Transportation Engineering最新文献_第5页

AI-driven data mining for sustainable ship power system technologies 可持续船舶动力系统技术的人工智能驱动数据挖掘

Q1 Engineering

Transportation Engineering

Pub Date : 2025-08-08 DOI: 10.1016/j.treng.2025.100383

Peter J. Stavroulakis , Periklis Prousaloglou , Maria-Christina Kyriakopoulou-Roussou , Stratos Papadimitriou

Shipping is pivotal for global supply chains, yet its predominance is made possible through a plethora of negative externalities that include extensive and very critical social, ethical, and environmental costs. The industry tries to power through the latter with a prime facilitator, which refers to maritime technology. Indeed, hope is placed in novel marine systems as they can foster a new age of sustainable shipping that will provide global mobility with high efficiency and utilization of clean, green, and minimized (if not zero) emissions technologies. As such, the domain of maritime technology that refers to ship power systems is of indicative importance, yet the literature is barren of a concise understanding of the trends and directions of contemporary research. Said gap in the body of knowledge is tackled by the present work. Through the utilization of artificial intelligence (AI), this work adopts a data mining approach that is executed in the body of research concerning ship power systems, and core trends along with dominant themes are extracted. The results of the current study summarize and highlight an array of current and future technological applications that can become integral parts of ships’ onboard systems, aiding the industry toward its sustainability endeavour and fostering resilient prosperity for the global society. Consequently, this work is a valuable instrument for maritime practitioners and policy makers in evaluating and distinguishing the most viable and readily applicable alternatives to foster environmental respect and entrepreneurial growth, simultaneously.

航运是全球供应链的关键，但它的主导地位是通过大量的负面外部性实现的，这些负面外部性包括广泛而非常关键的社会、道德和环境成本。该行业试图通过一个主要的推动者来推动后者，这指的是海事技术。事实上，人们把希望寄托在新的海洋系统上，因为它们可以培育一个可持续航运的新时代，以高效率和利用清洁、绿色和最小化（如果不是零）排放的技术，为全球交通提供便利。因此，涉及船舶动力系统的海事技术领域具有指示性的重要性，但文献缺乏对当代研究趋势和方向的简明理解。目前的工作解决了知识体系中的上述差距。通过利用人工智能（AI），这项工作采用了一种数据挖掘方法，该方法在船舶动力系统研究中执行，并提取了核心趋势以及主导主题。目前的研究结果总结并强调了一系列当前和未来的技术应用，这些技术应用可以成为船舶机载系统的组成部分，帮助该行业实现可持续发展，促进全球社会的弹性繁荣。因此，这项工作是海事从业者和决策者评估和区分最可行和最容易适用的替代方案的宝贵工具，以同时促进环境尊重和企业增长。

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引用次数: 0

A blockchain ecosystem model for a sustainable last-mile delivery operation management 区块链生态系统模式，实现可持续的最后一英里配送运营管理

Q1 Engineering

Transportation Engineering

Pub Date : 2025-08-05 DOI: 10.1016/j.treng.2025.100379

Mohammad Yaser Mofatteh, Omid Fatahi Valilai

The rapid growth of information technology has accelerated the expansion of E-commerce and online shopping, making Last-mile Delivery a critical component in ensuring timely product access for end consumers. This research proposes a blockchain-based ecosystem that supports a sustainable and focuses on service-oriented last-mile delivery model. It involves four key stakeholders: customers, retailers, fleet carriers, and optimization specialists (miners). The model leverages blockchain features such as transparency, traceability, agile planning, and secure claim management during delivery. It also supports reverse logistics for product recycling, enhancing environmental sustainability. The proposed "Green Blockchain Ecosystem" is implemented as an open-source project on public repository, and its operational workflow from order to delivery is analysed, including stakeholder interactions and transactions. The paper also examines stakeholder data access control and evaluates the model’s financial and environmental impact through a numerical analysis.

