Ride the tide of traffic conditions: opportunistic driving improves energy efficiency of timely truck transportation

We study the problem of minimizing fuel consumption of a heavy-duty truck traveling across the national highway network subject to a hard deadline, under a practical setting that traversing a road segment is subject to variable speed ranges due to dynamic traffic conditions. The consideration of dynamic traffic conditions not only differentiates our work from existing ones but also allows us to leverage opportunistic driving to improve fuel efficiency. The idea is for the truck to opportunistically wait(e.g., at highway rest areas) for benign traffic conditions, in order to traverse subsequent road segments at favorable speeds for saving fuel. We observe that the traffic condition and thus the speed ranges are mostly stationary within certain durations of the day, and we term them as phases. We formulate the fuel consumption minimization problem under phased speed ranges, considering path planning, speed planning, and opportunistic driving. We prove the problem is NP-hard, and develop a dual-subgradient algorithm for large-/national- scale instances. We characterize conditions under which the algorithm generates an optimal solution. We carry out simulations based on real-world traces over the US highway system. The results show that our scheme saves up to 20% fuel as compared to the shortest path based alternative, of which opportunistic driving contributes 13%. Meanwhile, opportunistic driving also reduces driving time by 6% as compared to only optimizing path planning and speed planning. As such, opportunistic driving offers a desirable design option to simultaneously reduce fuel consumption and hours of driving. Last but not least, our results highlight a perhaps surprising observation that dynamic traffic conditions can be exploited to achieve fuel savings even larger than those under stationary traffic conditions.我们研究了在实际的动态的交通条件下，车辆跨路段行驶受到可变速度约束时，如何优化重型卡车在国道上行驶时的燃油消耗的问题。对动态交通状况的考虑不仅使我们的工作区别于现有工作，还使我们能够利用机会化驾驶来提高燃油效率。该想法是使卡车策略性地等待（例如，在公路休息区）良性交通状况，以有利的更高能效的速度穿越后续路段以节省燃油。我们观察到交通状况以及速度范围在一天的特定时间阶段内大部分是固定的，我们将其称为交通相。考虑进路径规划，速度规划和机会化驾驶，我们制定了交通相速度约束下的油耗最小化问题。我们证明问题是NP难的，并且针对国家公路系统规模的实例开发了一个基于对偶次梯度理论的启发式算法。并且给出了启发式算法生成最佳解的条件。我们根据美国高速公路系统上的真实轨迹进行模拟。结果表明，与基于最短路径的替代方法相比，我们的方案最多可节省20％的燃料，其中13％是由机会化驾驶贡献的。同时，与仅优化路径规划和速度规划相比，机会化驾驶还将行驶时间减少了6％。因此，机会性驾驶提供了一种新的有利的设计空间，可同时减少油耗和驾驶时间。最后但并非最不重要的一点是，我们的结果突显出令人惊讶的观察结果，即可以充分利用动态交通条件来实现比静态交通条件下更大的节油效果。Xu, Wenjie.M.Phil. Chinese University of Hong Kong 2020.Includes bibliographical references (leaves 52-58).Abstracts also in Chinese.Title from PDF title page (viewed on October 24, 2022)