Intelligent dynamic signal timing optimization program
Intelligent dynamic signal timing optimization program
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发表时间：
2012-06
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通讯作者：
Ali Hajbabaie
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作者：
Ali Hajbabaie
在过去的几年里，城市地区的交通拥堵继续呈日益严重的趋势。它增加了延误、燃料消耗、温室气体排放，从而导致环境污染。此外，仅在美国，交通拥堵就导致城市旅客额外购买了39亿加仑的燃料，花费了1150亿美元。对交通供需进行适当的管理，特别是在城市地区，可能会潜在地减少与延误、燃料消耗等相关的一些成本。这可以通过优化交通灯信号的持续时间和优化城市网络中的交通分配来实现。现实条件下现实交通网络信号配时优化是一项极具挑战性的任务。首先，没有封闭形式的公式来表示决策变量方面的目标函数。因此，不能使用依赖于知道目标函数结构的方法。第二，问题的决策空间非常大。这使得穷举搜索和动态规划等传统的搜索方法无法解决问题。
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.