Matrix estimation from traffic counts: an alternative approach based on proportional path averages

Abstract

In attempting to match assigned volumes with traffic counts, several different methods are commonly used in transportation and traffic modelling to adjust demand matrices within iterative traffic assignment procedures. This paper describes an alternative approach based on proportional path averages, implemented using a simple algorithm translated into an Excel VBA macro. The algorithm can be applied independently of the assignment technique, as it requires as input only three text files: a demand prior matrix, a set of link and/or turn traffic counts and the assigned volumes along all Origin-Destination paths. An iterative adjustment is applied to the proportional path volumes where firstly, all fractional volumes passing through a count station are adjusted proportionally to match the specific count, and secondly, each fractional OD path volume is adjusted to match the average of the fractional path counts at all stations along the OD path. The two steps are repeated inside an inner loop until convergence, requiring at most 3 traffic assignments within the outer loop. Practical application of the principle is illustrated via two project case studies.