Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles

DImitris Assanis; Liuhui Zhao; Andreas A. Malikopoulos

doi:10.1109/ITSC.2018.8569432

Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles

DImitris Assanis
, Liuhui Zhao
, Andreas A. Malikopoulos

Mechanical Engineering

University of Delaware

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Connected and automated vehicles (CAVs) provide the most intriguing opportunity to improve traffic flow and eventually reshape the driving cycle of a typical commute. In this paper, we use a corridor consisting of a four-way intersection, a merging roadway, and a speed reduction zone to evaluate and quantify the impact of CAVs on a typical driving cycle. First, we use conventional vehicles that travel through this corridor to identify the baseline driving cycle, and then we use CAVs to determine how the baseline driving cycle is altered. We introduce specific metrics to quantitatively characterize a driving cycle and use these metrics to prescribe the new class of driving cycles for CAVs.

Original language	English
Title of host publication	2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3668-3673
Number of pages	6
ISBN (Electronic)	9781728103235
DOIs	https://doi.org/10.1109/ITSC.2018.8569432
State	Published - Dec 7 2018
Event	21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018 - Maui, United States Duration: Nov 4 2018 → Nov 7 2018

Publication series

Name	IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume	2018-November
ISSN (Print)	2153-0009
ISSN (Electronic)	2153-0017

Conference

Conference	21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018
Country/Territory	United States
City	Maui
Period	11/4/18 → 11/7/18

Access to Document

10.1109/ITSC.2018.8569432

Cite this

Assanis, DI., Zhao, L., & Malikopoulos, A. A. (2018). Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles. In 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018 (pp. 3668-3673). Article 8569432 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC; Vol. 2018-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2018.8569432

Assanis, DImitris ; Zhao, Liuhui ; Malikopoulos, Andreas A. / Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles. 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 3668-3673 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC).

@inproceedings{b3f389c7017047d4872afab152fcfbd1,

title = "Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles",

abstract = "Connected and automated vehicles (CAVs) provide the most intriguing opportunity to improve traffic flow and eventually reshape the driving cycle of a typical commute. In this paper, we use a corridor consisting of a four-way intersection, a merging roadway, and a speed reduction zone to evaluate and quantify the impact of CAVs on a typical driving cycle. First, we use conventional vehicles that travel through this corridor to identify the baseline driving cycle, and then we use CAVs to determine how the baseline driving cycle is altered. We introduce specific metrics to quantitatively characterize a driving cycle and use these metrics to prescribe the new class of driving cycles for CAVs.",

author = "DImitris Assanis and Liuhui Zhao and Malikopoulos, \{Andreas A.\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018 ; Conference date: 04-11-2018 Through 07-11-2018",

year = "2018",

month = dec,

day = "7",

doi = "10.1109/ITSC.2018.8569432",

language = "English",

series = "IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Assanis, DI, Zhao, L & Malikopoulos, AA 2018, Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles. in 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018., 8569432, IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, vol. 2018-November, Institute of Electrical and Electronics Engineers Inc., pp. 3668-3673, 21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018, Maui, United States, 11/4/18. https://doi.org/10.1109/ITSC.2018.8569432

Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles. / Assanis, DImitris; Zhao, Liuhui; Malikopoulos, Andreas A.
2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 3668-3673 8569432 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC; Vol. 2018-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2018/12/7

Y1 - 2018/12/7

N2 - Connected and automated vehicles (CAVs) provide the most intriguing opportunity to improve traffic flow and eventually reshape the driving cycle of a typical commute. In this paper, we use a corridor consisting of a four-way intersection, a merging roadway, and a speed reduction zone to evaluate and quantify the impact of CAVs on a typical driving cycle. First, we use conventional vehicles that travel through this corridor to identify the baseline driving cycle, and then we use CAVs to determine how the baseline driving cycle is altered. We introduce specific metrics to quantitatively characterize a driving cycle and use these metrics to prescribe the new class of driving cycles for CAVs.

AB - Connected and automated vehicles (CAVs) provide the most intriguing opportunity to improve traffic flow and eventually reshape the driving cycle of a typical commute. In this paper, we use a corridor consisting of a four-way intersection, a merging roadway, and a speed reduction zone to evaluate and quantify the impact of CAVs on a typical driving cycle. First, we use conventional vehicles that travel through this corridor to identify the baseline driving cycle, and then we use CAVs to determine how the baseline driving cycle is altered. We introduce specific metrics to quantitatively characterize a driving cycle and use these metrics to prescribe the new class of driving cycles for CAVs.

UR - https://www.scopus.com/pages/publications/85060465824

U2 - 10.1109/ITSC.2018.8569432

DO - 10.1109/ITSC.2018.8569432

M3 - Conference contribution

AN - SCOPUS:85060465824

T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

SP - 3668

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BT - 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018

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Assanis DI, Zhao L, Malikopoulos AA. Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles. In 2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 3668-3673. 8569432. (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC). doi: 10.1109/ITSC.2018.8569432

Characterization of the New Class of Driving Cycles for Connected and Automated Vehicles

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