Testing New Solutions for Eco-Driving: Haptic Gas Pedals in Electric Vehicles

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DOI: 10.4236/jtts.2017.71001    1,450 Downloads   2,897 Views  Citations

ABSTRACT

Reducing energy consumption has become a matter of increasing concern for electric vehicle owners. EcoDriver is a project funded by the European Commission, searching for new eco-driving solutions for reducing energy consumption in private and public transport. EcoDriver’s main purpose is to teach efficient driving strategies and facilitate drivers’ decision-making processes through several feedback modalities, in order to help increase driving efficiency and therefore reduce energy consumption. In the present study, the Full ecoDriver System combined with a haptic feedback gas pedal was tested in real driving conditions to give answers to some questions about its effectiveness, efficiency, workload and acceptability in an electric vehicle. The sample profile was composed by thirty young but experienced drivers. They had to drive around an open road track which allowed several possible scenarios such as curves, intersection or roundabout, speed limit changes and preceding vehicles. Average speed was registered on each lap, likewise other subjective measurements. The main results suggest that the efficiency benefits achieved while driving depend on the event type and the feedback modality provided. For instance haptic feedback seems to be especially indicated for roundabouts. In addition, the visual feedback provided by the FeDS nomadic device helps to save energy and learn eco-driving strategies. These outcomes indicate how several feedback modalities could facilitate the decision making process, changing driving behaviour, reducing energy consumption and increasing safety. These questions would help advance further research on eco-driving Intelligent Transport Systems and driving behaviour issues.

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Perelló, J. , Gomila, A. , García-Quinteiro, E. and Miranda, M. (2017) Testing New Solutions for Eco-Driving: Haptic Gas Pedals in Electric Vehicles. Journal of Transportation Technologies, 7, 1-25. doi: 10.4236/jtts.2017.71001.

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