基于经济风险最小化的自动驾驶卡车短期维护规划
Short-term Maintenance Planning of Autonomous Trucks for Minimizing Economic Risk
摘要：
新的自动驾驶技术每天都在涌现，其中一些已经在现实世界中得到商业应用。在受益于这些技术的同时，自动驾驶卡车在短期维护计划方面也面临着新的挑战，这直接影响了卡车运营商的利润。在本文中，我们通过解决运输任务中自动驾驶卡车的维护规划问题来实现车辆健康管理系统。我们还提出了一个维修计划模型，使用基于风险的决策方法，确定维修决策与最小的经济风险的卡车公司。在评估经济风险时，同时考虑可用性损失和维护成本。我们证明了所提出的模型，说明现实世界的情况下，通过数值实验。在实验中，相比于三个基线方法，所提出的方法的预期经济风险降低了高达$47\%$。我们还对不同的模型参数进行了敏感性分析。分析表明，随着剩余使用寿命估计精度、订单取消前最大允许交货延迟时间和车间数量的增加，经济风险显著降低。实验结果有助于从经济的角度确定自动驾驶卡车未来的研究和开发注意事项。
英文摘要：
New autonomous driving technologies are emerging every day and some of them have been commercially applied in the real world. While benefiting from these technologies, autonomous trucks are facing new challenges in short-term maintenance planning, which directly influences the truck operator's profit. In this paper, we implement a vehicle health management system by addressing the maintenance planning issues of autonomous trucks on a transport mission. We also present a maintenance planning model using a risk-based decision-making method, which identifies the maintenance decision with minimal economic risk of the truck company. Both availability losses and maintenance costs are considered when evaluating the economic risk. We demonstrate the proposed model by numerical experiments illustrating real-world scenarios. In the experiments, compared to three baseline methods, the expected economic risk of the proposed method is reduced by up to $47\%$. We also conduct sensitivity analyses of different model parameters. The analyses show that the economic risk significantly decreases when the estimation accuracy of remaining useful life, the maximal allowed time of delivery delay before order cancellation, or the number of workshops increases. The experiment results contribute to identifying future research and development attentions of autonomous trucks from an economic perspective.
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