UVM Theses and Dissertations
Format:
Print
Author:
Agbolosu-Amison, Seli James
Dept./Program:
Civil and Environmental Engineering
Year:
2004
Degree:
M.S.
Abstract:
Congestion along arterial systems in New England is often the result of adverse weather conditions. Snow and icy conditions typically change the normal traffic flow parameters, which could render the normal signal plans unsuitable. With recent advances in communications and signals' hardware, there is a need to explore the feasibility and likely operational benefits of implementing signal-timing plans, specifically tailored for inclement weather conditions. For this purpose, a better understanding of the impact of inclement weather on traffic flow parameters at signalized intersections and also the feasibility and likely operational benefits of designing and implementing "special" timing plans for inclement weather conditions are required. This thesis describes a study designed to "Validate Traffic Simulation Models to Inclement Weather Travel Conditions with Applications to Arterial Coordinated Signal Systems in Northern New England".
For the impact of inclement weather on the values of saturation headways and start up lost times at signalized intersections, a signalized intersection located in the City of Burlington, Vermont was selected. Winter data were collected for two winter seasons (2002-2003 and 2003-2004). For 2002-2003 winter season, at least 30 hours of video taped data were collected over a period of 3 months. Also, for 2003-2004 winter season, at least 48 hours of video-taped data were collected over 4 months. The weather/road surface conditions were categorized into six different classes, and values for the saturation headways and startup lost times were collected for each weather condition. Statistical analyses were then performed on the data, which revealed that inclement weather does have a significant impact on the values of saturation headways, particularly once slushy conditions start developing or once snow start sticking to the ground. Startup lost times, on the other hand, do not appear to be significantly impacted by inclement weather in comparison to the significant impact on saturation headways. The study also shows that the impact of inclement weather appears to be a function of the grade of the intersections approach.
To assess the likely operational benefits of designing and implementing "special" timing plans for inclement weather conditions, two signalized arterial corridors were selected as case studies. They are Vermont 15 and Dorset Street. Optimal signal plans were developed for these corridors for the six different weather/road surface conditions using both TRANSYT-7F and SYNCHRO models. The likely benefits of designing and implementing "special" plans for inclement weather were then determined by comparing travel conditions under the optimal inclement weather timing plans, to travel conditions assuming the optimal "Dry" condition plan would remain unchanged. This comparison was performed utilizing the macroscopic models of TRANSYT-7F and SYNCHRO models first, and then using the more detailed microscopic simulation environment of CORSIM and SIMTRAFFIC models. Results from the study indicate that operational benefits are to be expected from implementing "special" signal plans for inclement weather, especially once slushy conditions start developing or once snow starts sticking to the ground. The study also shows that the benefits estimated from the use of macroscopic, deterministic models tend to be significantly higher than those determined by stochastic, microscopic models.
For the impact of inclement weather on the values of saturation headways and start up lost times at signalized intersections, a signalized intersection located in the City of Burlington, Vermont was selected. Winter data were collected for two winter seasons (2002-2003 and 2003-2004). For 2002-2003 winter season, at least 30 hours of video taped data were collected over a period of 3 months. Also, for 2003-2004 winter season, at least 48 hours of video-taped data were collected over 4 months. The weather/road surface conditions were categorized into six different classes, and values for the saturation headways and startup lost times were collected for each weather condition. Statistical analyses were then performed on the data, which revealed that inclement weather does have a significant impact on the values of saturation headways, particularly once slushy conditions start developing or once snow start sticking to the ground. Startup lost times, on the other hand, do not appear to be significantly impacted by inclement weather in comparison to the significant impact on saturation headways. The study also shows that the impact of inclement weather appears to be a function of the grade of the intersections approach.
To assess the likely operational benefits of designing and implementing "special" timing plans for inclement weather conditions, two signalized arterial corridors were selected as case studies. They are Vermont 15 and Dorset Street. Optimal signal plans were developed for these corridors for the six different weather/road surface conditions using both TRANSYT-7F and SYNCHRO models. The likely benefits of designing and implementing "special" plans for inclement weather were then determined by comparing travel conditions under the optimal inclement weather timing plans, to travel conditions assuming the optimal "Dry" condition plan would remain unchanged. This comparison was performed utilizing the macroscopic models of TRANSYT-7F and SYNCHRO models first, and then using the more detailed microscopic simulation environment of CORSIM and SIMTRAFFIC models. Results from the study indicate that operational benefits are to be expected from implementing "special" signal plans for inclement weather, especially once slushy conditions start developing or once snow starts sticking to the ground. The study also shows that the benefits estimated from the use of macroscopic, deterministic models tend to be significantly higher than those determined by stochastic, microscopic models.