Tichakorn (Nok) Wongpiromsarn
About the research
The need and practical implications of this project are extreme. The U.S. Federal Highway Administration’s Road Weather Management Program reports that around 70% of US roadways lie in regions with five or more inches of snowfall annually, and around the same percentage of the US population lives in these regions. Inclement weather can levy a high cost on both transportation agencies and road users. The road user cost is incurred due to induced delay and an increased number of crashes.
Despite the amount of money spent on road clearance, technological constraints hinder the maintenance during severe storm conditions due to a reduction in visibility. In severe winter storms, sometimes visibility degrades to the point that it is no longer safe to continue plowing and crews are called back to the garage or other safe place until the storm subsides. When this occurs, there is no longer any plows keeping drifts back so roads can quickly cover, and in some cases, drift shut. This severely limits traffic and emergency services from using the road until plows can return. Also, once roads are covered and deep, it sometimes takes a considerable effort, special equipment, and longer than normal time to clear them out again.
In Phase 1 of this project, the research team will develop and retrofit an existing snowplow with a suite of sensors and mapping systems and a decision assist interface to guide the operator when visibility is too low for regular operation. In addition, to provide route guidance, the system will also provide alerts for unexpected obstacles such as stalled/slow-moving vehicles, people, or debris. The system designed in Phase 1 will not take over any control and only guide the operator. In addition, for Phase 1, only uninterrupted flow facilities will be evaluated, implying the system will not assist the driver in maneuvering merging and traffic control such as stop signs, signalized intersection, etc. In future phases, the system can be extended to address these limitations.
The guiding principle of this project will be economic efficiency and field readiness of the solution. The researchers will explicitly consider the trade-off between economics and the solution’s accuracy.