New algorithms for parking demand management and a city-scale deployment
New algorithms for parking demand management and a city-scale deployment
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停车需求管理和城市规模部署的新算法
DOI：
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发表时间：
2014
期刊：
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通讯作者：
J. Andreoli
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文献类型：
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作者：
O. Zoeter;C. Dance;S. Clinchant;J. Andreoli
路边停车场，就像任何公共设施一样，如果免费使用或价格远远低于市场价格，就会被低效使用。本文介绍了一种新的需求管理解决方案：使用来自专用占用传感器的数据，迭代方案更新停车费率，以更好地匹配需求。新费率鼓励停车者避开高峰时段和高峰位置，减少拥堵和使用不足。解决方案故意简单，以便易于理解，容易被认为是公平的，并导致容易记住和采取行动的停车政策。我们研究了迭代格式的收敛性质，并证明了它收敛到一个合理的分布的一个非常大的一类模型。自2012年6月以来，该算法被用于改变洛杉矶市中心6000多个停车位的停车费，作为洛杉矶快车公园项目的一部分。初步结果令人鼓舞，拥挤和使用不足的情况有所减少，而在更多的地点，费率下降而不是增加。
On-street parking, just as any publicly owned utility, is used inefficiently if access is free or priced very far from market rates. This paper introduces a novel demand management solution: using data from dedicated occupancy sensors an iteration scheme updates parking rates to better match demand. The new rates encourage parkers to avoid peak hours and peak locations and reduce congestion and underuse. The solution is deliberately simple so that it is easy to understand, easily seen to be fair and leads to parking policies that are easy to remember and act upon. We study the convergence properties of the iteration scheme and prove that it converges to a reasonable distribution for a very large class of models. The algorithm is in use to change parking rates in over 6000 spaces in downtown Los Angeles since June 2012 as part of the LA Express Park project. Initial results are encouraging with a reduction of congestion and underuse, while in more locations rates were decreased than increased.