Statistical estimation of the parameters of Daganzo's gap acceptance model

Joel L. Horowitz*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In a recent article in Transportation Research, Daganzo (1981) described a model of gap acceptance that permits the mean of the gap acceptance function to vary among drivers and permits the duration of the shortest acceptable gap for each driver to vary among gaps. The model contains several constant parameters whose values must be estimated statistically from observations of drivers' behavior. The results of numerical experiments reported by Daganzo (1981) suggested that the values of the parameters cannot be estimated by the method of maximum likelihood, which is the most obvious estimation technique, and Daganzo proposed using a sequential estimation method instead. The sequential method appeared to yield reasonable numerical results. In this paper, it is shown that subject to certain reasonable assumptions concerning the true parameter values and the probability distribution of gap durations, the maximum likelihood method does, in fact, yield consistent estimates of the parameters of Daganzo's model, whereas the sequential method does not. Hence, maximum likelihood is the better estimation method for this model.

Original languageEnglish (US)
Pages (from-to)373-381
Number of pages9
JournalTransportation Research Part B
Volume16
Issue number5
DOIs
StatePublished - Oct 1982

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation

Fingerprint Dive into the research topics of 'Statistical estimation of the parameters of Daganzo's gap acceptance model'. Together they form a unique fingerprint.

Cite this