Investigating the impacts of connected vehicle technology on the flow of trucks at the busiest Canada-U.S. border crossings
• Truck traffic at international land border crossings is not well studied. • The Canada-U.S. land border crossing is one of the busiest in the world. • Vehicle-to-vehicle and Vehicle-to-infrastructure scenarios are simulated. • A DTA model is used to simulate the movement of trucks from Canada to the U.S. • V2V and V2I will improve the performance of truck traffic flows at the border. Land-border crossings between Canada and the United States facilitate the movement of approximately 59 % of the goods traded between the two countries. Consequently, these border facilities experience heavy truck traffic daily. While connected vehicle technology have attracted attention in recent years, there has been no attempts to assess its impacts on truck traffic performance at international land borders. This paper addresses the issue by developing and applying a microscopic traffic simulation model for connected trucks. Scenarios depicting the movement of trucks between Canada and the U.S. through the two busiest border crossings (i.e., Windsor and Sarnia), are simulated in the presence of V2V and V2I technologies with the help of a dynamic traffic assignment. The simulation results suggest that truck traffic becomes more streamlined with up to 7 % of all trucks switching to the Sarnia crossing under a 100 % V2V scenario when a delay incident is present on the corridor leading to Windsor. Also, average time delay at the Windsor crossing under extended delay conditions spanning over a course of 8 h at this crossing is reduced by 30 % (i.e., delay dropped from 5 h to 3.5 h) when V2I technology is utilized.
Authors
- Sidra Anis
- Hanna Maoh (ORCID: https://orcid.org/0000-0002-6699-4568)
Institutions
- University of Windsor (CA)
Publication Details
- Journal
- Transportation Research Interdisciplinary Perspectives
- Published
- 2024-12-21
- DOI
- https://doi.org/10.1016/j.trip.2024.101310
- Citations
- 3
- Primary Topic
- Transportation Planning and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 2.05
Funders
- Natural Sciences and Engineering Research Council of Canada