On the analytical approximation of joint aggregate queue-length distributions for traffic networks: A stationary finite capacity Markovian network approach

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• 作者：Carolina Osorio ; ^{osorioc@mit.edu} ; Carter Wang ^{carterw@mit.edu}
• 刊名：Transportation Research Part B: Methodological
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：95
• 期：Complete
• 页码：305-339
• 全文大小：2656 K
• 卷排序：95

文摘

This paper proposes an analytical network model that approximates joint queue-length distributions and addresses the curse of dimensionality by combining ideas from decomposition methods with aggregation-disaggregation techniques. The model is formulated as a system of nonlinear equations with a dimension that is linear, instead of exponential, in the number of queues and that is independent of the space capacity of the individual queues. This makes it computationally tractable and scalable, it can be efficiently used for the higher-order distributional analysis of large-scale networks. The model is used it to address an urban traffic control problem. We show the added value of accounting for higher-order spatial between-queue dependency information in the control of congested urban networks. This paper contributes to the development of analytical traffic models that provide a higher-order description of between-link dependencies. This is particularly important for the design and operations of congested urban networks prone to the occurrence of spillbacks.