Technical Papers
Aug 23, 2018

Stability Analysis of Connected and Automated Vehicles to Reduce Fuel Consumption and Emissions

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 144, Issue 11

Abstract

Obtaining an optimal stability condition is very important to benefit traffic flow operations for a mix of connected and automated vehicles (CAVs) and regular vehicles. In view of multiple spatial anticipations of CAV car-following models, this paper presents a stability analysis method for mixed CAV flow from the perspective of the uniform local platoon. Transfer function theory was used to derive the stability criterion of the uniform local platoon, based on which a stability chart of equilibrium speeds and CAV feedback coefficients was calculated. Numerical simulations were also performed on a segment of highway with an on-ramp using car-following models to evaluate the impacts of the stability analysis on fuel consumption and emissions [carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOX)]. The stability chart indicates that by controlling CAV feedback coefficients, the optimal stability condition can be obtained, in which the uniform local platoon remains stable for all driving speeds. Moreover, the stability analysis method can reduce fuel consumption and traffic emissions.

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Acknowledgments

This research was supported by the National Natural Science Foundation of China (51478113), the National Key R&D Program in China (2016YFB0100906), the Fundamental Research Funds for the Central Universities and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX17_0146), and the Scientific Research Foundation of the Graduate School of Southeast University (YBJJ1792).

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 144Issue 11November 2018

History

Received: Nov 14, 2017
Accepted: Jun 13, 2018
Published online: Aug 23, 2018
Published in print: Nov 1, 2018
Discussion open until: Jan 23, 2019

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Ph.D. Candidate, School of Transportation, Jiangsu Key Laboratory of Urban ITS, Southeast Univ., Nanjing 210096, China. Email: [email protected]
Professor, School of Transportation, Jiangsu Key Laboratory of Urban ITS, Southeast Univ., Nanjing 210096, China (corresponding author). Email: [email protected]
Professor, Dept. of Civil and Environment Engineering, Univ. of Wisconsin–Madison, Madison, WI 53706. Email: [email protected]

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