Virginia DOT (VDOT) Uses Probe-Vehicle-Based Performance Measures from Different Sources to Measure Work Zone Related Delay and Queuing at the State, District, Corridor, and Project Levels.
Virginia, United States
Utilizing Probe-Vehicle Data for Work Zone Mobility Performance Measurement
Summary Information
Work zone mobility is a key focus area for VDOT’s performance measurement program. VDOT used probe-based performance measures to estimate related delays at State, district, corridor, and project levels. Probe vehicle data from different sources are used to identify macro-level (e.g., corridor-specific) and micro-level (e.g., project-specific) contributions to delay, as well as their underlying issues and root causes, and areas of opportunity for improvement. By measuring work zone mobility performance, VDOT is not only able to report performance on an annual basis but also analyze trends and patterns over time. Furthermore, by segmenting and aggregating performance measures at the individual-project level and the macro-levels, VDOT gains a comprehensive bottom-up and top-down view of work zone performance. VDOT’s work zone and traffic control practitioners use the intelligence gained from these efforts to improve project-level work zone management practices and broader agency, district, and corridor-level work zone policies and procedures.
VDOT uses commercial probe vehicle speed and travel time data at three different levels of granularity (with segment lengths of 0.16, 0.42, and 1.16 miles) as the key data for quantifying work zone mobility performance. Additional data, such as traffic volume counts, Bluetooth and WiFi travel time data, incident, work zone activity, road condition and weather data from Traffic Operation Centers, and vehicle hours of delay data from the Regional Integrated Transportation Information System are also used. These data provide additional contextual data to help understand the dynamics and causal relationships of work zone performance.
- A programmatic macro and micro analysis of work zone performance is useful to provide estimates of work zone impacts at the statewide, district, corridor, and individual project levels. Macro analysis benefits work zone coordination across stakeholders and helps State DOTs to identify and prioritize areas for mitigation, and to analyze trends and patterns towards ultimately improving work zone management policies and practices. The micro analysis identifies mitigation strategies needed for specific projects and enables the innovations needed for State DOTs and other agencies to better understand and manage the mobility performance of road projects.
- Probe vehicle data, with relatively low-cost and superior spatial coverage, provides a significant opportunity to measure both high-level as well as in-depth work zone performance. Granular (e.g., < 0.5-mile segments) probe-vehicle data can accurately analyze project-level delays and queues. However, lower granularity data (e.g., 1.16-mile segments) can still be useful in getting a broad estimate of delay induced by individual work zones. High granularity probe vehicle data (e.g., < 0.16-mile segments) can be reliably used for work zone performance measurement and real-time work zone management. This can potentially eliminate the need for conventional sensors and hardware, and lead to significant cost savings for the DOT.
- Accurate and reliable work zone performance measurement and monitoring requires fusing different data sources. All data sources should be cleaned and consistently formatted into a desired format, and appropriate fusion techniques need to be used to extract meaningful information. Creative data visualization techniques can also be useful in providing a visual understanding of the diverse datasets.
- Standardized work zone activity data and documentation practices are needed. Developing standard work zone activity data definitions, formats and processes will help to set the foundation for effective work zone impacts and performance management. Developing standard documentation procedures will increase the consistency and accuracy of manually entered work zone activity data.