信息技术的快速发展加速了电子商务和网上购物的发展，使“最后一英里配送”成为确保最终消费者及时获得产品的关键组成部分。这项研究提出了一个基于区块链的生态系统，支持可持续的，专注于面向服务的最后一英里交付模式。它涉及四个关键利益相关者：客户、零售商、车队运营商和优化专家（矿工）。该模型利用区块链特性，如交付过程中的透明性、可追溯性、敏捷计划和安全索赔管理。它还支持产品回收的逆向物流，提高环境的可持续性。提出的“绿色区块链生态系统”作为一个开源项目在公共存储库上实现，并分析了其从订单到交付的操作流程，包括利益相关者的互动和交易。本文还考察了利益相关者的数据访问控制，并通过数值分析评估了模型的财务和环境影响。

引用次数: 0

Performance and energy sizing of a series-hybrid aircraft using a modified energy distribution diagram and energy balance diagram: A case study of a German operator 基于改进的能量分布图和能量平衡图的串联混合动力飞机性能和能量大小：以德国运营商为例

Q1 Engineering

Transportation Engineering

Pub Date : 2025-08-04 DOI: 10.1016/j.treng.2025.100380

Bright Appiah Adu-Gyamfi , Clara Good , Steffen Haakon Schrader , Vegard Nergård

In pursuing sustainable aviation, efficient energy management is paramount, particularly for short-duration high-power flights, common in regional transport sectors. This paper presents a novel methodology for sizing batteries in hybrid-electric aircraft, specifically applied to a series-hybrid electric retrofit of the GA8 Airvan operated by Ostfriesischer-Flug-Dienst (OFD), which connects the mainland to Germany's northern islands. The core of the proposed approach lies in an innovative algorithm integrating energy distribution and balance considerations to determine the optimal battery size, balancing performance and weight. The study investigates three different charging scenarios, namely 1) overnight charging, 2) charging after each round trip, and 3) charging after each single flight. These alternative scenarios are designed to accommodate the dynamic nature of flight operations to optimize resource utilization and operational efficiency. Findings indicate that recharging the aircraft's battery after each flight is feasible with current technology; however, this practice may accelerate battery degradation. Incorporating an internal combustion engine (ICE) that can be used during diversions or the second leg of the flight significantly reduces fuel consumption by 34 % compared to today’s aircraft, suggesting hybrid systems could balance operational efficiency and sustainability. This research contributes to efforts to reduce aviation's environmental footprint and foster sustainable practices. The methodologies outlined have the potential to influence future electric and hybrid-electric aircraft design and operation, marking a significant step towards eco-friendly skies.

在追求可持续航空方面，有效的能源管理至关重要，特别是对于区域运输部门常见的短时间高功率飞行。本文提出了一种用于混合动力飞机电池尺寸的新方法，具体应用于由ostfriesisher - flug - dienst （OFD）运营的GA8空中客车的串联混合动力改装，该飞机连接了德国大陆和北部岛屿。该方法的核心在于一种创新的算法，将能量分配和平衡考虑结合起来，确定最佳的电池尺寸、平衡性能和重量。本研究研究了三种不同的充电场景，即1)夜间充电，2)每次往返后充电，3)每次飞行后充电。这些备选方案的设计是为了适应飞行操作的动态特性，以优化资源利用和操作效率。研究结果表明，在现有技术条件下，每次飞行后对飞机电池进行充电是可行的；然而，这种做法可能会加速电池的退化。与目前的飞机相比，在改道或第二段飞行中使用的内燃机（ICE）可以显著降低34%的燃油消耗，这表明混合动力系统可以平衡运行效率和可持续性。这项研究有助于减少航空业的环境足迹，促进可持续发展。概述的方法有可能影响未来电动和混合动力飞机的设计和运行，标志着向环保天空迈出了重要的一步。

