Abstract
This paper describes the development of an electric car prototype, aimed at autonomous, energy-efficient driving. Starting with an urban electric car, we describe the mechanical and mechatronics add-ons required to automate its driving. In addition, a variety of exteroceptive and proprioceptive sensors have been installed in order to obtain accurate measurements for datasets aimed at characterizing dynamic models of the vehicle, including the complex problem of wheel-soil slippage. Current and voltage are also monitored at key points of the electric power circuits in order to obtain an accurate model of power consumption, with the goal of allowing predictive path planners to trace routes as a trade-off between path length and overall power consumption. In order to handle the required variety of sensors involved in the vehicle, a MOOS-based software architecture has been developed based on distributed nodes that communicate over an onboard local area network. We provide experimental results describing the current stage of development of this platform, where a number of datasets have been already grabbed successfully and initial work on dynamics modeling is being carried on.
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Torres Moreno, JL., Blanco Claraco, JL., Bellone, M., Rodrìguez, F., Gimènez, A., Reina, G. (2014). A Proposed Software Framework Aimed at Energy-Efficient Autonomous Driving of Electric Vehicles. In: Brugali, D., Broenink, J.F., Kroeger, T., MacDonald, B.A. (eds) Simulation, Modeling, and Programming for Autonomous Robots. SIMPAR 2014. Lecture Notes in Computer Science(), vol 8810. Springer, Cham. https://doi.org/10.1007/978-3-319-11900-7_19
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DOI: https://doi.org/10.1007/978-3-319-11900-7_19
Publisher Name: Springer, Cham
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