Eco-driving advisory strategies for a platoon of mixed gasoline and electric vehicles in a connected vehicle system |
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| Institution: | 1. Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, United States;2. School of Transportation Science and Engineering, Beihang University, Beijing 100191, China;3. Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China;1. Univ. Orléans, PRISME, EA 4229, F45072, Orléans, France;2. PSA Peugeot Citroën, Direction Recherche Innovation & Technologies Avancées (DRIA), France;1. School of Transportation Science and Engineering, Harbin Institute of Technology, China;2. Office of Operation Research and Development, Federal Highway Administration, United States;3. Department of Transport & Planning and Department of BioMechanical Engineering, Delft University of Technology, Netherlands;4. Department of Civil and Environmental Engineering, University of Virginia, United States;1. Department of Mechanical Engineering, Clemson University, Clemson, SC, United States;2. BMW Group Information Technology Research Center, Greenville, SC, United States;1. NEXTRANS Center, Purdue University, 3000 Kent Avenue, West Lafayette, IN 47906, United States;2. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, Sichuan, China;3. Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109, United States;4. University of Michigan Transportation Research Institute, University of Michigan, Ann Arbor, MI 48109, United States;5. National-Local Association Laboratory of Comprehensive Transportation Intelligentization, Southwest Jiaotong University, Chengdu, Sichuan, China |
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| Abstract: | As electric vehicles (EVs) have gained an increasing market penetration rate, the traffic on urban roads will tend to be a mix of traditional gasoline vehicles (GVs) and EVs. These two types of vehicles have different energy consumption characteristics, especially the high energy efficiency and energy recuperation system of EVs. When GVs and EVs form a platoon that is recognized as an energy-friendly traffic pattern, it is critical to holistically consider the energy consumption characteristics of all vehicles to maximize the energy efficiency benefit of platooning. To tackle this issue, this paper develops an optimal control model as a foundation to provide eco-driving suggestions to the mixed-traffic platoon. The proposed model leverages the promising connected vehicle technology assuming that the speed advisory system can obtain the information on the characteristics of all platoon vehicles. To enhance the model applicability, the study proposes two eco-driving advisory strategies based on the developed optimal control model. One strategy provides the lead vehicle an acceleration profile, while the other provides a set of targeted cruising speeds. The acceleration-based eco-driving advisory strategy is suitable for platoons with an automated leader, and the speed-based advisory strategy is more friendly for platoons with a human-operated leader. Results of numerical experiments demonstrate the significance when the eco-driving advisory system holistically considers energy consumption characteristics of platoon vehicles. |
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| Keywords: | Eco-driving Speed advisory Platoon Mixed traffic Electric vehicle Connected vehicle |
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