Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

A LiDAR-based methodology for monitoring and collecting microscopic bicycle flow parameters on bicycle facilities

Bibliographic Data

ID19337913
AuthorsEhsan Nateghinia (0000-0003-3736-4652, McGill University, corresponding author), David Beitel (0000-0002-9035-5627, McGill University), Asad Lesani (McGill University), Luis Miranda-Moreno (0000-0003-3322-1814, McGill University), Luis F Miranda-Moreno
Year2024
Volume51
Issue1
Pages129-153
Publication date2024-02-01
Open AccessYes
TypeARTICLE
VenueTransportation (JOURNAL)
Journal identifiersISSN: 0049-4488 • E-ISSN: 1572-9435
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s11116-022-10322-8
OpenAlexW4306790596
LanguageEN
References cited24

Block (permutation group theory) · Calibration · Flow (mathematics) · Geography · Ground truth · Headway · Lidar · Mean squared error · Remote sensing · Simulation · Statistics · Traffic flow (computer networking) · Artificial Intelligence · Autonomous Vehicle Technology and Safety · Computer Science · Environmental Science · Mathematics · Traffic Prediction and Management Techniques · Vehicle emissions and performance

  • Do people consider an acceptable travel time? Evidence from Berkeley, CA

    Open Access•Dimitris Milakis, Robert Cervero et al.•Journal of Transport Geography•2015

Highly citedNo

Tools

Open DOI
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae