Using Automatic Vehicle Location (AVL) for Real-Time Maintenance Identification and Tracking
Improving the communication of work zone data has been a main focal point of the Work Zone Data Exchange (WZDx) which provides a standard protocol to push agency data to third party users. However, the accuracy of the work zone locations and times are difficult for many agencies to collect and maintain. Many agencies are beginning to focus on improving this data through the use of connected temporary traffic control devices such as smart arrow boards. Maintenance operations are another area that must be improved because of the short duration and the dynamic nature of the work. Currently, most maintenance operations must notify a traffic management center (TMC) of their work but this may extend multiple miles of roadway they are working on that day and if the work is cut short or ends early the TMC is not always notified.
To improve this data, many agencies currently equip their vehicles with AVL systems to track their snowplows. The snowplows in most cases also the same vehicles used for maintenance operations such as painting, pothole repairs, etc. To minimize the work by the maintenance staff and improve the quality of work zone data, the AVL data points can be used to classify a vehicle in maintenance mode then cluster all of the surrounding vehicles to get the extents of the maintenance operation. As the vehicles move the data will be updated in real-time to accurately communicate the extents of the maintenance operation through the agencies WZDx or ATIS system. This project will develop an automated process that identifies maintenance activities and clusters AVL data to communicate actual maintenance operations in real-time through the WZDx.
Committee: Samik Basu (major professor), Anuj Sharma (major professor), Pavan Aduri, and Soumik Sarkar