This paper develops a new route choice modelling framework that deals with both route correlations and unrealistic routes in a consistent and robust way. To do this, we explore the integration of a correlation-based Path Size Logit model with the Bounded Choice Model (BCM) (Watling et al. 2018. “Stochastic User Equilibrium with a Bounded Choice Model.” Transportation Research Part B: Methodological 114: 254–280). We find, however, that the natural integration of these models leads to behavioural inconsistencies and/or undesirable mathematical properties. Solving these challenges, we derive a mathematically well-defined Bounded Path Size (BPS) model form that utilises a consistent criterion for assigning zero choice probabilities to unrealistic routes while eliminating their path size contributions. A closed-form and fixed-point BPS model are consequently formulated. Subsequently, we consider parameter estimation in a simulation study and on a real-life large-scale network using GPS data, where computational feasibility is demonstrated. Estimation results show the potential of the BPS models to give improved fit relative to non-bounded versions (and BCM).

本文开发了一种新的路线选择建模框架，以一致且稳健的方式处理路线相关性和不切实际的路线。为此，我们探索了基于相关性的路径大小 Logit 模型与有界选择模型 (BCM) 的集成（Watling 等人，2018 年。“具有有界选择模型的随机用户平衡”。交通研究 B 部分：方法论114：254–280）。然而，我们发现这些模型的自然整合会导致行为不一致和/或不受欢迎的数学特性。为了解决这些挑战，我们推导出了一个数学上定义明确的有界路径大小 (BPS) 模型形式，该模型利用一致的标准将零选择概率分配给不切实际的路线，同时消除它们的路径大小贡献。因此制定了一个封闭形式的定点 BPS 模型。随后，我们在模拟研究和使用 GPS 数据的真实大规模网络中考虑参数估计，其中证明了计算可行性。估计结果显示了 BPS 模型相对于无界版本（和 BCM）提供改进拟合的潜力。