Dashboards for Real-time Monitoring of Winter Operations Activities and After-action Assessment

Abstract

The Indiana Department of Transportation (INDOT) operates a fleet of nearly 1100 snowplows and spends up to $60M annually on snow removal and de-icing as part of their winter operation maintenance activities. Systematically allocating resources and optimizing material application rates can potentially save revenue that can be reallocated for other roadway maintenance operations. Modern snowplows are beginning to be equipped with a variety of Mobile Road Weather Information Sensors (MARWIS) which can provide a host of analytical data characterizing on-the-ground conditions during periods of wintry precipitation. Traffic speeds fused with road conditions and precipitation data from weather stations provide a uniquely detailed look at the progression of a winter event and the performance of the fleet. This research uses a combination of traffic speeds, MARWIS and North American Land Data Assimilation System (NLDAS) data to develop real-time dashboards characterizing the impact of precipitation and pavement surface temperature on mobility. Twenty heavy snow events were identified for the state of Indiana from November 2018 through April 2019. Two particular instances, that impacted 182 miles and 231 miles of interstate at their peaks occurred in January and March, respectively, and were used as a case study for this paper. The dashboards proposed in this paper may prove to be particularly useful for agencies in tracking fleet activity through a winter storm, helping in resource allocation and scheduling and forecasting resource needs.

Methodology for Automatically Setting Camera View to Mile Marker for Traffic Incident Management

“…This data is used for a variety of real time and after-action analysis [26] [27] [28]. Integrating this CV data with freeway cameras helps provide real time assessment of traffic flow, weather conditions, and work zone impacts [26] [29] [30] [31] [32]. When CV data is closely integrated with freeway cameras, it can provide tremendous insight into impacts on freeway flow and help identify opportunities to facilitate improvements in incident management [1] [15] [33].…”

Measuring Roadway Lane Widths Using Connected Vehicle Sensor Data

“…The spatiotemporal heatmap in Figure 4 shows vehicle speeds at this location by linear referenced 0.1 mile segments. The heatmaps have been extensively used in past research to visualize congested conditions [ 13 , 14 , 15 , 16 ]. The horizontal axis on the speed profile heatmaps represents the time of day while the vertical axis represents mile marker location.…”