This study investigates the starting point of parking search, presenting new findings through empirical and theoretical approaches. It introduces a probabilistic model that describes the transition from normal driving to actively searching for parking, aiming to minimize journey costs. The model is tested using real-world data collected via a smartphone app that tracks the start of parking searches. Results validate the model, showing that drivers are more likely to begin searching for parking earlier when parking spaces are scarce and driving speeds are reduced (e.g., by congestion). Additionally, various factors influence the start of the parking search, including driver age, vehicle class, and familiarity with the destination. Specific conditions such as proximity to amenities, rush hour timing, and destination familiarity prompt earlier search initiation. The study also identifies scenarios where drivers skip the search process and park immediately, influenced by factors like driving home, short parking durations, and destination familiarity.

中文翻译：

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是什么促使司机开始巡航停车？模拟搜索过程的开始


本研究调查了停车搜索的起点，通过实证和理论方法提出了新的发现。它引入了一个概率模型，描述从正常驾驶到主动寻找停车位的转变，旨在最大限度地减少旅程成本。该模型使用通过智能手机应用程序收集的真实数据进行测试，该应用程序跟踪停车搜索的开始。结果验证了模型，表明当停车位稀缺且行驶速度降低（例如，由于拥堵）时，驾驶员更有可能更早开始寻找停车位。此外，各种因素都会影响停车搜索的开始，包括驾驶员年龄、车辆类别以及对目的地的熟悉程度。靠近便利设施、高峰时间和目的地熟悉程度等特定条件促使更早开始搜索。该研究还确定了驾驶员跳过搜索过程并立即停车的情况，这些情况受到开车回家、停车时间短和目的地熟悉程度等因素的影响。