Merging transit schedule information with a planning network to perform dynamic multimodal assignment: lessons from a case study of the Greater Toronto and Hamilton Area

Traffic assignment has traditionally been performed using aggregate static user equilibrium approaches for a single mode. These approaches are typically favoured over more complex dynamic multimodal micro and meso-simulated models. Investigations into dynamic multimodal assignment models have shown promise, prompting interest in the adoption of complex modelling structures. The development and operation of these complex models can still be problematic, highlighting the need for efficient approaches to allow practitioners to acquire and apply these models. This paper presents a method to modify existing static auto assignment networks for dynamic multimodal assignment. To complement this, a method, which improves the overall performance of the transit routing procedure used within many assignment models, is presented. These methods were tested using data from the Greater Toronto and Hamilton Area, and result in an assignment procedure with reasonable run time and results, suggesting potential for wide spread adoption of these approaches.

The Analysis of Transit Assignment with Variable Transit Price Based on Time Schedule

In this paper, we propose a method of peak period pricing to alleviate peak period crowding on the transit vehicles and the platforms. We expanded the route network into a time-expanded network based on the transit schedule, so the dynamic transit assignment is transferred into static transit assignment. Congestion coefficient is used to express the crowd in transit vehicles. In order to reach the goal of both government and the travelers, we establish a bi-level programming model.