Re-identification is the process of capturing unique identification about a vehicle and using this information to repeatedly identify that vehicle again at other times and/or locations. For example, a network of license plate readers can capture unique vehicle license numbers and use this information to identify specific vehicles at different times and locations. Based on the technology used to collect identifying information, vehicle re-identification data can inform origin-destination studies, route assignment algorithms, and travel time and speed analysis. Tracking commercial vehicle movement is especially valuable for understanding the interactions between the truck traffic and other road users and to identify the direct and indirect impacts of trucks traveling in urban areas.
Re-identifying vehicles are often complimentary with vehicle detection and classification approaches. Vehicle re-identification processes include matching the information captured from multiple data collection sites that use different vehicle detection/classification methods (see location and classification measures). After capturing and storing the unique characteristics of vehicles, such as license plate, GPS ID, media access control (MAC) address, etc., these stored characteristics can be used to re-identify the vehicles from other sets of captured information.
The following provides a list of data collection methods that inform vehicle re-identification technologies. Each of the items on this list will lead you to a brief discussion on the analytical methods used to obtain meaningful information from the data sources.
Global Navigation Satellite System (GNSS)
Wireless Address Matching (WAM)
Inductive Loop Detectors