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引用次数: 0

Investigation of injection rate characteristics and applicability of palm-biodiesel blending ratios in various diesel injector nozzle geometries under simulated CI engine operating conditions 模拟CI发动机工况下棕榈-生物柴油混合比例在不同喷嘴形状下的喷射速率特性及适用性研究

Q1 Engineering

Transportation Engineering

Pub Date : 2025-08-02 DOI: 10.1016/j.treng.2025.100378

Tan Chau Vo, Trung An Huynh

Variations in fuel properties, particularly density and kinematic viscosity, and the disturbed fuel flow inside the nozzle tip significantly affect the accurate determination of injection rate (IR) profiles and injection timing, impacting on their critical association with the effective diesel combustion mechanism, consequently posing a major challenge to the application of biofuels in diesel engines. This study investigates the effects of palm-biodiesel blending ratios and nozzle hole diameters on IR characteristics, serving as a comparative basis with diesel (B0) under various injection pressures. Three single-hole injectors with different nozzle hole diameters (0.28, 0.30, and 0.35 mm) and four palm-biodiesel blends (B15, B30, B60, and B100) were tested across a wide pressure range (400–1600 bar). Experiments were performed under a constant injection quantity, allowing isolated analysis of kinematic viscosity effects on the IR characteristics of a solenoid common-rail injector, while disregarding the influence of fuel density. The results show that blends up to B60 produce IR profiles comparable to diesel, exhibiting slightly lower quasi-steady state IR and marginally longer injection delays. In contrast, a clearly distinct trend for 100 % palm-biodiesel is observed. Increasing the nozzle hole diameter from 0.28 mm to 0.30 mm (7.14 % increase) and to 0.35 mm (16.67 % increase) enhances the quasi-steady-state IR of B100 by approximately 20.3 % and 39.4 %, respectively, across the experimental injection pressure range. At injection pressures below 1200 bar, the discharge coefficient of palm-biodiesel blends up to 60 % differs minimally from diesel; however, a noticeable opposite trend emerges for B60 at higher pressures.

燃油特性的变化，特别是密度和运动粘度的变化，以及喷嘴尖端内燃油流动的扰动，极大地影响了喷射速率（IR）曲线和喷射时间的准确测定，影响了它们与柴油有效燃烧机制的关键关联，从而对生物燃料在柴油发动机中的应用提出了重大挑战。本研究考察了棕榈-生物柴油混合比例和喷嘴孔径对红外特性的影响，作为不同喷射压力下与柴油（B0）的比较依据。在较宽的压力范围内（400-1600 bar）测试了三种喷嘴直径不同的单孔喷射器（0.28、0.30和0.35 mm）和四种棕榈生物柴油混合物（B15、B30、B60和B100）。实验是在恒定的喷射量下进行的，在忽略燃油密度影响的情况下，可以单独分析运动粘度对电磁共轨喷油器红外特性的影响。结果表明，B60的混合燃料产生的红外曲线与柴油相当，表现出稍低的准稳态红外和稍长的喷射延迟。相比之下，我们观察到100%棕榈生物柴油的明显趋势。在整个实验喷射压力范围内，将喷嘴孔径从0.28 mm增加到0.30 mm（增加7.14%）和0.35 mm（增加16.67%），B100的准稳态IR分别提高了约20.3%和39.4%。在低于1200巴的喷射压力下，棕榈生物柴油混合物的排放系数与柴油的差异最小，可达60%；然而，在较高的压力下，B60出现了明显相反的趋势。

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引用次数: 0

Predicting the temporal distribution of origin-destination traffic demand using machine learning 利用机器学习预测始发目的地交通需求的时间分布

