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

机译:基于模型的道路交通信息预测的生态驾驶员辅助系统

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摘要

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.
机译:这项研究提出了一种生态驾驶辅助系统(EDAS)的新概念,该系统可能在不久的将来在智能交通系统(ITS)中发挥重要作用。提议的EDAS旨在利用先进的传感和通信技术来测量即时车辆道路交通的相关信息。通过使用车辆动力学和交通流量模型,它可以预测车辆道路交通网络的未来状况,估算燃油消耗并生成生态驾驶所需的最佳控制输入。最佳控制输入一旦可用,便可以通过合适的人机界面来帮助驾驶员。车辆控制方法是使用模型预测控制算法开发的,该算法具有适当的性能指标,以确保安全和节油的驾驶。 EDAS在速度行为和燃油消耗方面的性能在微观运输模拟器AIMSUN NG上进行了评估。比较结果以图形方式说明和分析,以表明拟议的EDAS在构建环保ITS中的前景。

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