Type of Document	Thesis
Author	Zhu, Kangyuan
Author's Email Address	kangyuan_z@yahoo.com
URN	etd-05242004-195534
Title	Traffic Capacity and Speed Analyses of Freeway Work Zones Based on Computer Simulation
Degree	Master of Science
Department	Civil and Environmental Engineering, Department of
Advisory Committee	Advisor Name Title W. Virgil Ping Committee Chair Leonard J. Tung Committee Member Renatus Nyakiamo Mussa Committee Member
Keywords	Simulation Work Zone Capacity Speed CORSIM
Date of Defense	2004-05-20
Availability	unrestricted
Abstract Traffic capacity, queue discharge rates and vehicle speeds at work zones were equally essential in assessment of work zone performance and traffic operation. This study was conducted to analyze the traffic flow characteristics in freeway work zones based on the traffic data collected from CORSIM simulation. A total seven related factors were input into CORSIM software and 129,600 times of CORSIM simulation were run in the designed experiments. In the capacity and queue discharge rate analyses, it was found that capacity could not be obtained definitely on the onset of congested traffic conditions at work zones although the probability to reach the maximum flow rate on the onset of congested traffic conditions was the highest. With analysis of variance, it was found that almost all the levels in each selected factor were statistical significant with respect to the capacity and mean queue discharge rate. The additive regression models of capacity and mean queue discharge rate with the related factors were obtained. The capacity regression models had R-Square 0.903 and 0.726 respectively with or without considering the interaction effects of two factors. However, the models for mean queue discharge rate had R-Square 0.944 and 0.762 respectively with or without considering the interaction effects of two factors. The results showed that consideration of interaction effects of factors would improve the fitness of models greatly. In addition, mean queue discharge rate was more stable to estimate than the capacity. Number of simulation runs required for capacity analyses at work zones was also studied. It was found that 5 times of simulation runs were adequate for capacity analyses with 95% confident level within 5% estimation errors. In speed analyses, under uncongested traffic conditions, the speeds along freeway work zones were controlled mainly by the FFS (or Speed Limit) although there were some minor fluctuations in the traffic flow. However, under congested traffic conditions the speed characteristics were much more complex and the standard deviation of vehicle speeds were much larger. The speed patterns under congested traffic conditions could be divided into seven sections each with different traffic flow characteristics. Since the large standard deviations of the point speeds, only space-mean speed in three sections out of the seven sections was analyzed. Additive regression models of space-mean speed with related factors were developed under both congested and uncongested traffic conditions. The results showed space-mean speed models under uncongested traffic conditions had R-Square 0.902 and 0.870 respectively with or without considering the interaction effects of two factors. However, under congested traffic conditions, space-mean speed models had R-Square 0.801 and 0.742 respectively with or without considering the interaction effects of two factors. It indicated that it was more difficult to estimate speeds under congested traffic flow. In addition, simulation runs were analyzed for space-mean speed estimation at freeway work zones. The results showed 5 times of simulation runs were adequate for speed analyses with 95% confident level within 10% estimation errors under uncongested traffic conditions. However, under congested traffic conditions, 7 or more times of simulation runs were preferred.
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