Multiple-Vehicle Origin–Destination Matrix Estimation from Traffic Counts Using Genetic Algorithm

Abstract

Existing methods for estimating origin–destination (O–D) matrix from link traffic counts cannot consider multiple-vehicle information, which is easily obtained from a field survey. Those methods use a single-vehicle information and it may decrease the performance of an O–D matrix estimator. Up until now, there is little research regarding multiple-vehicle O–D matrix estimation from multiple-vehicle link counts. This paper suggests a multiple-vehicle O–D matrix estimation from traffic counts using a genetic algorithm (GAMUC). From the numerical tests, we found that the performance of GAMUC was better than those of the previous methods for the error of target O–D matrix and for the number of link counts. In this paper, we also found that the method provided good results on the error of target O–D matrix and on the varied O–D matrix structure, which occurred when the target O–D matrix was different from the true one.

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