Data-Driven Characterisation of Multidirectional Pedestrian Traffic

Marija Nikolić (), Michel Bierlaire () and Flurin Hänseler ()
Additional contact information
Marija Nikolić: École Polytechnique Fédérale de Lausanne, Transport and Mobility Laboratory, School of Architecture, Civil and Environmental Engineering
Michel Bierlaire: École Polytechnique Fédérale de Lausanne, Transport and Mobility Laboratory, School of Architecture, Civil and Environmental Engineering
Flurin Hänseler: École Polytechnique Fédérale de Lausanne, Transport and Mobility Laboratory, School of Architecture, Civil and Environmental Engineering

A chapter in Traffic and Granular Flow '15, 2016, pp 43-47 from Springer

Abstract: Abstract We propose theNikolić, Marija framework for pedestrianBierlaire, Michel traffic characterisation that is derived byHänseler, Flurin extending Edie’s definitions through a data-driven discretisation. The discretisation framework is based on three-dimensional Voronoi diagrams in order for the characterisation to be as independent as possible from an arbitrarily chosen aggregation. It can be designed through the utilisation of pedestrian trajectories described either analytically or as a sample of points.

Keywords: Pedestrian Traffic; Pedestrian Trajectories; Discretisation Framework; Three-dimensional Voronoi Diagram; Traffic Characterization (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-33482-0_6

Ordering information: This item can be ordered from
http://www.springer.com/9783319334820

DOI: 10.1007/978-3-319-33482-0_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().