At the start of the 2019 to 2020 snow season, vehicle-to-everything (V2X) systems using dedicated short-range communication (DSRC) were placed on Utah Department of Transportation snowplows and traffic signal controllers on selected state routes. This study was conducted to understand the overall impacts of snowplows using V2X DSRC to request signal preemption. Roadside units (RSUs) were deployed on five corridors throughout the Salt Lake metropolitan area. Similar routes without RSUs were selected as a control and were used in the analysis to quantify results. Each snowplow on these corridors was equipped with an onboard unit (OBU). Based on data collected, analysis was performed on both traffic signal performance and vehicle performance data. Within the traffic signal performance analysis, it was found that the V2X DSRC system was utilized often, with snowplows requesting preemption in more 50% of the occasions they approached a signalized intersection. Of those requests, signal controllers granted preemption in over 80% of cases. On average, signal controller coordination was affected for less than 5 min. The vehicle performance analysis found that the snowplows on equipped routes had travel speeds that were less affected when there was snow than on corresponding not-equipped routes. Vehicle crash data also showed that there was a greater decrease in crashes on equipped routes than not-equipped routes. Anecdotal evidence gathered from snowplow drivers indicated that snowplows stopped less when using signal preemption. Drivers also noted a benefit to overall snow removal operations on corridors equipped with the V2X DSRC system.


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    Title :

    Evaluating Signal Preemption Requests in Utah Using Vehicle-to-Everything Dedicated Short-Range Communication Equipped Snowplows


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2024-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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