Methodology to Backcalculate Individual Speed Data Originally Aggregated by Road Detectors

Abstract

Highway and traffic engineers collect vehicular speed data with detectors based on a variety of fixed and mobile device technologies, to support analysis and design activities. Most acquisition units aggregate speed data into speed classes for ease of management and storage. An unfortunate result of this practice is a significant loss of content associated with individual speed data. Moreover, the use of individual speeds is often necessary to support road safety analysis and speed management decisions. For bridging of this gap, this paper introduces an algorithm that disaggregates speed data collected with automatic road detectors that can measure speed frequency only in intervals. The objective is to obtain backcalculated individual speeds that operate with continuous distribution functions rather than discrete ones. This information allows the derivation of more robust, basic descriptive measures (average, variance, and percentiles) according to normal, lognormal, and gamma probability distribution functions. Therefore, the information produced is more useful than that calculated from standard aggregated speed reports. In this investigation, individual speed data collected from video cameras were used to derive reference distributions and descriptive measures on the same road sections where inductive double-loop detectors were installed. Comparisons of the backcalculated individual speeds and those collected from video cameras support the validity of the proposed algorithm.