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Applied Sciences
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Digital and Intelligent Solutions for Transportation Infrastructure
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Digital and Intelligent Solutions for Transportation Infrastructure

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 June 2024) | Viewed by 11805

Special Issue Editors

Prof. Dr. Rongqiao Xu

E-Mail Website
Guest Editor
College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, China
Interests: design and analytical theory of transportation infrastructure; transportation infrastructure and digital twin; smart materials and structures
Dr. Zhengong Cai

E-Mail Website
Guest Editor
School of Software Technology, Zhejiang University, Hangzhou, China
Interests: intelligent management of infrastructure

Special Issue Information

Dear Colleagues,

The artificial intelligence (AI), internet of things (IoT) and robotics techniques have been rapidly developed in the area of transportation infrastructure. Highly intelligent construction methods, including standardized prefabrication and assembly, have been applied to a large extent in the construction of transportation infrastructure. The operation and maintenance of transportation infrastructure has also gradually shifted to multi-dimensional intelligence based on IoT monitoring and robot inspection, intelligent analytical evaluation of service performance based on big data, deep learning and unmanned maintenance based on robots. Digital twin technology in the transportation infrastructure could realize the multi-dimensional fusion analysis and dynamic visibility of mechanical models, performance testing, data sensing in detection/monitoring, and service history mapped in the virtual space. The new technology could greatly accelerate the digitization of the construction, management and maintenance of transportation infrastructure.

This Special Issue on ‘Digital & Intelligent Solutions for Transportation Infrastructure’ includes the following topics:

  • intelligent design and analysis for transportation infrastructure;
  • intelligent construction for transportation infrastructure;
  • intelligent operation, maintenance and detection/monitoring sensing for transportation infrastructure;
  • building digital platforms with digital twin technology;
  • reviews of recent studies, new discoveries and breakthrough in the area of transportation infrastructure;
  • discussion of the future development direction for the digitization and intelligentization of transportation infrastructure;
  • other related studies.

Prof. Dr. Rongqiao Xu
Dr. Zhengong Cai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • transportation infrastructure
  • intelligent building
  • intelligent perception
  • intelligent maintenance
  • intelligent modeling
  • intelligent algorithms
  • digital technologies
  • digital twins

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Published Papers (7 papers)

