OpenPaths Case Study: DTA Revolutionizes Traffic Planning, Saves Millions

OpenPath by Bentley Systems is helping the Canadian government save millions of dollars on traffic management through the innovative Dynamic Traffic Assignment (DTA) Model, according to Bentley’s case study recently published.

The Regional Municipality of York is setting a new national standard for transportation planning and operations with its innovative Dynamic Traffic Assignment (DTA) Model. The project, officially titled “York Region DTA Model – A Next-Generation Transport Planning and Operations Tool,” has been recognized by ITE Canada and nominated for the prestigious 2025 ITE Transportation Achievement Award.

The DTA model is a cutting-edge mesoscopic simulation that provides a highly accurate and responsive analysis of traffic flow, surpassing the capabilities of traditional, static models. Covering a massive 1,762 square kilometers, the York Region DTA is the largest model of its kind in Canada. It was developed using Bentley’s OpenPaths DYNAMEQ software, which allowed the region to consolidate multiple conventional modeling processes into a single, efficient platform.

OpenPaths is a comprehensive transport modeling platform designed for strategic and operational transport planning. It incorporates both multimodal transport network modeling and modern travel demand forecasting capabilities to help users answer complex planning “what if?” questions, aiming for more efficient, resilient, and sustainable mobility.

It allows users to:

  1. Model: Build detailed representations of cities or regions based on key inputs like population, demand, and network data.
  2. Forecast: Predict and simulate the impacts of various changes, such as demographics, new infrastructure, and transport policy shifts.
  3. Analyze: Generate rich outputs based on user-defined metrics, including accessibility, efficiency, and equity.

Through OpenPaths, the DTA model helped the region make smarter infrastructure decisions, most notably by assisting in the avoidance of unnecessary road widenings, a measure that potentially saved millions of dollars in infrastructure costs.

Furthermore, the use of Python scripting and comprehensive APIs automated critical processes, reducing overall analysis time by a remarkable 60% compared to previous methods.

In terms of mobility, the model proved instrumental in optimizing traffic flow, supporting transit priority strategies, and assessing major projects like the Highway 7 Bus Rapid Transit (BRT) system.

Looking ahead, York Region plans to fully integrate the DTA model with its existing Activity-Based Model (ABM). This enhancement will allow for even more accurate simulations of individual travel behaviors.

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