Modeling loop detector location for traffic data collection on urban arterials for advanced traveler information system (ATIS) application

Traffic information is very important for drivers to select their routes. Many cities in North America provide traffic information for freeways using congestion maps and speed tables on a Website. However these information displays do not include traffic information on arterials. One of the main reasons for lack of traffic information on arterials is due to the inability to collect traffic information using existing loop detectors. An inductive loop detector provides only one spot speed at a specific location. The loop detectors provide comparatively good information on freeway speeds to the extent that traffic flows for a road section are stable. This means that one spot speed location can be a representative for an entire freeway section. In contrast, on the arterial, the loop detectors provide different speed information depending on their location relative to traffic signals. Travel speeds vary widely because of traffic signals and differences in turning movements on urban arterials. This indicates that a single spot speed can hardly be a link travel speeds for an entire arterial section, unless it is appropriately placed in respect to traffic signals. In recognition of the above problems, this study focused on how to find the best detector location on major arterials with various signal controls, and how to validate and apply the results to provide traffic information, particularly travel speed/time, to drivers. The traffic simulation model, CORSIM used to determine the best detector locations. The results have shown that one spot speed, where the detector is placed at the best location, can represent an average travel speed on urban arterials with any type of signal control. The study has validated the results of the model using real-world data, and proposed a Detector-based Congestion Algorithm (DCA) for ATIS on urban arterials. This algorithm uses occupancy and speed information to reduce error rates.