The 1688 Michigan Department of Transportation’s (MDOT’s) Automated Vehicle Location (AVL) and Maintenance Decision Support System (MDSS) Program - designed and implemented by 285 Delcan Technologies, a 4089 Parsons company, in partnership with 73 Iteris - recently received the Best of ITS award from the Intelligent Transportation Society of America (560 ITS America). Honoured as the Best New Innovative Practice in the Sustainability in Transportation category, MDOT was recognised for the program’s leading-edge technology as well as its rapid deployment on a large scale.
“We are honoured to have assisted MDOT on this innovative project,” said Todd Wager, Parsons Group President. “Not only does the technology save time and money, it increases public safety by maximising snowplough efficiency and effectiveness, keeping ahead of treacherous snowstorms.”
The AVL technology displays live roadway maintenance operations, produces fleet activity reports, and exports data to the MDSS, which in turn delivers location-specific weather forecasts along snowplow routes and predicts how road conditions will change due to forecast weather. The system then recommends maintenance locations and treatments, application rates, and suggested times to apply road maintenance materials to maximize their effectiveness.
“We are honoured to have assisted MDOT on this innovative project,” said Todd Wager, Parsons Group President. “Not only does the technology save time and money, it increases public safety by maximising snowplough efficiency and effectiveness, keeping ahead of treacherous snowstorms.”
The AVL technology displays live roadway maintenance operations, produces fleet activity reports, and exports data to the MDSS, which in turn delivers location-specific weather forecasts along snowplow routes and predicts how road conditions will change due to forecast weather. The system then recommends maintenance locations and treatments, application rates, and suggested times to apply road maintenance materials to maximize their effectiveness.