On Capturing Region-specific Effects of Traffic-state-dependent Trip Distances in Multi-region Bathtub Models

Abstract

Multi-region bathtub models are widely applied to urban networks with unevenly distributed congestion. They require explicit modeling of regional path choice and flow exchanges. Regional paths are commonly defined as sets of routes that share the same sequence of traversed regions, and their distances can vary depending on traffic conditions. However, existing studies lack a systematic way to capture how regional traffic states affect path distances. This paper extends the multi-region bathtub model by incorporating dynamic path distance approximations for paths in each region. The extended model is evaluated on a partitioned road network of the city of Delft, the Netherlands. Bathtub model simulations with different path distance assumptions are benchmarked against a macroscopic traffic simulation. Results indicate that dynamic path distance approximation improves the accuracy of regional accumulation and speed in regions with large variations in path distance. In regions with limited path distance variation, static distances remain sufficient.