基于拥挤约束的路边停车资源优化
Optimizing Curbside Parking Resources Subject to Congestion Constraints
摘要：
为了从理论上深入了解停车稀缺和拥堵之间的关系，我们将路边停车场的块面描述为一个排队网络。由于该网络的性质，我们无法获得规范的排队网络结果。我们提出了一种新的排队网络受到客户拒绝，由于缺乏可用的服务器。我们提供的条件，这样的网络是稳定的，一个计算上易处理的“单节点”这样的网络，并显示，通过价格控制这样的队列，最大限度地提高占用率，并受到限制的队列之间的允许拥塞搜索一个可用的服务器，是一个凸优化问题。我们展示了这种方法在旧金山任务区的应用，我们的研究结果表明，由于司机寻找停车场的交通拥堵源于停车资源的空间利用效率低下。
英文摘要：
To gain theoretical insight into the relationship between parking scarcity and congestion, we describe block-faces of curbside parking as a network of queues. Due to the nature of this network, canonical queueing network results are not available to us. We present a new kind of queueing network subject to customer rejection due to the lack of available servers. We provide conditions for such networks to be stable, a computationally tractable "single node" view of such a network, and show that maximizing the occupancy through price control of such queues, and subject to constraints on the allowable congestion between queues searching for an available server, is a convex optimization problem. We demonstrate an application of this method in the Mission District of San Francisco; our results suggest congestion due to drivers searching for parking stems from an inefficient spatial utilization of parking resources.
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