Case Study: Lower Don Lands Master Plan Environmental Assessment

Problem: The ‘Lower Don Lands’ is a large area of brownfields located on the waterfront area in the City of Toronto. It will be the next area of the waterfront to be revitalized. Although its revitalization will pose complex technical challenges, it has exceptional potential to create an exciting and beautiful new waterfront district with a unique identity. Continue reading

Case Study – AERIS Connected Vehicle Application Modeling

Problem: The objective of the AERIS research program is to generate and acquire environmentally-relevant real-time transportation data, and use these data to create actionable information that support and facilitate “green” transportation choices by transportation system users and operators. Our team chose Paramics microsimulation capabilities to support the modeling phase of the project. Continue reading

Case Study – Microsimulation and Conflict Analysis of Thorold Stone Plaza Access – Niagara Falls

Problem: The Niagara Region’s Public Works Department has been requested to assess the access and egress to/from Thorold Stone Plaza due to the increase in traffic volume accessing the plaza. This increase in traffic volumes results in queue spill back into the plaza area and creates a considerable conflict between Thorold Stone through traffic and the Left Turn traffic leaving the plaza. One of the challenges is the proximity of the Plaza Entrance to a major intersection (Thorold Road and Portage Road). Continue reading

Case Study: Development of a New Self-Learning Adaptive Traffic Signal Control System using Paramics

Problem: Population is steadily increasing worldwide resulting in intractable traffic congestion in urban dense areas. Adaptive Traffic Signal Control (ATSC) has shown strong potential to effectively alleviate urban traffic congestion by adjusting the signal timing plans in real-time in response to traffic fluctuations to achieve desirable objectives (e.g. minimize delay).

The main objective of this project is to design efficient and robust ATSC using a multi-agent reinforcement learning (MARL) approach in which each controller (agent) is responsible for the control of traffic lights around a single traffic junction. Continue reading

Case Study: Development of Comprehensive Traffic Microsimulation Models for the Toronto Queens Quay Corridor

Problem: The Waterfront Development Corporation oversees the redevelopment of Toronto’s waterfront as a mixed-use, pedestrian-oriented area. The first phase of this project concerned the assessment of the operational performance of Toronto’s Waterfront bounded by Queens Quay corridor (south), Front St (north), Don Valley Parkway (east), and Bahtrust St (west). Continue reading

Case Study: Development of TMC Simulator for Operator Training

Objective: Duplicate the standardized California TMC systems in an  off-line environment where TMC operators can be trained to enhance their skills.

The purpose of the project is to develop an off-line Traffic Management Center (TMC) simulation environment in which TMC operators can be trained to enhance their skills  using various pre-defined incident scenarios.

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Case Study: Stirling Regional Centre

Project: Stirling Regional Centre

Objective: Creation of a calibrated base network for the Stirling regional centre.

This is the beginning of more major transport modelling work to be undertaken in this area. At this stage a calibrated base case has been prepared that consists of 56 traffic zones  and more than 30 sets of signals. Continue reading

Case Study: Micro-Simulation Modeling and Calibration of the 400-Series Freeways in the Greater Toronto Area

Problem:

The Greater Toronto Area (GTA) is constantly growing resulting in mobility and safety concerns along congested urban corridors with estimated $6 Billion cost of congestion. To assess the existing conditions performance a large-scale regional Paramics microscopic traffic simulation model was developed and calibrated for the Greater Toronto Area (GTA). Continue reading