Enhancing the Validity of Traffic Flow Models with Emerging Data

Rita Excell; Jiaqi Ma; Steven Shladover; Daniel Work; Michael Levin; Samer H. Hamdar; Meng Wang; Stephen P. Mattingly; Alireza Talebpour

doi:10.1007/978-3-319-94896-6_20

Enhancing the Validity of Traffic Flow Models with Emerging Data

Rita Excell, Jiaqi Ma, Steven Shladover, Daniel Work, Michael Levin, Samer H. Hamdar, Meng Wang, Stephen P. Mattingly, Alireza Talebpour

Civil, Environmental, and Geo- Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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.

Original language	English (US)
Title of host publication	Lecture Notes in Mobility
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	233-241
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-319-94896-6_20
State	Published - 2019

Publication series

Name	Lecture Notes in Mobility
ISSN (Print)	2196-5544
ISSN (Electronic)	2196-5552

Bibliographical note

Funding Information:
The authors would like to acknowledge the breakout session organizers (thAHB45(3) committee members along with Robert Bertini from University of South Florida anSoyoung Ahn from University of Wisconsin, Madison) who made this book chapter possible Special thanks to Xiaopen Li from the University of South Florida, Danjue Chen from the University of Massachusetts Lowell, Steven Skabardonis from the University of California at Berkeley, Haizhong Wang from Oregon State University and Mark Brackstone from TSS-AIMSUM for their outreach efforts while coordinating the event details with the AVS2017 organizing committee.

Publisher Copyright:
© 2019, Springer International Publishing AG, part of Springer Nature.

Keywords

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

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10.1007/978-3-319-94896-6_20

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Cite this

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title = "Enhancing the Validity of Traffic Flow Models with Emerging Data",

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.",

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author = "Rita Excell and Jiaqi Ma and Steven Shladover and Daniel Work and Michael Levin and Hamdar, {Samer H.} and Meng Wang and Mattingly, {Stephen P.} and Alireza Talebpour",

note = "Funding Information: The authors would like to acknowledge the breakout session organizers (thAHB45(3) committee members along with Robert Bertini from University of South Florida anSoyoung Ahn from University of Wisconsin, Madison) who made this book chapter possible Special thanks to Xiaopen Li from the University of South Florida, Danjue Chen from the University of Massachusetts Lowell, Steven Skabardonis from the University of California at Berkeley, Haizhong Wang from Oregon State University and Mark Brackstone from TSS-AIMSUM for their outreach efforts while coordinating the event details with the AVS2017 organizing committee. Publisher Copyright: {\textcopyright} 2019, Springer International Publishing AG, part of Springer Nature.",

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AU - Wang, Meng

AU - Mattingly, Stephen P.

AU - Talebpour, Alireza

N1 - Funding Information: The authors would like to acknowledge the breakout session organizers (thAHB45(3) committee members along with Robert Bertini from University of South Florida anSoyoung Ahn from University of Wisconsin, Madison) who made this book chapter possible Special thanks to Xiaopen Li from the University of South Florida, Danjue Chen from the University of Massachusetts Lowell, Steven Skabardonis from the University of California at Berkeley, Haizhong Wang from Oregon State University and Mark Brackstone from TSS-AIMSUM for their outreach efforts while coordinating the event details with the AVS2017 organizing committee. Publisher Copyright: © 2019, Springer International Publishing AG, part of Springer Nature.

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Enhancing the Validity of Traffic Flow Models with Emerging Data

Abstract

Publication series

Bibliographical note

Keywords

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