Q1 Engineering

Transportation Engineering

Pub Date : 2025-07-27 DOI: 10.1016/j.treng.2025.100376

Keyvan Pourhassan , Mojgan Pourhassan , Sekhar Somenahalli

Temporal distribution of travel demand provides valuable insights into the planning and operation of transport systems. As a key input to dynamic traffic assignment (DTA) models, estimation of time-dependent origin-destination (TDOD) traffic demand matrices across the modelled network gained attention in the 1980s, with significant advancements in methods and techniques since then. However, the strong reliance on observed traffic counts has long been recognised as a limitation of these approaches. In the travel demand modelling (TDM) domain, the time-dependency of travel demand has been associated with travellers' characteristics, typically implemented through theory-based choice modelling (CM) methods informed by stated or revealed preference datasets. CM's reliance on preference datasets introduces its own limitations, e.g. the high cost of conducting reliable surveys, which constrain its broader applicability for predicting the temporal distribution of travel demand. This paper demonstrates the successful application of machine learning to predict the temporal distribution of origin-destination (OD) traffic demand using TDM data, including sociodemographic and land use information of the origin and destination zones as well as OD level network statistics, e.g. travel time. By incorporating the TDM data and available count-based TDOD estimates, we construct a combined dataset, which is partitioned into training, validation and test sets to train and evaluate the machine learning models. Results show that the trained models accurately predict the temporal distribution of origin-destination traffic demand. Our approach effectively addresses the limitations associated with count-based estimation and theory-driven choice modelling approaches.

旅行需求的时间分布为交通系统的规划和运作提供了宝贵的见解。作为动态交通分配（DTA）模型的关键输入，在20世纪80年代，随着方法和技术的显著进步，建模网络中时间相关的始发目的地（TDOD）交通需求矩阵的估计得到了关注。然而，对观测到的流量计数的强烈依赖长期以来一直被认为是这些方法的局限性。在旅行需求建模（TDM）领域，旅行需求的时间依赖性与旅行者的特征相关联，通常通过基于理论的选择建模（CM）方法实现，该方法由陈述或揭示的偏好数据集提供信息。CM对偏好数据集的依赖有其自身的局限性，例如进行可靠调查的高成本，这限制了其在预测旅行需求时间分布方面的更广泛适用性。本文展示了机器学习的成功应用，利用TDM数据预测出发地到目的地（OD）交通需求的时间分布，包括出发地和目的地地区的社会人口统计和土地利用信息，以及OD级别的网络统计，如旅行时间。通过合并TDM数据和可用的基于计数的TDOD估计，我们构建了一个组合数据集，该数据集被划分为训练集、验证集和测试集，以训练和评估机器学习模型。结果表明，所建立的模型能够准确地预测始发目的地交通需求的时间分布。我们的方法有效地解决了与基于计数的估计和理论驱动的选择建模方法相关的局限性。

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引用次数: 0

Exploring the role of an underground logistics system in enhancing Swiss intermodal freight 探讨地下物流系统在促进瑞士多式联运中的作用

Q1 Engineering

Transportation Engineering

Pub Date : 2025-07-26 DOI: 10.1016/j.treng.2025.100375

Mariana de Almeida Costa , Ihab Kaddoura , Annick Noll , Merlin Unterfinger , Miloš Balać , Francesco Corman

This research examines the integration of intermodal freight transport within Switzerland’s logistics network, focusing on the role of Cargo Sous Terrain (CST), a proposed innovative underground logistics system. Using the Swiss Transport Outlook 2050 by the Federal Office for Spatial Development (ARE), we developed an agent-based simulation model to analyse a potential future freight demand scenario considering inland, import and export cargo relevant to intermodal transport. The model evaluates the performance and interactions of road, rail, and CST, allowing containers to choose modes, routes, and schedules. This approach enables the investigation of intermodal dynamics, spatial factors, and transhipment processes. The results show that the modal share of intermodal rail remains stable and largely unaffected by CST, with its performance primarily dependent on terminal availability and capacity, maintaining a competitive position even when CST is fully developed. In contrast, the modal share of CST for intermodal transport is determined by network size, with a full CST network leading to significant increases in CST share. This expansion reduces road-leg distances for both rail and CST intermodal operations and promotes more regionalised freight flows, where specific terminals experience increased demand and shorter road legs. Additionally, the study examines the effects of varying costs and tolerance for delays on modal shares. By emphasising the importance of terminal infrastructure, network expansion, and coordinated mechanisms, the findings offer valuable insights into enhancing the efficiency, competitiveness, and sustainability of Switzerland’s intermodal freight system in response to future demand scenarios.

