Optimizing the trade-off between fuel consumption and travel time in an unsignalized autonomous intersection crossing

Andreas Hadjigeorgiou, S. Timotheou
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引用次数: 13

Abstract

Connected and autonomous vehicles (CAVs) have the potential to disrupt road transportation. CAVs provide several attractive features, such as seamless connectivity and fine-grained control, which can be exploited to improve the efficiency of traffic networks. In this work, the problem of CAV coordination at an unsignalized intersection crossing is considered, aiming to select the CAV trajectories that minimize fuel consumption and/or travel time. Nonetheless, the minimization of travel time implies high fuel consumption and vice-versa. For this reason, this work considers the problem of simultaneously optimizing the fuel consumption-travel time trade-off for a set of CAVs that are expected to arrive at the intersection within a specific time-window. As the resulting problem is non-convex, we construct a Mixed-Integer Programming formulation that provides tight lower and upper bounds. We also develop a heuristic convex-concave procedure that yields fast, high-quality solutions. Simulation results validate the effectiveness of the proposed approaches and highlight the importance of optimizing the fuel consumption-travel time trade-off, as small compromises in travel time produce significant fuel savings.
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无信号自动交叉口交叉口油耗与行驶时间的优化权衡
联网和自动驾驶汽车(cav)有可能颠覆道路交通。自动驾驶汽车提供了一些吸引人的功能,例如无缝连接和细粒度控制,可以用来提高交通网络的效率。本文研究了无信号交叉口自动驾驶汽车的协调问题,旨在选择燃油消耗和/或行驶时间最小的自动驾驶汽车轨迹。然而,旅行时间的最小化意味着高燃料消耗,反之亦然。因此,本研究考虑了一组预计在特定时间窗口内到达十字路口的自动驾驶汽车同时优化油耗-行驶时间权衡的问题。由于所得到的问题是非凸的,我们构造了一个提供紧下界和上界的混合整数规划公式。我们还开发了一种启发式凸凹程序,可以产生快速,高质量的解决方案。仿真结果验证了所提出方法的有效性,并强调了优化油耗-行驶时间权衡的重要性,因为行驶时间的微小妥协可以显著节省燃料。
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