Implementation of Lane Boundary Guidance System for Snowplow Operations
Principal Investigator(s):Max Donath, Professor, Mechanical Engineering
- Chen-Fu Liao, Former Researcher, Mechanical Engineering
- Nichole Morris, Director, Mechanical Engineering
Snowplow operators are often tasked with numerous monitoring and operational activities that they need to do simultaneously while removing snow and spreading deicing agents on the road. The University of Minnesota has developed a snowplow driver assist system that provides lane guidance and forward obstacle detection feedback to the driver. The lane guidance system uses a Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) receiver and high-accuracy maps of the roadway to provide information to the driver about their position within the lane. The forward obstacle detection system uses forward-facing radar to detect potential forward obstacles and alert the driver to their presence. Information is provided to the driver through a dash-mounted light bar which has a series of shapes that illuminate to provide information to the driver about their lane position and the presence of forward obstacles.
This project focused on a two-phase deployment of the system over two winter seasons. In the first phase, work was done to integrate and test the lane guidance and forward obstacle detection systems and to conduct user testing on the initial LED light bar design to ensure appropriate luminance and color perception under different ambient lighting conditions. The Phase 1 system was deployed on four snowplows across Minnesota for use during the 2020-2021 winter season. Driver feedback about the system's performance was collected through usability testing. In the second phase, the light bar was redesigned and deployed on nine plows to incorporate a new LCD panel based on feedback from the Phase 1 winter season. These improvements included redesigning the system display to increase flexibility and clarity and to further improve the performance of the forward obstacle detection system. The system was deployed on all nine plows during the 2021-2022 winter season and driver feedback was again collected through usability testing.
- Project number: 2020004
- Start date: 06/2019
- Project status: Active
- Research area: Transportation Safety and Traffic Flow
- Topics: Snow and ice control