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• W2182173516 abstract "Traffic congestion in urban areas has continued its ever-increasing trend during the past years. It increases delay, fuel consumption, greenhouse gas emissions, and consequently environmental pollutions. In addition, only in the United States traffic congestion caused urban travelers to purchase an extra 3.9 billion gallons of fuel with a cost of $115 billion. Proper management of traffic supply and demand especially in urban areas could potentially reduce some of these costs associated with delay, fuel consumption, etc.. This can be achieved by optimizing the duration of traffic light signals and optimizing traffic assignment in an urban network. Signal timing optimization in realistic transportation networks under realistic conditions is an extremely challenging task. First, there is no closed-form formulation to represent the objective function in terms of the decision variables. Therefore, methods that rely on knowing the structure of the objective function cannot be used. Second, the decision space of the problem is extremely large. This makes traditional search methods such as exhaustive search and dynamic programming unsuccessful in solving the problem." @default.
• W2182173516 created "2016-06-24" @default.
• W2182173516 creator A5086598856 @default.
• W2182173516 date "2012-06-27" @default.
• W2182173516 modified "2023-09-26" @default.
• W2182173516 title "Intelligent dynamic signal timing optimization program" @default.
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• W2182173516 hasPublicationYear "2012" @default.
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