A Demand Estimator Based on a Nested Logit Model

Tao Li ()
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Tao Li: Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia 24060

Transportation Science, 2017, vol. 51, issue 3, 918-930

Abstract: The importance of historical travel demand has been well recognized by transportation researchers and practitioners. This paper presents a new nonlinear demand estimator that can be applied in both ground and air transportation. The estimator is formulated such that the distribution of the estimated demand follows a nested logit model. To solve the demand estimator, we develop an exact solution algorithm, which maximizes its dual problem sequentially along unit directions and keeps some of the first-order optimality conditions satisfied for the estimator. We investigate the convergence of the algorithm. We prove that all of the accumulation points produced by the solution algorithm satisfy some optimality conditions. A large example (a real U.S. network), which contains 66,767 origin-destination pairs, is presented.

Keywords: OD demand estimation; path flow estimator; nested itinerary flow estimator; logit model; nested logit model; iterative solution algorithm (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:51:y:2017:i:3:p:918-930

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