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Winter Operations Decision Support Tools for the Iowa DOT Maintenance Bureau

Project Details
STATUS

Completed

PROJECT NUMBER

17-616, 17-SPR0-010

START DATE

06/01/17

END DATE

06/18/20

SPONSORS

Federal Highway Administration State Planning and Research Funding
Iowa Department of Transportation

Researchers
Principal Investigator
Neal Hawkins

Director Research Administration, ISU

Co-Principal Investigator
Jing Dong-O'Brien

Transportation Engineer, CTRE

Co-Principal Investigator
Zachary Hans

Director, CWIMS

Co-Principal Investigator
Skylar Knickerbocker

Research Engineer, CTRE

Student Researcher(s)
Bryce Hallmark

About the research

This research serves as a beginning point to explore new ways to support timely and accurate decision making during winter operations given the massive stream of data coming from the Iowa Department of Transportation (DOT) snowplow fleet. The Iowa DOT Maintenance Bureau manages roughly 900 snowplows, which are equipped and continuously transmitting important operational data every few seconds during winter operations. These data provide truck locations using automated vehicle location (AVL) pings and report operational status such as whether the plow is up or down and which materials, if any, are being applied to the roadway.

This research project created visual and tabular summaries of one day of winter operations data to provide practical information based on the interest and needs of both administrative and district maintenance staff. Future efforts can consider integrating these summaries and similar tools into daily operations.

This project includes the results of an attempt to conduct an analysis of snowplow blade performance using periodic measurements from specific trucks at the beginning of, and regularly throughout, two winter seasons. Unfortunately, the analysis was not possible given that snowplow operators are faced with too many demands and providing these driver-reported blade measurements was problematic, even with the significant efforts made and refined to secure the data over a second winter season. These efforts are described along with a framework that can be used for future efforts to complete this analysis.

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