Abstract Manager

Parsons and WSP are developing a mesoscopic dynamic traffic assignment (DTA) model for the Region of York. The model covers the entire Region and a 2-kilometer buffer beyond its geographic boundaries, capturing key transportation connections with adjacent jurisdictions. This DTA model is expected to be integrated with the Region’s existing Activity-Based Model (ABM) to achieve the final integrated ABM-DTA modelling platform. 

For over two decades, the Region has been using a 4-step model to assess the benefits/impact of plans and policies in addressing its ongoing and future transportation needs. While traditional 4-step models are effective for long-term planning at a regional scale and have favourable properties such as stability and computational traceability, the modelling framework suffers from several drawbacks. Specifically, the assignment algorithms in the models do not have the capability to perform dynamic assignments, which reduces the fidelity in network travel times and poses practical limitations for multimodal modelling of short- to medium-term applications.

The newer generation integrated models (i.e., ABM-DTA) for both travel demand forecasting and transportation network simulation overcome these challenges and lead to better and more reliable decisions about the transportation system. INRO’s Dynameq has been selected as the software platform for the mesoscopic DTA model. The initial DTA model development covers demands for the AM and PM peak periods for auto and transit trips based on a refined traffic analysis zone (TAZ) system. Challenges and lessons learned have been gathered in various aspects during the process of model development, such as how to develop a large-size road and transit network efficiently, how to simulate adaptive traffic signal control and transit signal priority (with noted limitations), how to integrate travel demands from the Region’s existing ABM (CTRAMP2), and how to utilize scripts and APIs to automate the data organization and model development processes to increase the work efficiency.