Two teams of UWindsor engineering students have triumphed in an industry-led, pitch-off competition for their solutions to cross-border congestion at the future Gordie Howe International Bridge.
The teams impressed a panel of industry judges with their suggestions to implement mobile apps to reduce delays at the border and to facilitate the use of alternate modes of transportation to relieve congestion. The students also recommended using machine learning technologies, sensor-based systems, and even a suicide prevention system in plans for the new bridge, which is one of the largest infrastructure projects underway in North America.
The pitch-off competition hosted by Ontario’s Autonomous Vehicle Innovation Network (AVIN) and Windsor-Detroit Bridge Authority (WDBA) challenged post-secondary students in engineering, information technology, and business administration to utilize smart mobility technologies, data analytics, and new payment and security technologies to reduce cross-border congestion and wait times.
“Ontario is home to leading post-secondary institutions and top talent, and the pitches put forward by the students at the University of Windsor are a testament to that,” says Mona Eghanian, AVIN’s director of strategy and programs – automotive and mobility, which is under the Ontario Centre of Innovation umbrella.
PhD candidates in civil engineering Dhwani Shah, Umair Durrani, and Haesung Ahn took first place for their three-tier plan that includes:
- an online portal and mobile application that reduces inspection and payment time;
- a state-of-the-art machine learning technology for traffic prediction and management; and
- smart mobility options such as bikes, e-scooters, car-pooling, and shuttles.
“Our data analysis showed that inspection and payment time were the main reasons for border delays,” Shah says. “So we proposed real-time speed and wait time updates through the mobile application. Our solutions make crossing the border easy, accessible, sustainable, and environment-friendly while also relieving congestion.”
Third place went to Nikunj Vadsak and Vivek Siwach, both Master of Engineering students in the electrical stream. The duo came up with a smart toll collection system that doesn’t require human intervention thanks to a lidar sensor-based vehicle detection system, smart weigh-in-motion system, and advance toll collection portal. To amplify smart mobility infrastructure, the team made several recommendations such as a weather alert system, smart traffic signal, air quality monitoring and controlling system, and solar rooftops.
“Apart from this, our research led us to discover the current bridge has 20 recorded suicides, so we suggested incorporating a suicide prevention system to avoid similar tragic incidents in the future,” Vadsak says. “The lidar sensor-based human activity monitoring system helps analyse suspicious activities such as someone climbing over the fence or people fighting.”
Students had four days to submit their proposed solution followed by a presentation to a panel of industry judges. The first-place team received $1,200 and the opportunity to be mentored by an industry leader.
Eghanian says the panel was “truly impressed with the robust, creative, and well thought-out solutions put forward, demonstrating the incredible potential of applying academic knowledge to real-world business challenges.”