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The envisioned operational tests of Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) in the Minneapolis/St. Paul area call for the provision of timely and reliable travel times over an entire road network. Unfortunately, travel time cannot be directly measured by certain new detection technologies, such as Automatic Vehicle Identification (A VI) or Automatic Vehicle Location (A VL) systems, these new technologies are not widely deployed and are much more costly than loop detectors. Finding an accurate way to estimate link travel time using loop detector data offers great economic benefits. This project examines the development if improved arterial travel time models. In the project's first phase, researchers reviewed existing travel time database. The project's second phase will seek to develop and evaluate new travel time estimation models.

Successful implementation of advanced traveler information systems over an entire urban network requires real-time measurement or estimation of arterial travel times ( or equivalently arterial journey speeds). This project develops an arterial journey speed model using data from inductive loop detectors and traffic controllers. This model incorporates the following key findings of traffic data analysis that researchers collected in Phase I. • Spot speeds are highly correlated with journey speeds when both speeds are low (0-15 mph) and uncorrelated with journey speeds when both speeds are high (greater than 25 mph). • Signal offsets or greenband width, traffic demand, green splits and capacity-reduction incidents are major factors that affect arterial travel time/journey speed. The model consists of two parts--the speed estimated from the volume and occupancy measured by detectors and the speed estimated based on critical volume/capacity ratio. Researchers tested and compared the model with a number of existing models, with promising results.