论文标题

在故障状态下智能车辆的多标准决策增强了公私合作伙伴关系

Multi-criteria Decision-making of Intelligent Vehicles under Fault Condition Enhancing Public-private Partnership

论文作者

Tao, Xin, Čičić, Mladen, Mårtensson, Jonas

论文摘要

随着自动化,电气化和数字化的车辆技术的发展,车辆变得越来越聪明,同时面临更复杂,不确定且经常发生的故障。在本文中,我们调查了在故障状态下操作车辆的维护计划,并将其作为多标准决策问题制定。维护决策是通过在道路网络中进行的路线搜索而产生的,并根据风险评估来评估车辆故障的不确定性。特别是,我们考虑两个标准,即公共时间损失的风险和任务延迟的风险,分别代表公共部门和私营部门的关注。开发了公共时间损失模型,以评估车辆故障和相应的牵引过程引起的交通拥堵。帕累托最佳的非主导决策集是通过评估决策风险来得出的。我们通过从现实世界情景中得出的数值实验来证明问题的相关性以及所提出方法的有效性。实验表明,忽略公共道路上车辆崩溃的风险可能会导致公共时间损失的高风险。通过提出的方法,可以提出其他决定,以大大减少公共时间损失的风险,而任务延迟的风险降低。这项研究旨在通过私营部门与公共部门之间的合作决策来催化公私伙伴关系,从而将来归档更可持续的运输系统。

With the development of vehicular technologies on automation, electrification, and digitalization, vehicles are becoming more intelligent while being exposed to more complex, uncertain, and frequently occurring faults. In this paper, we look into the maintenance planning of an operating vehicle under fault condition and formulate it as a multi-criteria decision-making problem. The maintenance decisions are generated by route searching in road networks and evaluated based on risk assessment considering the uncertainty of vehicle breakdowns. Particularly, we consider two criteria, namely the risk of public time loss and the risk of mission delay, representing the concerns of the public sector and the private sector, respectively. A public time loss model is developed to evaluate the traffic congestion caused by a vehicle breakdown and the corresponding towing process. The Pareto optimal set of non-dominated decisions is derived by evaluating the risk of the decisions. We demonstrate the relevance of the problem and the effectiveness of the proposed method by numerical experiments derived from real-world scenarios. The experiments show that neglecting the risk of vehicle breakdown on public roads can cause a high risk of public time loss in dense traffic flow. With the proposed method, alternate decisions can be derived to reduce the risks of public time loss significantly with a low increase in the risk of mission delay. This study aims at catalyzing public-private partnership through collaborative decision-making between the private sector and the public sector, thus archiving a more sustainable transportation system in the future.

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