This research is a combination of three studies carried out to explore weather impacts on traffic parameters. The first part investigates light rainfall’s impact on uncongested speed during the daytime on a two lane state highway with a detailed statistical analysis and spatially compatible rainfall and speed data. The results show that the speed distribution in light rain conditions is significantly different from the no-rain condition. Light rain causes a drop of 0.9 mph (1.5 km/hr) or 1.8% of speed from the no-rain condition. Variability of speed is not found significantly different between the two conditions. The second part investigates the impact of rainfall on the behaviors of drivers in a car-following state by analyzing the differences in time gap, speed, and following distances of platooned vehicles. Rainy weather conditions resulted in a greater spread in gap and speed distributions. Mean speed reduction and mean time gap increment was found to be 3.7% and 5.6 % respectively. No significant differences were observed between following distances in any weather conditions. This indicates that drivers maintained the same following distances irrespective of weather conditions and reduced speed which caused the time gap increase. The third part was conducted to assess benefit of weather responsive signal retiming. Traffic signal optimization and simulation software were used to assess the impact of rainfall and benefit of retiming on travel time and average delay on a section of a hypothetical roadway. Rainfall increased travel time and average delay as the traffic volume was being increased beyond what would occur without the impacts of precipitation. Signal retiming based on rainy weather traffic parameters resulted in a maximum 6.8% reduction of travel time and 18.52 % of average delay compared to not retiming for weather impacts. These findings suggest that the operational impacts of weather are substantial and there is a strong case for the benefits of weather-based signal timing.
","abstract_html":"<p>This research is a combination of three studies carried out to explore weather impacts on traffic parameters. The first part investigates light rainfall’s impact on uncongested speed during the daytime on a two lane state highway with a detailed statistical analysis and spatially compatible rainfall and speed data. The results show that the speed distribution in light rain conditions is significantly different from the no-rain condition. Light rain causes a drop of 0.9 mph (1.5 km/hr) or 1.8% of speed from the no-rain condition. Variability of speed is not found significantly different between the two conditions. The second part investigates the impact of rainfall on the behaviors of drivers in a car-following state by analyzing the differences in time gap, speed, and following distances of platooned vehicles. Rainy weather conditions resulted in a greater spread in gap and speed distributions. Mean speed reduction and mean time gap increment was found to be 3.7% and 5.6 % respectively. No significant differences were observed between following distances in any weather conditions. This indicates that drivers maintained the same following distances irrespective of weather conditions and reduced speed which caused the time gap increase. The third part was conducted to assess benefit of weather responsive signal retiming. Traffic signal optimization and simulation software were used to assess the impact of rainfall and benefit of retiming on travel time and average delay on a section of a hypothetical roadway. Rainfall increased travel time and average delay as the traffic volume was being increased beyond what would occur without the impacts of precipitation. Signal retiming based on rainy weather traffic parameters resulted in a maximum 6.8% reduction of travel time and 18.52 % of average delay compared to not retiming for weather impacts. These findings suggest that the operational impacts of weather are substantial and there is a strong case for the benefits of weather-based signal timing.</p>","abstract_has_math":false,"creators":["Rahman, Ashrafur"],"institution":null,"degree_name":"Master of Science","degree_level":null,"degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Nicholas E. Lownes; John N. Ivan; Nalini Ravishanker","Nicholas E. Lownes"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-12-18T08:00:00Z","date_published":"2010-12-18T08:00:00Z","updated_at":"2026-07-24T06:31:35Z","subjects":["Traffic","Weather","Rainfall","Speed","Gap","Microsimulation","Traffic Signal","Travel time","Delay"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.lib.uconn.edu/gs_theses/19","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Nicholas E. Lownes; John N. Ivan; Nalini Ravishanker","Nicholas E. 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The first part investigates light rainfall’s impact on uncongested speed during the daytime on a two lane state highway with a detailed statistical analysis and spatially compatible rainfall and speed data. The results show that the speed distribution in light rain conditions is significantly different from the no-rain condition. Light rain causes a drop of 0.9 mph (1.5 km/hr) or 1.8% of speed from the no-rain condition. Variability of speed is not found significantly different between the two conditions. The second part investigates the impact of rainfall on the behaviors of drivers in a car-following state by analyzing the differences in time gap, speed, and following distances of platooned vehicles. Rainy weather conditions resulted in a greater spread in gap and speed distributions. Mean speed reduction and mean time gap increment was found to be 3.7% and 5.6 % respectively. No significant differences were observed between following distances in any weather conditions. This indicates that drivers maintained the same following distances irrespective of weather conditions and reduced speed which caused the time gap increase. The third part was conducted to assess benefit of weather responsive signal retiming. Traffic signal optimization and simulation software were used to assess the impact of rainfall and benefit of retiming on travel time and average delay on a section of a hypothetical roadway. Rainfall increased travel time and average delay as the traffic volume was being increased beyond what would occur without the impacts of precipitation. Signal retiming based on rainy weather traffic parameters resulted in a maximum 6.8% reduction of travel time and 18.52 % of average delay compared to not retiming for weather impacts. These findings suggest that the operational impacts of weather are substantial and there is a strong case for the benefits of weather-based signal timing.
"]},{"key":"dc:title","label":"Title","values":["Weather Impacts on Traffic Parameters and Signal Timing Performance"]}]}],"canonical_facts":{"dc:contributor":["Nicholas E. Lownes; John N. Ivan; Nalini Ravishanker","Nicholas E. Lownes"],"dc:creator":["Rahman, Ashrafur"],"dc:date.available":["2010-12-18T08:00:00Z"],"dc:description.abstract":["This research is a combination of three studies carried out to explore weather impacts on traffic parameters. The first part investigates light rainfall’s impact on uncongested speed during the daytime on a two lane state highway with a detailed statistical analysis and spatially compatible rainfall and speed data. The results show that the speed distribution in light rain conditions is significantly different from the no-rain condition. Light rain causes a drop of 0.9 mph (1.5 km/hr) or 1.8% of speed from the no-rain condition. Variability of speed is not found significantly different between the two conditions. The second part investigates the impact of rainfall on the behaviors of drivers in a car-following state by analyzing the differences in time gap, speed, and following distances of platooned vehicles. Rainy weather conditions resulted in a greater spread in gap and speed distributions. Mean speed reduction and mean time gap increment was found to be 3.7% and 5.6 % respectively. No significant differences were observed between following distances in any weather conditions. This indicates that drivers maintained the same following distances irrespective of weather conditions and reduced speed which caused the time gap increase. The third part was conducted to assess benefit of weather responsive signal retiming. Traffic signal optimization and simulation software were used to assess the impact of rainfall and benefit of retiming on travel time and average delay on a section of a hypothetical roadway. Rainfall increased travel time and average delay as the traffic volume was being increased beyond what would occur without the impacts of precipitation. Signal retiming based on rainy weather traffic parameters resulted in a maximum 6.8% reduction of travel time and 18.52 % of average delay compared to not retiming for weather impacts. These findings suggest that the operational impacts of weather are substantial and there is a strong case for the benefits of weather-based signal timing.
"],"dc:identifier":["https://digitalcommons.lib.uconn.edu/gs_theses/19"],"dc:subject":["Traffic","Weather","Rainfall","Speed","Gap","Microsimulation","Traffic Signal","Travel time","Delay"],"dc:title":["Weather Impacts on Traffic Parameters and Signal Timing Performance"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_name":["Master of Science"]},"updated_at":"2026-07-24T06:31:35Z"}