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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: closed (20 May 2024) | Viewed by 14384

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Special Issue Editors

Prof. Dr. Xu Guan

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Guest Editor

School of Management, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: supply chain management

Prof. Dr. Kai Wang

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Guest Editor

Economics and Management School, Wuhan University, Wuhan 430072, China
Interests: supply chain management; scheduling; health care management; computational optimization

Prof. Dr. Tingsong Wang

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Guest Editor

School of Management, Shanghai University, Shanghai 200444, China
Interests: maritime transportation; network modeling; operations research
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Special Issue Information

Dear Colleagues,

This Special Issue on “Efficient and Innovative Goods Transportation and Logistics” to be published in Applied Sciences aims to bring together recent theoretical, applied or methodological advances concerning operational management in sustainable transportation and the logistics industry, no matter whether pertaining to hardware, software or related innovative approaches. We encourage researchers in related fields with deep interest in making the transportation industry more sustainable and green to contribute their work, welcoming both research and review papers.

Prof. Dr. Xu Guan
Prof. Dr. Kai Wang
Prof. Dr. Tingsong Wang
Guest Editors

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Published Papers (7 papers)

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Research

25 pages, 4557 KiB

Open AccessArticle

Spatio-Temporal Transformer Networks for Inland Ship Trajectory Prediction with Practical Deficient Automatic Identification System Data

by Youan Xiao, Xin Luo, Tengfei Wang and Zijian Zhang

Appl. Sci. 2024, 14(22), 10494; https://doi.org/10.3390/app142210494 - 14 Nov 2024

Viewed by 423

Abstract

Inland waterways, characterized by their complex, narrow paths, see significantly higher traffic volumes compared to maritime routes, increasing the regulatory demands on traffic management. Predictive modeling of ship traffic flows, utilizing real AIS historical data, enhances route and docking planning for ships and port managers. This approach boosts transportation efficiency and safety in inland waterway navigation. Nevertheless, AIS data are flawed, marred by noise, disjointed paths, anomalies, and inconsistent timing between points. This study introduces a data processing technique to refine AIS data, encompassing segmentation, outlier elimination, missing point interpolation, and uniform interval resampling, aiming to enhance trajectory analysis reliability. Utilizing this refined data processing approach on ship trajectory data yields independent, complete motion profiles with uniform timing. Leveraging the Transformer model, denoted TRFM, this research integrates processed AIS data from the Yangtze River to create a predictive dataset, validating the efficacy of our prediction methodology. A comparative analysis with advanced models such as LSTM and its variants demonstrates TRFM’s superior accuracy, showcasing lower errors in multiple metrics. TRFM’s alignment with actual trajectories underscores its potential for enhancing navigational planning. This validation not only underscores the method’s precision in forecasting ship movements but also its utility in risk management and decision-making, contributing significantly to the advancement in maritime traffic safety and efficiency. Full article

(This article belongs to the Special Issue Efficient and Innovative Goods Transportation and Logistics)

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29 pages, 3829 KiB

Open AccessArticle

Evaluating Consolidation Centers of an Integrated Transportation Network under the Belt and Road Initiative

by Qin Yu, Guangmin Wang and Yun Xiao

Appl. Sci. 2024, 14(13), 5637; https://doi.org/10.3390/app14135637 - 27 Jun 2024

Viewed by 744

Abstract

Following the Belt and Road, the Air Silk Road has also been proposed. The coordinated development of multiple transportation modes, including air, land, and water, will create a strong transportation force in node cities. However, the current insufficient supply of cargo in various regions and the lack of integration among different transportation modes result in low transportation efficiency, which in turn affects the further advancement of the Belt and Road. To investigate these issues and attempt to find a solution, we selected 44 candidate cities from the prefecture-level cities in China as nodes based on relevant government policies, and constructed an integrated transportation network. For each node city, we first calculated the values of six classical indicators and then used the CRITIC to assign weights to each indicator. Subsequently, we employed the TOPSIS method combined with Grey Relational Analysis (GRA) to compute the comprehensive score for each node city. Based on the spatial layout and government policies under the BRI, eight cities, including Wuhan, Chongqing, Tianjin, Shanghai, Guangzhou, Lianyungang, Hefei, and Dalian, were finally recommended as the consolidation centers of the integrated transportation network. It is hoped that the results of this analysis can provide some insights for the government to outline and build the consolidation centers of the integrated transportation network composed of railway, air, highway, and water routes, which in turn can offer insights for elevating the Belt and Road Initiative (BRI) to a new level. Full article

