论文标题
一种用于停车位搜索的理论方法，其停车场信息有限
A Game Theoretic Approach for Parking Spot Search with Limited Parking Lot Information
论文作者
论文摘要
我们提出了一种游戏理论方法，以解决在停车场寻找可用停车位的问题，并选择``最佳''一个人进行停车。该方法利用了停车场提供的有限信息，即其布局和当前的汽车数量。考虑到此类信息可以或可以轻松地用于许多结构化停车场的事实，因此建议的方法可以适用，而无需对现有停车设施进行重大更新。对于大型停车场，将基于抽样的策略与拟议的方法集成在一起，以克服相关的计算挑战。将所提出的方法与文献中的基于启发式的停车位搜索策略进行了比较，并通过模拟研究将其优势证明了其实现较低的成本功能值的优势。
We propose a game theoretic approach to address the problem of searching for available parking spots in a parking lot and picking the ``optimal'' one to park. The approach exploits limited information provided by the parking lot, i.e., its layout and the current number of cars in it. Considering the fact that such information is or can be easily made available for many structured parking lots, the proposed approach can be applicable without requiring major updates to existing parking facilities. For large parking lots, a sampling-based strategy is integrated with the proposed approach to overcome the associated computational challenge. The proposed approach is compared against a state-of-the-art heuristic-based parking spot search strategy in the literature through simulation studies and demonstrates its advantage in terms of achieving lower cost function values.
