Are vehicle trajectories simulated by dynamic traffic models relevant for estimating fuel consumption? |
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Institution: | 1. Université de Lyon, IFSTTAR, ENTPE, Laboratoire d’Ingénierie Circulation Transports, 3 Rue Maurice Audin, 69518 Vaulx-en-Velin cedex, France;2. LUNAM Université, IFSTTAR, AME-EASE, F-44341 Bouguenais, France;3. IFSTTAR, Laboratoire Transports et Environnement, France;1. LUNAM Université (l’Université Nantes-Angers-Le Mans), Ifsttar (Institut français des sciences et technologies des transports, de l’aménagement et des réseaux), AME-LAE (département Aménagement-Mobilité-Environnement, Laboratoire d’Acoustique Environnementale), F-44341 Bouguenais, France;2. IRSTV FR CNRS 2488, Ecole Centrale de Nantes, Bâtiment T, 1 rue de la Noë, BP 92101, 44321 cedex 3, France;1. LUNAM Université, IFSTTAR, AME, LAE, Centre de Nantes, CS 4, Route de Bouaye, F-44341 Bouguenais, France;2. IRSTV, Ecole Centrale de Nantes, Bâtiment T, 1 rue de la Noë, BP 92101, 44321, France;1. Department of Sociology, Institute of Transportation Studies, University of California, Davis, United States;2. Institute of Transportation Studies, University of California, Davis, United States |
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Abstract: | This paper questions the relevance of microscopic traffic models for estimating the impact of traffic strategies on fuel consumption. Urban driving cycles from the ARTEMIS database are simplified into piecewise linear speed profiles to mimic the classical outputs of microscopic traffic flow models. Fuel consumption is estimated for real and simplified trajectories and links between kinematics and the fuel consumption errors are investigated. Simplifying trajectories causes fuel consumption underestimation, from ?1.2 to ?5.2% on average according to the level of simplification; errors can approach ?20% for some cycles. A focus on kinematic phases indicates that the maximum speed reached and the time decelerating are the main influences on fuel consumption. Finally, in the case where maximum speeds are estimated correctly, it is shown that errors committed at each kinematic phase when acceleration distributions are approximated by their mean values, converge towards small errors over complete cycles. A method is developed to quantify and reduce these errors. |
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Keywords: | Fuel consumption estimation Microscopic traffic modeling Driving cycle Trajectories simplification |
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