(This article belongs to the Special Issue Efficient and Innovative Goods Transportation and Logistics)

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18 pages, 5905 KiB

Open AccessArticle

Studying Spatial Unevenness of Transport Demand in Cities Using Machine Learning Methods

by Denis Chainikov, Dmitrii Zakharov, Evgeniy Kozin and Anatoly Pistsov

Appl. Sci. 2024, 14(8), 3220; https://doi.org/10.3390/app14083220 - 11 Apr 2024

Cited by 2 | Viewed by 959

Abstract

The article discusses the issues of spatial unevenness of transport demand in the city by various transport modes. It describes the creation of models using an artificial neural network to estimate the travel time and share by private and public transport in a large city that does not have off-street transport. The city transport macromodel in PTV Visum (V.18) was used as a data source, from which data were obtained on 50 basic parameters taken into account in the specialized software during the development of the transport model. In total, 50 factors act as independent variables that do not have linear relationships with each other and with the dependent variable, which significantly complicates the use of other models. These models allow assessing the influence degree of the most important factors. Further, the article shows the uneven spatial distribution of the shares of trips by private and public transport across the areas of a city. Using machine learning methods, the transport areas of Tyumen were clustered into nine classes belonging to the central sector, where the share of public transport is significantly higher than at the city border. The dependence of the trip share by cars and shuttle buses on the average travel time and distance by private and public transport for each class of transport areas has been established. The research results can be used when creating new transport areas in the city macromodel and when adjusting transport planning documents. The methods used for analyzing big data on the operation of the transport complex can be implemented in the digital twin of the city and the Intelligent Transport System. Full article

(This article belongs to the Special Issue Efficient and Innovative Goods Transportation and Logistics)

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18 pages, 4149 KiB

Open AccessArticle

Improving Transportation Management Systems (TMSs) Based on the Concept of Digital Twins of an Organization

by Aleksey Dorofeev, Valery Kurganov, Nadejda Filippova, Artur Petrov, Dmitrii Zakharov and Sergei Iarkov

Appl. Sci. 2024, 14(4), 1330; https://doi.org/10.3390/app14041330 - 6 Feb 2024

Cited by 1 | Viewed by 2409

Abstract

Transportation process reliability is a competitive advantage in the market of cargo delivery services. Transportation customers are interested in shipping cargoes within agreed timeframes and ensuring their safety. These are the two main parameters of transportation process reliability, compliance with which depends on a number of factors. In particular, changes in the external environment where road transportation companies operate inevitably affect the transportation process stability. The purpose of this study is to develop an approach to road transportation reliability and risk mitigation based on the digital twin concept. The variability of business processes is usually the reason for deviations from the transportation terms agreed with the customer. These deviations can be interpreted as failures in delivering cargoes. A prerequisite for ensuring smooth cargo transportation by a road transportation company is the reduction of deviations in the performance of its business processes. The article proposes methods of computer modeling and creating a digital twin of a company reflecting the reference business processes for transportation. As a result, various deviations from the reference digital model that business processes exhibit when there are changes in the external environment can be promptly identified and corrected. Full article

(This article belongs to the Special Issue Efficient and Innovative Goods Transportation and Logistics)

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13 pages, 3691 KiB

Open AccessArticle

Cost-Effectiveness of Introducing Autonomous Trucks: From the Perspective of the Total Cost of Operation in Logistics

by Sangwan Lee, Kuk Cho, Hyunbae Park and Dooyong Cho

Appl. Sci. 2023, 13(18), 10467; https://doi.org/10.3390/app131810467 - 19 Sep 2023

