, there is still a significant differential between observed speeds and the safe speed calculated using the SSD. The models showed that speeds for I-64 were much less sensitive to changes in visibility compared to I-77. A possible explanation for this difference is the presence of illuminated in-pavement markers on I-64. The improved delineation provided by these markers during foggy conditions may cause drivers to perceive less of a need to reduce speed during limited visibility. It is also possible that mean speeds in low visibility conditions are higher on I-64 because of the regular commuters who may be more comfortable driving during foggy conditions. The observed driver behavior from this study is being used as a basis for the VSL control algorithm that is being implemented in the field. A primary concern of the operators of the VSL system is that it will not be heeded by all motorists and thus will result in increased speed variance in foggy conditions. The developed model was used to create a VSL control algorithm to help bridge the gap between current driver behavior and safe speed. It is recommended that future VSL system deployments reflect existing driver behavior in the initial algorithms as well. After VSL activation, speed and crash data for I-77 should be analyzed to determine the operational and safety effects of the system. If the system on I-77 reduces the frequency and severity of crashes, improves speed limit compliance, and reduces speed variance, a similar system should be developed for I-64 using the current driver behavior models from this study as part of the initial algorithm.

In Virginia, sections of I-77 and I-64 in mountainous parts of the state have significant recurring fog events. These locations have also been the sites of several chain reaction crashes involving more than 50 vehicles during fog. These crashes were typically caused by drivers traveling too fast for the visibility conditions. To improve safety on the I-77 corridor, the Virginia Department of Transportation constructed a variable speed limit (VSL) system that posts dynamic speed limits based on the visibility condition. As of April 2016, the system was undergoing pre-deployment testing. Before the system was activated, it was important to understand existing driver speed choice behavior during low visibility conditions. It was possible that posting a VSL speed based only on the stopping sight distance (SSD) could create significant speed variance and decrease safety if drivers were driving much faster than conditions would warrant. In this study, crash, speed, and visibility data were examined at several locations on I-64 and I-77 where there were recurring fog events. The crash history for I-77 revealed that crashes during low visibility conditions were more likely to be severe and involve more than two vehicles than crashes during clear conditions. Mean speed analysis found that observed mean speeds exceeded safe speeds for all low visibility conditions and at all sites. In the worst visibility conditions, drivers often exceeded the safe speed by more than 20 mph. Standard deviation analysis found that speed variance did not increase as visibility decreased on I-77, but for several locations on I-64, the standard deviation was different during low visibility when compared to clear conditions. Models were developed to allow a better understanding of the relationship between speed and visibility. The models showed that although motorists reduce their speeds in low visibility, there is still a significant differential between observed speeds and the safe speed calculated using the SSD. The models showed that speeds for I-64 were much less sensitive to changes in visibility compared to I-77. A possible explanation for this difference is the presence of illuminated in-pavement markers on I-64. The improved delineation provided by these markers during foggy conditions may cause drivers to perceive less of a need to reduce speed during limited visibility. It is also possible that mean speeds in low visibility conditions are higher on I-64 because of the regular commuters who may be more comfortable driving during foggy conditions. The observed driver behavior from this study is being used as a basis for the VSL control algorithm that is being implemented in the field. A primary concern of the operators of the VSL system is that it will not be heeded by all motorists and thus will result in increased speed variance in foggy conditions. The developed model was used to create a VSL control algorithm to help bridge the gap between current driver behavior and safe speed. It is recommended that future VSL system deployments reflect existing driver behavior in the initial algorithms as well. After VSL activation, speed and crash data for I-77 should be analyzed to determine the operational and safety effects of the system. If the system on I-77 reduces the frequency and severity of crashes, improves speed limit compliance, and reduces speed variance, a similar system should be developed for I-64 using the current driver behavior models from this study as part of the initial algorithm.