An Arterial Incident Detection Procedure Utilizing Real-Time Vehicle Reidentification Travel Time Data

摘要

Our road and highway system has become a source of multiple types of big data. One such type of data is travel time data obtained from vehicle reidentification systems, a type that is increasingly available due to the implementation of existing and relatively new technologies such as license-plate recognition and Bluetooth-based wireless vehicle identification. Travel time data obtained in real time from such systems are used to update estimated travel times displayed on variable message signs, and research has also been conducted that utilizes travel time data as inputs to incident detection algorithms. Implementation of such systems and prior research has primarily focused on freeways and other free-flowing roads. However, such systems for travel time data collection are also being implemented on arterials. In this research an incident detection procedure that utilizes point-to-point travel time data obtained from an arterial vehicle reidentification system is developed and evaluated. Historical travel time data provided by a Bluetooth-based travel time data collection system and reported incident data are utilized to evaluate the procedure. The results show that the procedure provides a good balance of detection and false alarm rates.