This paper presents a new method to model and optimize the vehicle fuel consumption and its speed in the design of an eco-driving assistance system (EDAS) developed within the EU ecoDriver project. The main objective of this EDAS is to combine a precise fuel consumption model with a robust optimization module. An optimal speed profile is obtained to reduce the energy consumption. The gear management is also included in this procedure. The instantaneous fuel consumption rate is expressed as a piecewise polynomial of the instantaneous engine speed and engine torque. A dynamic programming technique is used to optimize the vehicle fuel consumption considering the safety requirements. The real vehicle experiments show the good performance of the piecewise model. The algorithm is implementable in a light vehicle Renault Clio 3.
In the framework of future innovation and for the sake of road safety, there is a great hope in fully supporting, or even replacing, the human driver by reliable technology. But, due to the novelty of this context, an important care will have to be devoted to investigate drivers' expectation, needs, behavior and functional abilities to reach this goal. In this context, this paper reviews several human factors issues related to partial and fully automated vehicles, with discussion of strengths and weaknesses of methods investigating driver automation acceptability, trust, situation awareness and workload. Main results of these parameters in relation to automated driving are presented and relevant methodologies to investigate these human variables are discussed in the perspective of real road experiments context.
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