Applying artificial intelligence to improve the resilience, fluidity and safety of road freight transport in the Canadian Prairie and Northern Region

 

Canada's vast Prairie Region relies on roads that must be kept fluid, resilient and safe for freight transport. The network is sparse and subject to seasonal changes, making it prone to risks and hazards that can disrupt the supply chain.

With the University of Manitoba Department of Civil Engineering, the NRC is developing a leading-edge truck traffic and road-weather monitoring facility. Researchers will use artificial intelligence (AI) to model risks and their impacts on the network, and to propose response scenarios when these risks are encountered.

The project supports the planning, operation and management of the road freight transport network in Canada's Prairies and North, to help sustain and grow the industry sectors that drive this region's economy.

Collaborators

Objectives

  • Gather new data about traffic operations and road-weather conditions on regional trucking routes
  • Analyze data relating to road-weather conditions, incidents involving hazardous materials, and human behaviour in response to these factors
  • Evaluate the impact of disruptions due to risks and hazards on the performance of the road freight transport network

Deliverables

  • Monitoring facility for trucking transportation: new, portable roadside data-capture and analysis equipment
  • Response scenarios and other tools to mitigate the impact of risks and disruptions
  • National datasets for freight trucking R&D

Activities

Logistics and transportation activities are impacted by factors relating to infrastructure (capacity, deterioration), human activities (traffic, accidents) and environment (temperature, precipitation).

The University of Manitoba Department of Civil Engineering, in collaboration with International Road Dynamics and Manitoba Infrastructure, will develop new, roadside data-capture equipment and deploy it on remote and northern roads in Manitoba. This mobile equipment will enable the team to collect data at points previously out of reach.

NRC and University of Manitoba researchers will then use AI methods to analyse data about truck traffic, weather and road conditions. They aim to better understand 4 types of risks and their impact on network resilience, fluidity and safety:

  • Warming winters and their impacts on truck regulations and productivity
  • Flooding, particularly when it induces road closures
  • Hazardous-materials incidents and their impact on the travelling public
  • Adverse road-weather conditions related to truck operations

Researchers will build data-driven models that uncover various factor relationships in scenarios of interest, benefit from historical data, and generate complex scenarios. These models and simulation tools can be updated when new data is added. They will also propose response scenarios to mitigate the impact of risks and disruptions. The project will provide governments with the data they need to make informed decisions in the planning, operation and management of the network.

Project team

Contact us

Margaret McKay, Program Leader, AI for Logistics Supercluster Support program
Telephone: 613-991-6853
Email: NRC.AIforLogistics.Program-Programme.IALogistique.CNRC@nrc-cnrc.gc.ca

Jonathan Regehr
Associate Professor, University of Manitoba Department of Civil Engineering
Email: Jonathan.Regehr@umanitoba.ca

Rish Malhotra
President and CEO, International Road Dynamics
Email: Rish.Malhotra@irdinc.com

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