Real-time speed and vehicle-classification data are important inputs for modern freeway traffic control and management systems. However, these data are not directly measurable by single-loop detectors. Although dual-loop detectors provide speeds and classified vehicle volumes, there are too few of them on our current freeway systems to meet the practical ATMS (Advanced Traffic Management System) needs, and the cost of upgrading from a single-loop detector to a dual-loop detector is high. This makes it extremely desirable to develop appropriate algorithms to make single-loop detectors capable of performing the tasks of double loops. This paper presents just such an algorithm, i.e., one that uses single-loop measurements to provide accurate speed and vehicle-classification estimates. There are three steps in the algorithm: (1) to separate intervals with long vehicles (LVs) from those without; (2) to use measurements of intervals without LVs for speed estimation; and (3) to identify LV volumes for the intervals with LVs using the estimated speed. Preliminary tests for both spatial transferability and temporal transferability of the algorithm were performed, and the results were encouraging.
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Wang et al. (2003) studied this question.
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