Enhancing the Validity of Traffic Flow Models with Emerging Data

Research output: Contribution to book/conference proceedings/anthology/reportChapter in book/anthology/reportContributedpeer-review

Contributors

  • Rita Excell - , Australia and New Zealand Driverless Vehicle Initiative (Author)
  • Jiaqi Ma - , University of Cincinnati (Author)
  • Steven Shladover - , University of California at Berkeley (Author)
  • Daniel Work - , Vanderbilt University (Author)
  • Michael Levin - , University of Minnesota System (Author)
  • Samer H. Hamdar - , George Washington University (GWU) (Author)
  • Meng Wang - , Delft University of Technology (Author)
  • Stephen P. Mattingly - , University of Texas at Arlington (Author)
  • Alireza Talebpour - , Texas A&M University (Author)

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

Original languageEnglish
Title of host publicationLecture Notes in Mobility
PublisherSpringer Science and Business Media B.V.
Pages233-241
Number of pages9
Publication statusPublished - 2019
Peer-reviewedYes
Externally publishedYes

Publication series

SeriesLecture Notes in Mobility
ISSN2196-5544

Keywords

Keywords

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