Chapter
Jun 29, 2020
13th Asia Pacific Transportation Development Conference

Development of the Autonomous Vehicle Trajectory on the Hilly Road Using Approaches of Eco-Operating Modes

Publication: Resilience and Sustainable Transportation Systems

ABSTRACT

This paper presented the development of a novel approach to generate the trajectory for an autonomous vehicle running on a hilly road using approaches of eco-operating modes to minimize the fuel consumption. The study analyzed the ecological approaches for the accelerating mode and the braking mode. First, the curvilinear function of the eco-accelerating mode was developed by analyzing the profiles optimized by the genetic algorithm. Then, the curvilinear function of the eco-braking mode was generated and proved to be effective by the mathematical method. In this development, the fuel consumption model based on the vehicle specific power (VSP) was implemented with road conditions obtained from digital road maps. Subsequently, the development scheme of the vehicle trajectory on the hilly road was proposed by using the eco-accelerating mode, the eco-braking mode, and the cruising mode. It was shown that compared with the fix speed drive (FSD) vehicle, the fuel savings of the ecological speed drive (ESD) vehicle were 1.8%, 3.9%, 4.5%, and 3.4% when running on an up slope, a down slope, an up-down slope, and a down-up slope, respectively. Finally, when the proposed approach was adopted on a simulation network, its ability to reduce the fuel consumption was analyzed under different traffic volumes and market penetration rates of ESD vehicles.

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ACKNOWLEDGMENTS

The authors acknowledge the support from the National Key R&D Program of China (2018YFB1600700), and the Program of Henan Transportation Department (2018G3). The authors are thankful to all the personnel who either provided the technical support or assisted in the data collection and processing.

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Published In

Go to Resilience and Sustainable Transportation Systems
Resilience and Sustainable Transportation Systems
Pages: 725 - 733
Editors: Fengxiang Qiao, Ph.D., Texas Southern University, Yong Bai, Ph.D., Marquette University, Pei-Sung Lin, Ph.D., University of South Florida, Steven I Jy Chien, Ph.D., New Jersey Institute of Technology, Yongping Zhang, Ph.D., California State Polytechnic University, and Lin Zhu, Ph.D., Shanghai University of Engineering Science
ISBN (Online): 978-0-7844-8290-2

History

Published online: Jun 29, 2020

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Authors

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Henan Provincial Engineering Research Center for Public Transport Bigdata of Small-Medium Cities, Xuchang Univ., Weidu District, Xuchang, Henan, P.R. China. E-mail: [email protected]
Texas Southern Univ.; Beijing Jiaotong Univ.; and Xuchang Univ., Houston, TX. E-mail: [email protected]
Guohua Song [email protected]
MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong Univ., Haidian District, Beijing, P.R. China. E-mail: [email protected]
Henan Provincial Engineering Research Center for Public Transport Bigdata of Small-Medium Cities, Xuchang Univ., Weidu District, Xuchang, Henan, P.R. China. E-mail: [email protected]

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