Method To Preprocess Observed Traffic Data for Consistency: Application of Fuzzy Optimization Concept

Abstract

For any of the algorithms of an intelligent transportation system (ITS) to be effective, high-quality data are essential. In reality the data obtained in the field carry significant noise because of imperfections in the measurement devices. For example, the traffic volume data on different links of a network must be consistent and must satisfy the conservation of flow, but this condition is rarely met by the observed values. A way to adjust the observed values so that the adjusted values satisfy predetermined conditions, such as the flow conservation equations or any consistency requirements in a network, is proposed. The adjusted values are found to be as close to the observed value as possible by using the concept of fuzzy optimization. The method can be applied to any network configuration and can also estimate the traffic volumes for links for which traffic volume data may be missing. The method is so general that it can be applied to various transportation problems in which a set of observed or calculated values must be adjusted to satisfy some predetermined rigid relationships among the parameters.

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