首页> 外文会议>Annual American Control Conference >A Real-Time Optimal Eco-driving Approach for Autonomous Vehicles Crossing Multiple Signalized Intersections* This work was supported in part by NSF under grants ECCS-1509084, IIP-1430145, and CNS-1645681, by AFOSR under grant FA9550-12-1-0113, by ARPA-E‘s
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A Real-Time Optimal Eco-driving Approach for Autonomous Vehicles Crossing Multiple Signalized Intersections* This work was supported in part by NSF under grants ECCS-1509084, IIP-1430145, and CNS-1645681, by AFOSR under grant FA9550-12-1-0113, by ARPA-E‘s

机译:用于自主车辆交叉多个信号交叉路口的实时最佳生态驾驶方法*这项工作是由NSF在Grant Fa9550-12-1的AFOSR下的NSF下的NSF支持 - 0113,由Arpa-E的

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This paper develops a methodology for obtaining an optimal acceleration/speed profile for a single autonomous vehicle crossing multiple signalized intersections without stopping in free flow mode. We aim to minimize an objective function that involves a trade-off between travel time and energy consumption of autonomous vehicles. Our design approach differs from most existing approaches based on numerical calculations: it begins with identifying the structure of the optimal acceleration profile and then showing that it is characterized by several parameters, which are used for design optimization. Therefore, the infinite dimensional optimal control problem is transformed into a finite dimensional parametric optimization problem, which enables a real-time online analytical solution. We include simulation results to show quantitatively the advantages of considering multiple intersections jointly rather than dealing with them individually. Based on mild assumptions, the optimal eco-driving algorithm is readily extended to include interfering traffic.
机译:本文开发了一种用于获得单个自主车辆的最佳加速/速度曲线的方法,而不在没有停止在自由流动模式下停止的单一信号交叉路口。我们的目标是最大限度地减少涉及自动车辆的旅行时间和能耗之间的权衡的客观函数。我们的设计方法与基于数值计算的大多数现有方法不同:它开始识别最佳加速度分布的结构,然后表明它的特征在于用于设计优化的若干参数。因此,无限维度最优控制问题被转换为有限维参数优化问题,这使得实时在线分析解决方案。我们包括仿真结果,以便定量表明共同考虑多个交叉点而不是单独处理它们。基于温和的假设,最佳的生态驱动算法容易扩展以包括干扰流量。

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