Enhancing the Validity of Traffic Flow Models with Emerging Data

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in Buch/Sammelband/GutachtenBeigetragenBegutachtung

Beitragende

  • Rita Excell - , Centre for Connected and Automated Transport (CCAT) (Autor:in)
  • Jiaqi Ma - , University of Cincinnati (Autor:in)
  • Steven Shladover - , University of California at Berkeley (Autor:in)
  • Daniel Work - , Vanderbilt University (Autor:in)
  • Michael Levin - , University of Minnesota System (Autor:in)
  • Samer H. Hamdar - , George Washington University (GWU) (Autor:in)
  • Meng Wang - , Technische Universität Delft (Autor:in)
  • Stephen P. Mattingly - , University of Texas at Arlington (Autor:in)
  • Alireza Talebpour - , Texas A&M University (Autor:in)

Abstract

Modeling the impact of connected and automated vehicles (CAVs) on the environmental sustainability, mobility and safety of roadway traffic at the local link level or the regional network level requires a significant amount of currently non-available data. Multiple CAV test-beds and data collection efforts utilizing the latest sensing and communication technologies have been however publicized over the past few years. Such efforts have been led by the industry and public agencies in the US and abroad. Accordingly, (1) researchers and practitioners should be aware of the type and quantity of data needed to calibrate and validate traffic models while taking into account the impact of CAV technological specifications, the driver behavioral characteristics and the surrounding driving environments. (2) Moreover, the gap between such emerging data needs and the data made available to researchers or practitioners should be identified. This chapter summarizes the presentations of speakers that are investigating such gap during the Automated Vehicles Symposium 2017 (AVS17) held in San Francisco, California on July 11–13, 2017. These speakers participated in the break-out session titled “Enhancing the Validity of Traffic Flow Models with Emerging Data”. The corresponding discussion and recommendations are presented in terms of the lessons learned and the future research direction to be adopted. This session was organized by the AHB45(3) Subcommittee on Traffic Flow Modeling for Connected and Automated Vehicles.

Details

OriginalspracheEnglisch
TitelLecture Notes in Mobility
Herausgeber (Verlag)Springer Science and Business Media B.V.
Seiten233-241
Seitenumfang9
PublikationsstatusVeröffentlicht - 2019
Peer-Review-StatusJa
Extern publiziertJa

Publikationsreihe

ReiheLecture Notes in Mobility
ISSN2196-5544

Externe IDs

ORCID /0000-0001-6555-5558/work/171064722

Schlagworte

Schlagwörter

  • CACC, Calibration/Validation, CAV/AV, Data, Deployment, DSRCs, Platooning, Test-beds, Traffic flow modeling