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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Development of a Salt Spreader Controller Program Using Machine-Sensed Roadway Weather Parameters and Climate Data</title>
      <link>https://rip.trb.org/View/2543223</link>
      <description><![CDATA[The Massachusetts Department of Transportation (MassDOT) has recently completed a research project on leveraging the instrumented mobile road weather information system (RWIS), computer vision, and a new salt application model. The research was aimed at developing four critical aspects of the intelligent salt application system, including hardware (i.e., data collection I/O and power supplies system), software (i.e., data logging, synchronization, and data fusion), algorithm (i.e., road surface classification (RSC) algorithm), and model (i.e., the salt rate prediction (SRP) model) so that an optimized salt application decision can be provided to the actuator to treat the road surfaces. Through this study, a complete hardware/software system with automated RSC and SRP algorithms has been developed, pilot-tested, and validated with promising performance. The performance of the developed system showed good results. Once implemented in a more extensive fleet of MassDOT’s material spreaders utilized during winter operations, it could save a significant amount of salt. The goal of this research is to leverage the prototype system from the previous study and to implement 1) a fully validated spreader controller system that is operated in a fleet of MassDOT’s snowplowing trucks and 2) an intelligent salt treatment program that will include weather forecasting information to better prepare for challenging situations, such as freezing rain, black ice, etc.]]></description>
      <pubDate>Wed, 23 Apr 2025 16:15:33 GMT</pubDate>
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