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In Florida, low visibility roadway environment due to fog is one of the major traffic safety concerns. It is known that in low visibility conditions, such as fog and smoke, crashes tend to be more severe than under normal clear conditions. Thus, there is a drastic need to test and develop countermeasures to improve driver safety and performance under reduced visibility conditions. The research team will study the human factors issues relevant to implementing a visibility system on Florida's highways. Specifically, design driver simulator experiments to evaluate how drivers respond to low visibility warning strategies such as effective messaging plans using VMS (Variable Message Sign), different combinations of warning types (e.g., messages, sound, vibration, etc.) using in-vehicle warning device, and implementation of engineering countermeasures. The research team will investigate the effectiveness of warning strategies on low visibility conditions utilizing driving simulator. Various low visibility warning systems will be tested for different combinations of scenarios to assistant drivers' decisions or avoid certain type of crashes. Based on the tested results of driver behaviors, can examine which warning types are the most safety effective among the various types such as messages (e.g., sentence, pictogram, etc.), sound, and vibration. Furthermore, identify additional countermeasures (e.g., LED RPM (Raised Pavement Marker), etc.) to improve driver safety under reduced visibility conditions from Worldwide experience (e.g., Korea, Japan, European countries, etc.) and investigate the effects, if it is needed. Hence, the research team will propose the best strategy to enhance roadway safety under low visibility conditions. Moreover, the results from this research can be used in micro-simulation (e.g., VISSIM) and enable to estimate corridor-level safety effectiveness and benefits of the proposed low-visibility warning system under different roadway conditions such as connected vehicle (CV), managed lane, etc.