Loading...
| Friend's email | |
| Your name | |
| Your email | |
| enter code | |
This page was sent successfuly
- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 47876 (09)
- University: Sharif University of Technology
- Department: Civil Engineering
- Advisor(s): Nassiri, Habibollah
- Abstract:
- For any country, the road system is an important part of its infrastructure which can affect economic development. A good level of service for a road system requires implementation of work zone projects to maintain it which usually close one or more of the lanes available for traffic. Lane reductions could cause a disturbance to normal traffic flow and speed reductions, further resulting in a reduction of road capacity and an increase of traffic delay. In addition, work zone capacity and traffic delay are the two critical indices to determine whether the effectiveness of traffic control systems is acceptable or not. Hence, the accurate estimation of capacity and traffic delay in work zones is of utmost importance. In this study, three adaptive Neuro-Fuzzy logic models using 15 different variables are proposed for estimation of the freeway work zone capacity. Data for training, checking, and testing of the models were collected from the existing literature. In the first model all of the variables and datasets are used. However, in the second model 3 of variables, which had low correlation with work zone capacity, are not considered in modeling process and in the third model some of datasets are eliminated. In the meantime, the empirical model proposed by Kim is selected for comparison of results of models proposed in this study. RMSE of the first, second, third, and Kim model for testing datasets is respectively 27%, 15%, 10%, and 16% of average Work Zone capacity. Comparing these relative error percents reckons that the third Neuro-Fuzzy model, which is developed by using 12 variables, is the most accurate model. The variables used in this model are: Lane width, Heavy vehicle percent, Work zone length, Speed Limit, Number of closed lanes, Number of open lanes, Work intensity, Night-time operation, Continuous operation, Ramp presence, Work zone grade, and Work zone duration. Finally, queue delays and lengths are computed using a deterministic traffic flow model based on the estimated work zone capacity
- Keywords:
- Work Zone ; Capacity ; Delay ; Adaptive Neuro-Fuzzy Inference System (ANFIS) ; Maintenance ; Travel Time ; Truncation
Digital Object List
-
محتواي کتاب
- view
Bookmark