Deliver a Set of Tools for Resolving Bad Inductive Loops and Correcting Bad Data

Inductive Loops are widely used in California for traffic detection and monitoring. Extensive studies have been conducted to improve loop detection system performance. This paper reviews previous work on faulty loop data analysis for correction and faulty loop diagnosis. It is necessary to distinguish faulty loop data analysis and loop fault detection according to the data level. According to the level of data used, it divides the work in three levels: (1) macroscopic level as in TMC (Transportation Management Center) or PeMS (Performance Measurement System) in California, which uses highly aggregated data to look at loop problems related wide range; (2) mesoscopic level, which involves synchronized data for a section of freeways involving several control cabinet such as Berkeley Highway Lab (BHL); and (3) microscopic level: or at a control cabinet level including all the loop stations involved. Corresponding data correction methods are also briefly reviewed. The whole paper is enclosed as deliverables. We also look at the traffic data system from corridor management viewpoint. Some preliminary high level considerations have been poster-presented at the TRB Western Traffic Data Workshop on April 10-11 2008 at the National Academies Beckman Center in Irvine, LA. Title for the presentation is: “Developing Integrated Traffic Data System for Corridor Management and Operation”. The Presentation Summary and the poster are also enclosed as deliverables. Besides, we still spent certain time to look at systematically loop fault detection from a control cabinet level. We are investigating it in three aspects: (a) loop fault detection based low level signals; (b) data correction if possible; and (c) data imputation. 2. Progress on Task 7 and 8 T-7 Preliminarily Code the “Reporter Generator” software and establish data connection with PeMS. T-8. Code the software tool for scheduling and tracking the suspect loop detectors for onsite diagnostics.