Corridor Deployment and Investigation of Anonymous Vehicle Tracking for Real-Time Traffic Performance Measurement

This report presents the results of a multi-year research effort on the development of a real-time section-based traffic performance measurement system using inductive vehicle signatures obtained from single conventional loop sensors along a six-mile freeway corridor in the City of Irvine, California and a separate effort to investigate the potential of a new type of inductive sensor called the Blade™ for the purpose of commercial vehicle surveillance at the San Onofre Truck Weigh and Inspection Facility in Southern California. The real-time performance measurement system (RTPMS) is based on a new vehicle reidentification algorithm called RTREID-2 and vehicle classification model, both of which are based on a new data extraction method that extracts an equal number of Piecewise Slope Rate (PSR) values from each vehicle signature. As a part of this study, a framework based on CORBA was developed to enable communication between field computers and the RTPMS server. A database system was also developed to store the output from the RTPMS server and present it in a prototype RTPMS Testbed Website that presents advanced real-time traffic performance measures. In the separate investigation of Blade™ inductive sensors, a new commercial vehicle classification model was developed to profile commercial vehicles by their body type and axle configuration. A new commercial vehicle vector classification framework is introduced to describe the depth of information available from this developed model. The results obtained from both studies have yielded very promising results, and warrants the need for further investigation.