Developing Extended Trajectory Database for Heterogeneous Traffic like NGSIM Database

Narayana Raju, Shriniwas Arkatkar, Said Easa, gaurang joshi

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)
79 Downloads (Pure)

Abstract

The present work introduced a framework of developing comprehensive extended vehicular trajectory data under heterogeneous non-lane-based traffic conditions like the NGSIM datasets in the United States. Due to the absence of automation and instrumentation, and even the lack of sensor deployment on roads in developing economies like India, it is even more challenging to study driver behavior. A new stitching-based algorithm was used for developing the extended trajectory database for three traffic-flow levels on a 535-m long section of an urban arterial. The algorithm was used to stitch the trajectory data over the segments such that the subject vehicle with continuous trajectory data points over the entire study stretch. The developed framework is a novel tool for establishing a trajectory dataset for mixed traffic, it should be of interest to researchers in developing and developed countries.

Original languageEnglish
Pages (from-to)555-564
Number of pages10
JournalTransportation Letters: the international journal of transportation research
Volume14
Issue number5
DOIs
Publication statusPublished - 2021

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • NGSIM
  • Rear-end collisions
  • mixed traffic
  • trajectory data

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