Probabilistic time geography (PTG) can be used to measure the probability of random encounters between two moving objects. Available PTG methods are based on homogeneous space, while the network space is typically heterogeneous, which constrains individuals to the network. Therefore, the PTG of the network must consider the geographic network. Based on this, we put forward a method for calculating the encounter probability of objects that are moving in a network by considering network constraints on movement. These constraints not only restrict the space‐time accessibility of the moving objects, but also affect the probability of them visiting locations or encountering other objects in space and time. Therefore, in network space, our method improves measures of the likelihood of encounters between moving objects, thereby enabling more accurate predictions of encounter events and their probabilities. Finally, the performance of the method is experimentally evaluated. In the experiment, campus road network data and simulated trip data are used to calculate the encounter probabilities of two moving objects and to determine when and where two moving objects meet with the highest probability.

中文翻译：

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网络空间中遭遇概率的计算方法

概率时间地理（PTG）可用于测量两个移动物体之间随机相遇的概率。可用的PTG方法基于同构空间，而网络空间通常是异构的，这将个人限制在网络中。因此，网络的PTG必须考虑地理网络。基于此，我们提出了一种通过考虑网络对运动的约束来计算网络中正在运动的物体的相遇概率的方法。这些限制不仅限制了运动对象的时空可访问性，而且还影响了它们在空间和时间上访问位置或遇到其他对象的可能性。因此，在网络空间中，我们的方法改进了移动物体之间相遇的可能性的度量，从而可以更准确地预测遭遇事件及其概率。最后，通过实验评估了该方法的性能。在实验中，校园道路网络数据和模拟行进数据用于计算两个运动物体的遭遇概率，并确定何时和何处两个运动物体以最高概率相遇。