Investigating Effects of Correlated Service Times on System Performance: Implications in Border Crossing Operations

Abstract

Many transportation systems rely on information technology (IT) for effective and efficient system operations. When the IT systems or resources are shared among various processes or servers, the service times of these processes or servers become correlated. Failure to recognize such correlations in model development may lead to significant inaccuracies. The effects of various types of correlation in the context of border crossing operations were investigated. Several possible reasons for correlation among servers and the ways in which such correlations may affect system operations are explained. Three scenarios are investigated through numerical experimentation: correlated tandem queues, correlated parallel queues, and the impact of correlated parallel queues on a downstream service station. Models are developed with and without consideration for the correlation for these three cases. Ignoring correlation in the performance analysis (i.e., assuming that the servers are independent) leads to inaccurate results, especially when system use is great, that is, at high levels of congestion. In the case of parallel queues, independence assumption leads to overestimated system capacity and to underestimated capacity in tandem queues.