Performance monitoring is an issue of growing concern both nationally and in Washington State. Travel times and speeds have always been of interest to traveler-information researchers, but as they become a key measure in performance monitoring, this interest is now greater than ever. However, instrumenting the roadway infrastructure to obtain this type of data is very expensive. In this project, we use transit vehicles as probe sensors and develop a framework to use the vehicle position estimates as a speed sensor.
This report documents the second phase of a three-phase project that will create a robust set of virtual sensors for freeways and arterials. The first phase was a proof of principle that examined the statistics of successfully using transit vehicles as traffic probes. The results of the second phase are presented in this report. An optimal filter method is described that estimates acceleration, speed, and position as a function of space and time. The third phase will implement a server to place speed estimates from the transit probe virtual sensors into the WSDOT Northwest Region’s operational Traffic Management System.
WSDOT will benefit from this work by gaining additional traffic management sensing capabilities without the additional installation and maintenance costs of cabinets, loops, and communications. The traveling public in metropolitan Seattle will benefit from having additional traveler information about arterials that can be used as alternatives to freeway travel. Publication of results that validate the techniques used to derive virtual sensors from transit probe vehicles will have a national impact as an increasing number of cities use transit fleet management systems.
April 21, 2007
Daniel J. Dailey, Fredrick W. Cathey.
Washington State Transportation Center (TRAC)
- # of Pages: 45 p., 1,401 KB (PDF)
- Subject: Advanced traffic management systems, Automatic vehicle location, Buses, Probe vehicles, Public transit, Traffic flow, Traffic speed.
- Keywords: Bus, transit, probe, Calman filters, Kalman smoother, GIS, AVL, TCIP, MML, virtual sensors, traffic probes, transit probes, speed sensors, geographic information systems, road traffic, traffic control, traffic engineering computing, transportation.
- Related Publications:
AVL Equipped Vehicles as Traffic Probe Sensor, (WA-RD 534.1).
AVL-Equipped Vehicles As Speed Probes (Final Phase), (WA-RD 617.1).
This abstract was last modified April 29, 2008