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Ecological driver assistance system using model-based anticipation of vehicle–road–traffic information

Ecological driver assistance system using model-based anticipation of vehicle–road–traffic information

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This study presents a novel concept of an ecological driver assistance system (EDAS) that may play an important role in intelligent transportation systems (ITS) in the near future. The proposed EDAS is designed to measure relevant information of instant vehicle–road–traffic utilising advanced sensing and communication technologies. Using models of vehicle dynamics and traffic flow, it anticipates future situations of the vehicle–road–traffic network, estimates fuel consumption and generates the optimal control input necessary for ecological driving. Once the optimal control input becomes available, it could be used to assist the driver through a suitable human interface. The vehicle control method is developed using model predictive control algorithm with a suitable performance index to ensure safe and fuel-efficient driving. The performance of the EDAS, in terms of speed behaviour and fuel consumption, is evaluated on the microscopic transport simulator AIMSUN NG. Comparative results are graphically illustrated and analysed to signify the prospect of the proposed EDAS in building environmentally friendly ITS.

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