Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/412723
Title: | Intelligent intersection with advance traffic signal control using fuzzy inference system |
Researcher: | Agrawal, Aditi |
Guide(s): | Paulus, Rajeev |
Keywords: | Engineering Engineering and Technology Engineering Electrical and Electronic |
University: | Sam Higginbottom Institute of Agriculture, Technology and Sciences |
Completed Date: | 2022 |
Abstract: | newline Due to population growth, immigration and social, economic and cultural changes the urban newlinecommunities are rapidly changing and evolving. Increased traffic in urban areas lead to newlinesignificant concerns such as road blockage, transportation delay, pollution level, fuel newlineconsumption, etc. Traffic congestion influence the quality of life, road safety, effect on newlineenvironment and travel time. Traffic signals implemented at intersections play a significant newlinerole in effectively controlling the traffic movement. With the exponential increase in traffic the newlineconventional pre-timed traffic lights become insufficient in managing traffic clearance which newlineleads to heavy traffic congestion at intersection. Another major issue is that the Emergency newlinevehicles like ambulance, police van, fire brigade experience prolonged waiting time to cross newlinethe intersection. For these reasons, with the development of smart intersections with the aid of newlineexisting technologies, including fuzzy logic, neural networks, artificial intelligence, newlinemultiprocessor systems etc. can help to provide solution and improve the urban traffic newlinemanagement problems. Smart cities are increasingly adopting solutions by using adaptive and newlineintelligent approach to develop smart traffic lights to improve the traffic flow at intersections. newlineSince fuzzy logic is the method to deal with uncertainty issues and traffic flow usually contains newlineuncertainty, fuzzy controllers can be an alternative to manage traffic at intersections. Research newlinein fuzzy logic-based traffic signal control is getting inspired by the results which indicate better newlineperformance compared to traditional traffic signal controls, specifically during heavy and newlineuneven traffic volume conditions. This thesis makes contribution in developing intelligent and newlineadaptive systems to resolve traffic congestion problems at single and connected intersections newlinewith an objective to improve traffic clearance and prioritize passage of Emergency vehicle at newlinean isolated intersection. |
Pagination: | |
URI: | http://hdl.handle.net/10603/412723 |
Appears in Departments: | Faculty of Engineering and Technology |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 429.24 kB | Adobe PDF | View/Open |
02_declaration.pdf | 574.65 kB | Adobe PDF | View/Open | |
03_certificate.pdf | 584.32 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 349.64 kB | Adobe PDF | View/Open | |
05_content.pdf | 420.67 kB | Adobe PDF | View/Open | |
06_list of graph and table.pdf | 414 kB | Adobe PDF | View/Open | |
07_chapter 1.pdf | 888.85 kB | Adobe PDF | View/Open | |
08_chapter 2.pdf | 545.31 kB | Adobe PDF | View/Open | |
09_chapter 3.pdf | 3.13 MB | Adobe PDF | View/Open | |
10_chapter 4.pdf | 1.75 MB | Adobe PDF | View/Open | |
11_bibliography.pdf | 725.63 kB | Adobe PDF | View/Open | |
12_annexure.pdf | 524.96 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 853.81 kB | Adobe PDF | View/Open | |
abstract.pdf | 407.46 kB | Adobe PDF | View/Open |
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