本研究考察了瑞士物流网络中多式联运货物运输的整合，重点关注货物地形（CST）的作用，这是一种拟议的创新地下物流系统。利用联邦空间发展办公室（ARE）的《瑞士运输展望2050》，我们开发了一个基于代理的模拟模型，以分析潜在的未来货运需求情景，考虑到与多式联运相关的内陆、进出口货物。该模型评估公路、铁路和CST的性能和相互作用，允许集装箱选择模式、路线和时间表。这种方法使多式联运动态，空间因素和转运过程的调查。结果表明，多式联运铁路的模式份额保持稳定，并且在很大程度上不受CST的影响，其性能主要取决于终端可用性和容量，即使在CST完全发展时仍保持竞争地位。相比之下，多式联运的CST模式份额是由网络规模决定的，一个完整的CST网络会导致CST份额的显著增加。这一扩展减少了铁路和CST多式联运业务的道路距离，并促进了更多的区区化货运流，其中特定的终端需求增加，道路距离缩短。此外，该研究还考察了不同成本和延迟容忍度对模式份额的影响。通过强调码头基础设施、网络扩展和协调机制的重要性，研究结果为提高瑞士多式联运货运系统的效率、竞争力和可持续性以应对未来需求提供了有价值的见解。

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引用次数: 0

An MPC-driven VSL control of motorway traffic by employing a continuum second-order traffic model 采用连续二阶交通模型的mpc驱动VSL控制高速公路交通

Q1 Engineering

Transportation Engineering

Pub Date : 2025-07-24 DOI: 10.1016/j.treng.2025.100365

Waheed Imran , Alessio Tesone , Balázs Varga , Gennaro Nicola Bifulco , Luigi Pariota

Variable speed limit (VSL) system driven by model predictive control (MPC) is implemented as a proactive traffic control measure for effective and safer traffic flow operations. Conventionally, the application of the VSL control hinges upon the discrete second-order macroscopic models. Conversely, the MPC paradigm hardly ever employs continuum second-order models for traffic control. In this paper, an improved continuum second-order macroscopic model is used as a predictive model in VSL control driven on MPC. The VSL control is based on actual motorway traffic in Dublin, and is implemented in a microscopic traffic simulation. The findings of the study are two-fold: first, the predictive capability of the continuum second-order model is evaluated; second, the effectiveness of the MPC-driven VSL control strategy is assessed. Within this MPC paradigm, the motorway experience a significant reduction in traffic congestion. The efficacy of the proposed VSL control is demonstrated with a key performance index, flatness index (FI). FI of 0.77 and 0.72 is observed in the congested segments of the motorway, indicating moderate to strong improvement of traffic flow with the VSL control. In other words, 58% to 76% improvement is observed in the congested segments of the motorway. The proposed framework is vital for effective traffic control as it demonstrates the capability to alleviate congestion.

模型预测控制（MPC）驱动的变速限制（VSL）系统是一种有效、安全的交通控制措施。传统上，VSL控制的应用取决于离散的二阶宏观模型。相反，MPC范式很少使用连续的二阶模型进行交通控制。本文采用改进的连续统二阶宏观模型作为MPC驱动VSL控制的预测模型。VSL控制是基于都柏林的实际高速公路交通，并在微观交通模拟中实现的。研究结果主要体现在两个方面：一是评价了连续统二阶模型的预测能力；其次，评估了mpc驱动的VSL控制策略的有效性。在这种MPC模式下，高速公路的交通拥堵显著减少。用关键性能指标平整度指数（FI）证明了所提出的VSL控制的有效性。在高速公路的拥挤路段，FI分别为0.77和0.72，表明VSL控制对交通流量有中等到强烈的改善。换句话说，高速公路拥堵路段的交通效率提高了58%至76%。建议的架构对有效的交通管制至关重要，因为它显示了纾缓挤塞的能力。

