The FDW provides storage and access to large freight datasets necessary for the execution of CLUE research projects. The data enables novel data science applications, including applications in Theme 1 on freight flows, bottlenecks, safety and fuel efficiency, and pandemic supply chain performance and several projects in Themes 2, 3 and 4. Two surveys (and many more) are being conducted to enable analysis of freight demand and other applications.
The volume of e-commerce shopping continues to increase but details of the demand and the congestion, environmental and economic impacts of single-package delivery are not understood. Projects in this theme develop data resources and analyses to assess trends in delivery demand resulting from e-commerce, their social, environmental and economic impacts and methods for the reduction of these impacts.
Increased road congestion, lack of suitable parking, inadequate loading facilities noise and vehicle restriction by-laws pose delivery operations challenges in last-mile logistics in the GTHA and increase vehicle emissions. A set of pilot studies demonstrate feasibility and assess efficacy of city logistics solutions, including a large-scale, off-peak delivery program, a cargo tricycle pilot, an autonomous vehicle delivery pilot, and an assessment of technology-enhanced curbside loading zones. These projects serve as demonstrations that could enable scale-up across the GTHA and Canada.
The number of freight deliveries continues to grow, increasing the interactions between trucks and vulnerable road users, emissions, congestion and the burden on drivers. These projects use analysis, simulation and optimization to understand driver behaviour, develop solutions to mitigate unsafe behaviour, and to identify opportunities to improve parking supply and optimize traffic signalization. It also studies equity, diversity and inclusion in the logistics labour force dynamics and demographics.