Summary
Investigating how technology systems can support our transportation system and its users presents a significant opportunity to improve operational safety, mobility, and productivity of road users. The HFSL has developed and deployed in-vehicle, roadside, and centralized technologies integrating technologies such as GNSS/GPS, LIDAR, RADAR, cellular communications, embedded computing, telemetry, and cloud services.
In addition to developing the enabling technology itself, significant attention is given to the holistic design of the system, including the interface between the technology and the humans who interact with it. This includes designing and fine-tuning visual, audio, and haptic feedback devices and workflows for operating the system to perform a particular task.
Most recently, HFSL has partnered with the Minnesota Department of Transportation to deploy the snowplow driver assist system, an in-vehicle system to support snowplow operators working in low visibility conditions. It is currently deployed in nine plows across the state representing all eight MnDOT districts as well as Dakota County.
Current and Past Projects
Selected Publications
Jeon, W., Xie, Z., Craig, C., Achtemeier, J., Alexander, L., Morris, N., Donath, M., & Rajamani, R. (2021). A Smart Bicycle That Protects Itself: Active Sensing and Estimation for Car-Bicycle Collision Prevention. IEEE Control Systems Magazine, 41(3), 28-57.
Craig, C. M., Morris, N. L., Achtemeier, J. D., & Schwieters, K. R. (2021). Auditory alerts and safety with simulated bicycles and motor vehicles. Transportation Research Record, 2675(9), 408-416.
Achtemeier, J.D., Craig, C.M., Morris, N.L., & Davis, B. (2020). Superior Side Sound Localization Performance in a Full-Chassis Driving Simulator. Ergonomics, 63, 538-547.
Davis, B., Achtemeier, J., Morris, N. L., & Patzer, B. (2019). In-Vehicle Dynamic Curve Speed Warnings (No. 19-01323). Transportation Research Board 98th Annual Meeting. Washington DC, USA.
Katariya, V., Baharani, M., Morris, N., Shoghli, O., & Tabkhi, H. (2022). Deeptrack: Lightweight deep learning for vehicle trajectory prediction in highways. IEEE Transactions on Intelligent Transportation Systems, 23(10), 18927-18936.