Cited by 4 | Viewed by 3305

Abstract

This study explored the economic influence of introducing fully autonomous trucks (ATs) on the total cost of operation (TCO) from the viewpoint of freight transport operators. We utilized the cost–benefit analysis and scenario planning frameworks using a case study of a middle-mile route between a port and a large logistics distribution center in South Korea, where an autonomous truck pilot project has been running for several years. We employed a data source obtained from Hanjin Transportation Co., LTD., which enables us to reflect the actual expenses of operating freight transportation in the context of the study route. The findings of this study indicate that ATs would attain substantial operation cost savings for freight transport operators across all five scenarios, ranging from the most pessimistic to the most optimistic. Specifically, results of the base scenario reveal that monthly TCO decreases by 56.25, 47.04, 42.97, and 41.73 percent for 1-, 5-, 12-, and 25-ton trucks, respectively. The cost reduction per month was USD 2399 for a 1-ton truck, USD 2891 for a 5-ton truck, and USD 3438 for a 12-ton truck. Even in the most pessimistic scenario, the operation cost savings for operating with ATs in the route are USD 1415, USD 1642, USD 1985, and USD 2222 per month for 1-, 5-, 12-, and 25-ton trucks, respectively. When factoring in changes in cost, the wage reduction for vehicle drivers was substantial (USD 2430, USD 2835, USD 3240, and USD 3645 for 1-, 5-, 12-, and 25-ton trucks, respectively). However, remote operation was a new cost factor that increased TCO, which increased by USD 243,384,357 in the base case. This study’s findings have multiple implications, including (1) informing economic efficiency and productivity of operating autonomous vehicles (AVs), (2) providing insights on indicative cost estimates for AV operations, (3) providing valuable information for making informed investment decisions, and (4) supporting the notion that freight transport is an especially attractive market for AVs. Full article

(This article belongs to the Special Issue Efficient and Innovative Goods Transportation and Logistics)

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23 pages, 6602 KiB

Open AccessArticle

Synchromodal Supply Chains for Fast-Moving Consumer Goods

by Ilya Jackson, Maria Jesus Saenz, Yulu Li and Michelle Stephanie Ramirez Moreno

Appl. Sci. 2023, 13(5), 3119; https://doi.org/10.3390/app13053119 - 28 Feb 2023

Cited by 1 | Viewed by 3773

Abstract

Synchromodality is an emerging concept in supply chain management. A synchromodal supply chain can be defined as a multimodal transportation planning system, wherein the different agents work in an integrated and flexible way that enables them to dynamically adapt the transport mode based on real-time information from stakeholders, customers, and the logistic network. The potential of synchromodality for the fast-moving consumer goods (FMCG) industry is related to the nature of business. The FMCG market is characterized by relatively low margins and high turnover, which is especially important in export supply chains. However, for a company, it may be challenging to objectively evaluate the costs and benefits, not to mention the design of a synchronized supply chain. In order to facilitate the adoption of the concept and guide the practitioners, our study put forward the following research questions: What should be considered in incorporating synchromodality in the export supply chain for FMCG? How should companies approach tradeoffs among factors affecting the supply chain? To answer these questions, we propose an adaptable framework, which should be considered a primary contribution of our study. The framework incorporates the center of gravity model, mixed integer linear programming, and sensitivity analysis. The framework is validated using a real-world problem from a multinational FMCG company. The problem involves the optimal volume allocation and the selection of the most efficient transportation mode for inland freight. Our study demonstrates that incorporating synchromodality in the export supply chain could reduce the overall cost by 9% and enhance flexibility by allowing multiple modes of transportation. Full article

(This article belongs to the Special Issue Efficient and Innovative Goods Transportation and Logistics)

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31 pages, 4265 KiB

Open AccessArticle

Method of Assessing the Logistics Process as Regards Information Flow Unreliability on the Example of a Container Terminal

by Mateusz Zając and Justyna Swieboda

Appl. Sci. 2023, 13(2), 962; https://doi.org/10.3390/app13020962 - 10 Jan 2023

Cited by 1 | Viewed by 1946

Abstract

The reliability of logistics processes is most often considered in the context of the correct flow of materials. The information that accompanies the logistic flow is usually not considered a potential source of errors or disruptions to the correct operation of the logistic chain. The article presents literature studies in this field and presents a model for evaluating the logistics process, taking into account the quality of information. An example of process evaluation based on a container terminal was presented. Full article

(This article belongs to the Special Issue Efficient and Innovative Goods Transportation and Logistics)

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