标题： 自主运输可能未来的一种定量分析 显示英文标题

标题： A Quantitative Analysis of Possible Futures of Autonomous Transport

摘要： 自主船舶（AS）用于货物运输近年来引起了相当多的关注。 它们承诺带来诸如减少船员成本、提高安全性和增加灵活性等好处。 本文探讨了通过利用计算机处理器和先进能源存储等快速改进的技术领域，实现海洋运输技术性能更快增长的影响。 基于几种运输方式（货船、航空、铁路、卡车运输）的历史改进率，使用了一个简化的马尔可夫链蒙特卡洛（MCMC）模拟的多式联运运输模型（IMTM），以探索AS不同技术改进率的影响。 结果表明，传统航运的年改进率（海洋货运船=2.6%，航空货运=5.5%，卡车运输=0.6%，铁路=1.9%，内河运输=0.4%）比与自动化相关的技术如计算机处理器（35.6%）、燃料电池（14.7%）和汽车自动驾驶硬件（27.9%）的改进率要低。 到2050年的IMTM模拟显示，任何一种自主运输方式的引入都会增加低成本运输选项的竞争，但不太可能显著改变运输方式成本的整体分布。 其次，如果所有运输方式最终都转换为自主系统，那么改进率的不确定性将导致一个复杂的多式联运解决方案，涉及多种选项，在一段时间内成本都大大降低。 最终，研究显示需要更准确地测量当前自主运输成本以及它们随时间的变化情况。 显示英文摘要

摘要： Autonomous ships (AS) used for cargo transport have gained a considerable amount of attention in recent years. They promise benefits such as reduced crew costs, increased safety and increased flexibility. This paper explores the effects of a faster increase in technological performance in maritime shipping achieved by leveraging fast-improving technological domains such as computer processors, and advanced energy storage. Based on historical improvement rates of several modes of transport (Cargo Ships, Air, Rail, Trucking) a simplified Markov-chain Monte-Carlo (MCMC) simulation of an intermodal transport model (IMTM) is used to explore the effects of differing technological improvement rates for AS. The results show that the annual improvement rates of traditional shipping (Ocean Cargo Ships = 2.6%, Air Cargo = 5.5%, Trucking = 0.6%, Rail = 1.9%, Inland Water Transport = 0.4%) improve at lower rates than technologies associated with automation such as Computer Processors (35.6%), Fuel Cells (14.7%) and Automotive Autonomous Hardware (27.9%). The IMTM simulations up to the year 2050 show that the introduction of any mode of autonomous transport will increase competition in lower cost shipping options, but is unlikely to significantly alter the overall distribution of transport mode costs. Secondly, if all forms of transport end up converting to autonomous systems, then the uncertainty surrounding the improvement rates yields a complex intermodal transport solution involving several options, all at a much lower cost over time. Ultimately, the research shows a need for more accurate measurement of current autonomous transport costs and how they are changing over time.