Technical Papers
Mar 23, 2020

Empirical Analysis of a Freeway Bundled Connected-and-Automated Vehicle Application Using Experimental Data

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 6

Abstract

Connected-and-automated vehicles (CAV) hold the potential for substantial improvements to traffic safety, travel time reliability, driver comfort, roadway capacity, environmental impacts, and users’ overall travel experience. Numerous modeling and simulation studies have been conducted to evaluate these impacts. However, model accuracy and simulation assumptions limit the validity of evaluation results. These factors have resulted in the wide range of differences in effectiveness among studies examining the same CAV applications available in the literature. In this study, we propose a bundled CAV application that involves platoons of equipped vehicles governed by an integrated set of cooperative adaptive cruise control (CACC), cooperative merge, and speed harmonization applications. We implemented the bundled application in a fleet of five vehicles at the Saxton Transportation Operations Lab of the Federal Highway Administration. Experiments were conducted to collect and compare data on CAV and human-driven behavior. Based on the real experimental data, our results show that the performance of the CAV operations, including platooning and cooperative merging under varying Infrastructure-to-vehicle speed commands, demonstrate string stability. The results also present key behavioral parameters of the vehicles and strings. This will eventually help the research community, particularly the modelers, to come up with models with realistic performance to further understand the CAV impacts on traffic. The results can also serve as references for transportation agencies to make informed decisions on infrastructure and traffic management decisions.

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Data Availability Statement

Some or all data, models, or code generated or used during the study are available from the corresponding author by request (data analysis codes and a portion of the experimental data).

Acknowledgments

This study is funded in part by the US Department of Transportation (Project No. DTFH61-12-D-00020), National Science Foundation CMMI #1901998, and the University of Cincinnati Office of Research. The authors want to thank a few other team members for their contributions to the field experiment and paper manuscript: Kyle Rush, John Stark, Steven Shladover, Xiao-Yun LU, Robert Ferlis, Fang Zhou, Shuwei Qiang, and Michael McConnel. The work presented in this paper remains the sole responsibility of the authors.

References

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Information & Authors

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Published In

Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 146Issue 6June 2020

History

Received: May 31, 2019
Accepted: Oct 16, 2019
Published online: Mar 23, 2020
Published in print: Jun 1, 2020
Discussion open until: Aug 23, 2020

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Authors

Affiliations

Jiaqi Ma, M.ASCE [email protected]
Assistant Professor, Dept. of Civil and Architectural Engineering and Construction Management, Univ. of Cincinnati, 765 Baldwin Hall, Cincinnati, OH 45221 (corresponding author). Email: [email protected]; [email protected]
Edward Leslie [email protected]
Senior Electrical Engineer, Leidos, Inc., 11251 Roger Bacon Dr., Reston, VA 20190. Email: [email protected]
Transportation Engineer, Leidos, Inc., 11251 Roger Bacon Dr., Reston, VA 20190. ORCID: https://orcid.org/0000-0002-0986-9840. Email: [email protected]
Zhitong Huang [email protected]
Senior Transportation Engineer, Leidos, Inc., 11251 Roger Bacon Dr., Reston, VA 20190. Email: [email protected]
Graduate Research Assistant, Dept. of Civil and Architectural Engineering and Construction Management, Univ. of Cincinnati, 765 Baldwin Hall, Cincinnati, OH 45221. ORCID: https://orcid.org/0000-0002-4778-1823. Email: [email protected]

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