Energy saving potentials of connected and automated vehicles |
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| Affiliation: | 1. Department of Mechanical Engineering, Clemson University, Clemson, SC 29634-0921, USA;2. Technology, Computer Science, and Applied Mathematics Div. IFP Energies Nouvelles, Rueil-Malmaison, France;1. Department of Mechanical Engineering, Clemson University, Clemson, SC, United States;2. BMW Group Information Technology Research Center, Greenville, SC, United States;1. Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Ave, Urbana, IL 61801, USA;2. Department of Mathematics, Temple University, 1805 North Broad Street, Philadelphia, PA 19122, USA;3. Inria, University Grenoble Alpes, CNRS, GIPSA-lab, F-38000 Grenoble, France;4. Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721-0104, USA;5. Lipscomb University, 1 University Park Drive, Nashville, TN 37204, USA;6. Yale University, New Haven, CT 06520, USA;7. Pennsylvania State University, University Park, PA 16801, USA;8. Department of Mathematical Sciences, Rutgers University – Camden, 311 N. 5th St, Camden, NJ 08102, USA;9. Department of Civil and Environmental Engineering, Vanderbilt University, 1025 16th Ave. S., Nashville, TN 37212, USA;1. State Key Laboratory of Automotive Simulation and Control, Jilin University, 5988, Renmin Ave., Changchun 130025, China;2. Automated Driving Lab, The Ohio State University, 1320 Kinnear Road, Columbus, OH 43212, USA;1. Department of Civil Engineering, Nagoya University, Nagoya, 4640803, Japan;2. Institute of Materials and Systems for Sustainability, Nagoya University, Nagoya, 4640803, Japan |
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| Abstract: | Connected and automated vehicles (CAV) are marketed for their increased safety, driving comfort, and time saving potential. With much easier access to information, increased processing power, and precision control, they also offer unprecedented opportunities for energy efficient driving. This paper is an attempt to highlight the energy saving potential of connected and automated vehicles based on first principles of motion, optimal control theory, and a review of the vast but scattered eco-driving literature. We explain that connectivity to other vehicles and infrastructure allows better anticipation of upcoming events, such as hills, curves, slow traffic, state of traffic signals, and movement of neighboring vehicles. Automation allows vehicles to adjust their motion more precisely in anticipation of upcoming events, and save energy. Opportunities for cooperative driving could further increase energy efficiency of a group of vehicles by allowing them to move in a coordinated manner. Energy efficient motion of connected and automated vehicles could have a harmonizing effect on mixed traffic, leading to additional energy savings for neighboring vehicles. |
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| Keywords: | Connected vehicles Automated vehicles Eco-driving Optimal control Anticipative driving Collaborative driving |
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