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Leveraging Connected Vehicle Technology and Telematics to Enhance Vehicle Fuel Efficiency in the Vicinity of Signalized Intersections

机译:利用互联车辆技术和远程信息处理技术,在信号交叉口附近提高车辆燃油效率

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摘要

Driving on highways and arterial roadways involves vehicle acceleration, braking, cruising, coasting, and idling episodes. As the vehicle speed deviates from its "fuel optimum speed," additional fuel is consumed, thus reducing the vehicle fuel efficiency. The research presented in this article develops a connected vehicle application entitled Eco-Cooperative Adaptive Cruise Control (ECACC) that uses infrastructure-to-vehicle (I2V) communication to receive signal phasing and timing (SPaT) data, predict future constraints on a vehicle's trajectory, and optimize its trajectory to minimize the vehicle's fuel consumption level. The trajectory optimization is made using a moving horizon dynamic programming (DP) approach. A modified A-star algorithm is developed to enhance the computational efficiency of the DP for use in real-time implementations. The model is calibrated and tested on 30 top-sold vehicles in the United States and is demonstrated to provide fuel savings within the vicinity of signalized intersections in the range of 5 to 30%.
机译:在高速公路和主干道上行驶涉及车辆加速,制动,巡航,滑行和空转。当车辆速度偏离其“燃料最佳速度”时,消耗了额外的燃料,从而降低了车辆的燃料效率。本文介绍的研究开发了一种名为“生态合作式自适应巡航控制(ECACC)”的互联车辆应用程序,该应用程序使用基础设施到车辆(I2V)的通信来接收信号定相和定时(SPaT)数据,预测车辆轨迹的未来限制,并优化其轨迹以最大程度地减少车辆的油耗水平。使用移动视野动态规划(DP)方法进行轨迹优化。开发了一种改进的A-star算法,以增强用于实时实现的DP的计算效率。该模型在美国的30辆最畅销的汽车上进行了校准和测试,并被证明可以在信号交叉口附近节省5%至30%的燃油。

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