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引用次数: 0

Research on parameter optimization method of linear induction motor for rail transit based on kriging surrogate model 基于kriging代理模型的轨道交通直线感应电机参数优化方法研究

Q1 Engineering

Transportation Engineering

Pub Date : 2025-07-23 DOI: 10.1016/j.treng.2025.100373

Dangchao Ge

To improve the output stability of linear induction motor for rail transit, this paper proposes a parameter optimization method based on the Kriging surrogate model. The dynamic characteristics of rail transit linear induction motor parameters are thoroughly analyzed, with particular focus on improving the harmonic permanent magnet flux linkage amplitude response. Motor voltage, current, and flux linkage are introduced as dynamic guidance fusion parameters, while the Kriging surrogate model is employed to adjust both fundamental wave and harmonic frequency conversion dynamics of the motor parameters, effectively suppressing harmonic oscillations and controlling the output stability of rail transit linear induction motors. The experimental results demonstrate that after implementing this optimization method, the torque-to-current ratio reaches its maximum value, stator copper consumption is significantly reduced, and torque ripple is effectively suppressed. The achieved minimum transmission delay of 0.638 ms represents a substantial performance advantage.

为了提高轨道交通用直线感应电机的输出稳定性，提出了一种基于Kriging代理模型的参数优化方法。对轨道交通直线感应电机参数的动态特性进行了深入分析，重点研究了改善谐波永磁链幅值响应的方法。引入电机电压、电流和磁链作为动态引导融合参数，利用Kriging代理模型对电机参数的基波和谐波变频动态进行调节，有效抑制谐波振荡，控制轨道交通直线感应电机输出稳定性。实验结果表明，采用该优化方法后，定子转矩电流比达到最大值，定子铜耗显著降低，转矩脉动得到有效抑制。实现的最小传输延迟为0.638 ms，这代表了实质性的性能优势。

引用次数: 0

Designing and testing shape memory alloy actuators for smart aircraft wings 智能飞机机翼形状记忆合金作动器设计与试验

Q1 Engineering

Transportation Engineering

Pub Date : 2025-07-22 DOI: 10.1016/j.treng.2025.100374

Afsar Husain, Latifa Al Farsi, Muhra Alshamsi, Sanan H. Khan

The pursuit of enhanced aircraft performance through shape-adapting smart wings ne- cessitates lightweight, reliable, and efficient actuation systems. While Shape Memory Alloys (SMAs) offer a high power-to-weight ratio, a primary challenge remains in the validation of robust bidirectional control mechanisms within realistic airframe structures. This study presents a complete methodology for the design, additive manufacturing, and experimental testing of an aircraft flap actuated by an antagonistic SMA spring system. The core novelty lies in the holistic experimental validation of this dual-sided mechanism, which is fully integrated within a 3D-printed NACA 4412 airfoil, demonstrating a practical pathway from concept to functional prototype. A corresponding Finite Element Analysis was developed and validated to verify structural integrity under measured operational loads. Experimental testing demonstrated highly controllable and repeatable bidirectional flap deflections, achieving a maximum of 30^◦ of upward actuation at 12 V with response times under 20 s. The structural analysis confirmed the prototype’s robustness, with the highest stress concentrations correctly identified at the hinge. This work provides a validated, low-cost framework and critical performance data, offering a foundational step towards the practical implementation of advanced smart wing technologies. The findings underscore the viability of the antagonistic SMA design while also highlighting key operational challenges, such as the need for active cooling to improve reset times, which are critical for future development. This research serves as a comprehensive case study, bridging the gap between theoretical SMA capabilities and tangible aerospace application.

