Reporting Framework for Arterial-Level Traffic Signal Performance Measures Estimated from Connected Vehicle Trajectory Data

Traffic signal performance measures based on connected vehicle (CV) trajectory data can provide practitioners actionable information on the operational state of their systems. Agencies need visualization tools that can enable them to quickly assess arterial-level performance by time-of-day (TOD) to identify challenges and opportunities. This document presents a framework to report four signal performance measures over a corridor for all relevant movements, including traditional Highway Capacity Manual (HCM) level of service (LOS), arrivals on green (AOG), split failures (SF), and downstream blockage (DSB). The reporting framework can provide up to 3,072 performance data points per intersection since it provides information for eight different movements and four performance measures for every 15-minute period over 24 hours. To demonstrate implementation, 14 reports displaying performance estimations for 12 corridors, located in 11 different states, are presented. This reporting approach can facilitate the determination of possible mitigation strategies by contrasting operational conditions between movements by TOD

Crowdsourcing/Winter Operations Dashboard Upgrade

INDOT has recently completed the deployment of Parsons telematics-based dash-cameras, automatic vehicle locator (AVL) positions, and spreader rate monitoring across their winter operations fleet. The motivation of this study was to develop dashboards that integrate connected vehicle data into the real-time monitoring and after-action review of winter storms. Each month approximately 13 billion connected vehicle records are ingested for the state of Indiana and almost 99 billion weather data records are ingested nationwide in 15-minute intervals. This study developed techniques to utilize this connected vehicle data and weather data to monitor real-time mobility of interstates and post storm after-action assessments to identify improvement opportunities of winter operations activities. In multiple instances, these agile reviews have influenced operational changes in snow removal and maintenance around the state, leading to a marked improvement in observed mobility and safety

Salt Monitoring and Reporting Technology (SMART) for Salt Stockpile Inventory Reporting

Transportation agencies in northern environments spend a considerable amount of their budget on salt for winter operations. For example, in the state of Indiana, there are approximately 120 salt storage facilities distributed throughout the state and the state expends between 30 M USD and 60 M USD on inventory and delivery each year. Historical techniques of relying on visual estimates of salt stockpiles can be inaccurate and unhelpful for managing the supply chain during the winter or planning for re-supply during the summer months. This project report describes the implementation of a portable and permanent LiDAR system that can be used to inventory indoor stockpiles of salt in under 15 min and describes how this system has been deployed over 300 times at over 120 facilities. A quick and easy accuracy test, based on the conservation of volume, was used to provide an independent check on the system performance by repositioning portions of the salt pile. Those tests indicated stockpile volumes can be estimated with an accuracy of 1%–3% of indicated stockpile volumes. The report concludes by discussing how this technology can be permanently installed for systematic monitoring throughout the year

<b>TECHNIQUES FOR REDUCING TRAFFIC MANAGEMENT CENTER CAMERA POSITIONING LATENCY FOR ACCELERATED INCIDENT RESPONSE</b>

Traffic Incident Management (TIM) is an important tool for agencies to reduce secondary crashes, improve travel reliability, and ensure safety of first responders. Having “eyes” on the scene from roadside traffic cameras can assist operators to dispatch appropriate personnel, provide situational awareness, and allow for quick response when incident conditions change. Many intelligent traffic systems (ITS) centers deploy pan-tilt-zoom (PTZ) cameras that provide broad coverage but require operators to position. When incidents occur or a public safety vehicle stops for roadside assistance, Traffic Management Center (TMC) operators need to reposition cameras to monitor the event. The camera positioning time depends on operator experience, accuracy of 911 call, location, public safety radio reports, and in some cases, GPS positions. This research outlines the methodology to use GPS data sources to automate camera position to a scene for event nature verification. In general, this GPS information can come from either connected vehicles or public safety vehicles, such as Indiana Department of Transportation (INDOT) Hoosier Helpers. Implementing this research into INDOT daily operations has increased the number of events that cameras verify, while decreasing the time from event occurrence to camera verification from a median of 5 minutes to a median of approximately 90 seconds. The time is driven by the accuracy and frequency of GPS data from devices. With increased telematics polling rates and availability of enhanced vehicle data such as door open/close and seatbelt latch events, this latency is expected to further decline. </p

Trajectory-Based Arterial Traffic Signal Performance Measures Reports

Traffic signal performance measures based on connected vehicle (CV) trajectory data can provide practitioners actionable information on the operational state of their systems. A visualization framework that can enable agencies to quickly assess arterial-level performance by time-of-day (TOD) to identify challenges and opportunities has been recently developed. The framework provides information on four relevant signal performance measures over a corridor, including traditional Highway Capacity Manual (HCM) level of service (LOS), arrivals on green (AOG), split failures (SF), and downstream blockage (DSB). This document uses the proposed framework to provide 58 arterial-level performance reports analyzing 571 unique signalized intersections on 42 corridors in 14 different states. Results are estimated from over 18,000,000 vehicle trajectories and 328,000,000 GPS points. Since the reporting approach can provide up to 3,072 performance data points per intersection, this manuscript provides almost 2 million measures for all the analyzed locations

Development of Latitude/Longitude (and Route/Milepost) Model for Positioning Traffic Management Cameras

Traffic Incident Management (TIM) is a FHWA Every Day Counts initiative with the objective of reducing secondary crashes, improving travel reliability, and ensuring the safety of responders. Agency roadside cameras play a critical role in TIM by helping dispatchers quickly identify the precise location of incidents when receiving reports from motorists with varying levels of spatial accuracy. Reconciling position reports that are often mile-marker based with cameras that operate in a Pan-Tilt-Zoom (PTZ) coordinate system relies on dispatchers having detailed knowledge of hundreds of cameras and perhaps some presets. During real-time incident dispatching, reducing the time it takes to identify the most relevant cameras and view the incident improves incident management dispatch times. This research developed a camera-to-mile marker mapping technique that automatically sets the camera view to a specified mile marker within the field-of-view of the camera. A new performance metric on verification time (TEYE) that captures the time it takes for TMC operators to have the first visual on roadside cameras is proposed for integration into the FHWA TIM event sequence. Performance metrics that summarize spatial camera coverage and image quality for use in both dispatch and long-term statewide planning for camera deployments were also developed. Using mobile mapping and LiDAR geospatial data to automate the mapping of mile markers to camera PTZ settings, and the integration of connected vehicle trajectory data to detect incidents and set the nearest camera view on the incident are both discussed for future studies