通过自适应形状的智能机翼来提高飞机性能，需要轻量级、可靠和高效的驱动系统。虽然形状记忆合金（sma）具有很高的功率重量比，但在实际机身结构中验证坚固的双向控制机制仍然是一个主要挑战。本研究提出了一种完整的方法，用于设计、增材制造和由对抗SMA弹簧系统驱动的飞机襟翼的实验测试。核心新颖性在于这种双面机制的整体实验验证，这是完全集成在一个3d打印的NACA 4412翼型，展示了从概念到功能原型的实际途径。开发并验证了相应的有限元分析，以验证结构在测量工作载荷下的完整性。实验测试证明了高度可控和可重复的双向襟翼偏转，在12 V下实现最大30◦的向上驱动，响应时间低于20 s。结构分析证实了原型的坚固性，在铰链处正确识别出最高的应力集中。这项工作提供了一个经过验证的低成本框架和关键性能数据，为先进智能翼技术的实际实施提供了基础步骤。研究结果强调了抗逆性SMA设计的可行性，同时也强调了关键的操作挑战，例如需要主动冷却来缩短复位时间，这对未来的发展至关重要。本研究作为一个全面的案例研究，弥合了SMA理论能力和实际航空航天应用之间的差距。

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引用次数: 0

AI project portfolio ranking in port and maritime industries: a novel framework for assessing deployment complexity 港口和航运业中的人工智能项目组合排名：评估部署复杂性的新框架

Q1 Engineering

Transportation Engineering

Pub Date : 2025-07-17 DOI: 10.1016/j.treng.2025.100370

Mehran Farzadmehr, Valentin Carlan, Thierry Vanelslander

Although AI is a trending topic and many industries are eager to adopt this technology, its successful implementation at the organizational level remains low. The majority of organizations are struggling with the assessment of AI initiatives to make informed investment decisions. The port and maritime industries are no exception in this regard. This research offers a concrete methodology to compare AI project portfolios based on their perceived deployment complexity. It first identifies the characteristics of AI initiatives that contribute to the overall deployment complexity of AI projects. Then, it leverages a list of characteristics as a typology and develops a structured framework for calculating the relative complexity of AI project portfolios and ranking them for further decision-making. A comprehensive literature review is first carried out on various topics, including technology adoption theories, to develop the AI typology. Afterward, the study calculates the deployment complexity of four AI project portfolios based on the data collected through interviews concerning the designed typology framework. The AI project portfolios are finally ranked based on their deployment complexity in the typology dimensions under different conditions. Using this novel assessment framework, port stakeholders can prioritize their AI project portfolios and start from AI initiatives under the least complex AI portfolio to build experience in AI deployments, minimizing the potential impact of failures.

尽管人工智能是一个热门话题，许多行业都渴望采用这项技术，但它在组织层面的成功实施仍然很低。大多数组织都在努力评估人工智能计划，以做出明智的投资决策。在这方面，港口和海运行业也不例外。这项研究提供了一种具体的方法，可以根据人工智能项目组合的部署复杂性来比较它们。它首先确定了有助于AI项目整体部署复杂性的AI计划的特征。然后，它利用特征列表作为类型学，并开发一个结构化框架，用于计算人工智能项目组合的相对复杂性，并为进一步的决策对它们进行排名。首先对各种主题进行全面的文献综述，包括技术采用理论，以发展人工智能类型学。随后，该研究根据通过访谈收集的有关设计的类型学框架的数据计算了四个AI项目组合的部署复杂性。最后根据AI项目组合在不同条件下在类型学维度上的部署复杂度对其进行排序。使用这种新的评估框架，港口利益相关者可以优先考虑他们的人工智能项目组合，并从最不复杂的人工智能组合下的人工智能计划开始，以建立人工智能部署的经验，最大限度地减少失败的潜在影响。

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引用次数: 0