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Research

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13 pages, 2812 KiB  
Article
Quantitative Analysis of Influencing Factors on Changzhou Ship Lock Capacity
by Quanbo Xin, Yong Wang, Ming Zhang, Ruixi Wang and Yongchao Wang
Appl. Sci. 2024, 14(11), 4958; https://doi.org/10.3390/app14114958 - 6 Jun 2024
Viewed by 1063
Abstract
The Changzhou ship lock is approaching its capacity limit. In order to quantitatively analyze the influencing factors that restrict the capacity of the Changzhou ship lock, this study proposes an influencing factor analysis method based on principal component analysis (PCA). This method estimates [...] Read more.
The Changzhou ship lock is approaching its capacity limit. In order to quantitatively analyze the influencing factors that restrict the capacity of the Changzhou ship lock, this study proposes an influencing factor analysis method based on principal component analysis (PCA). This method estimates the confidence interval of ship passing time by fitting a lognormal distribution curve, eliminates redundancy in navigability data by combining the hydrological data and cargo load data, and quantitatively analyzes the influencing factors of ship lock capacity under saturated operating conditions. The results show that the influencing factors of Changzhou ship lock capacity are classified according to their influence contribution rate as minimum water depth above the lock sill, operation direction, ship dimensions, draft, loading capacity, and actual load. The research results can provide a theoretical basis for improving the ship lock capacity and have application value for lock scheduling management. Full article
(This article belongs to the Special Issue Digital and Intelligent Solutions for Transportation Infrastructure)
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26 pages, 4192 KiB  
Article
Supporting the Management of Rolling Stock Maintenance with an Ontology-Based Virtual Depot
by Hassna Louadah, Emmanuel Papadakis, Thomas Leo McCluskey and Gareth Tucker
Appl. Sci. 2024, 14(3), 1220; https://doi.org/10.3390/app14031220 - 31 Jan 2024
Cited by 2 | Viewed by 2968
Abstract
The railway industry forecasts growth in passenger and freight traffic over the next 30 years. This places additional demands on rolling stock depot facilities, many of which were designed and built before the modern age of information technology. This paper explores the potential [...] Read more.
The railway industry forecasts growth in passenger and freight traffic over the next 30 years. This places additional demands on rolling stock depot facilities, many of which were designed and built before the modern age of information technology. This paper explores the potential of improving the efficiency and effectiveness of rolling stock maintenance management to meet the challenges of the near future, by utilising advanced computing techniques. The objective of the work is to create optimised maintenance plans for a fleet of trains, considering optimal use of resources. As a “glue” for joining up functions and operations, a generic Depot and Vehicle ontology (called the Virtual Depot) is introduced. The ontology captures the structures, relationships, and attributes of objects in the Depot (rolling stock, sensors, depot assets, tools, resources, and staff). The ontology is populated with example company and fleet-specific knowledge using an automated knowledge acquisition method. This paper describes the systematic method for the creation of a Virtual Depot. Two particular aspects are discussed in detail—knowledge acquisition of fleet-specific information obtained from a manufacturer’s Vehicle Maintenance Instruction manuals and the construction of a short-term scheduling process within the Virtual Depot. Our evaluation considers the integrative aspects of the method, demonstrating how the ontological structure and its acquired specific information informs and benefits the scheduling process, in particular with respect to schedule optimisation. Results from an initial case study show there is significant potential to optimise short-term maintenance schedules, and the ability to automatically consider resource availability in short-term scheduling is demonstrated. Full article
(This article belongs to the Special Issue Digital and Intelligent Solutions for Transportation Infrastructure)
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15 pages, 878 KiB  
Article
A Hybrid Traffic Sensor Deployment Model with Communication Consideration for Highways
by Xing Tong, Ming Li and Zhichao Cui
Appl. Sci. 2024, 14(2), 536; https://doi.org/10.3390/app14020536 - 8 Jan 2024
Viewed by 1257
Abstract
This paper mainly studies the deployment of hybrid sensors on highways. By constructing the deployment location constraint model, the overall accuracy of sensor deployment can be maximized. In addition, in order to meet the needs of intelligent transportation, the consideration of traffic data [...] Read more.
This paper mainly studies the deployment of hybrid sensors on highways. By constructing the deployment location constraint model, the overall accuracy of sensor deployment can be maximized. In addition, in order to meet the needs of intelligent transportation, the consideration of traffic data communication is added to the work. The highway under study is first divided into several units, and the combination type of sensors is used to represent the possible layout of two adjacent sensors. Then, a 0–1 optimization model reflecting the interaction between the sensor position and the server position is established. Then, a two-step search algorithm is proposed to find the optimal solution of the model and determine the deployment scheme with maximum accuracy. Finally, an example is given to verify the method. The results show that there are significant differences between uniform unit-deployment schemes and non-uniform unit-deployment schemes. Through the sensitivity analysis of each factor, the influence of budget and communication radius on the deployment plan is proven. In addition, the ramp length can also have a negative impact on the target value. Full article
(This article belongs to the Special Issue Digital and Intelligent Solutions for Transportation Infrastructure)
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28 pages, 33130 KiB  
Article
Identification of Dynamic Vibration Parameters of Partial Interaction Composite Beam Bridges Using Moving Vehicle
by Tao Wu, Bowen Chen, Yong Chen, Biao Hu and Jian-Ping Lin
Appl. Sci. 2023, 13(22), 12534; https://doi.org/10.3390/app132212534 - 20 Nov 2023
Cited by 1 | Viewed by 1297
Abstract
The vibration response of a partial composite beam bridge under the influence of moving vehicular loads was investigated. Due to the coupling effect between the vehicle and the bridge, the vibration information of the vehicle encompassed the vibration information of the bridge. Consequently, [...] Read more.
The vibration response of a partial composite beam bridge under the influence of moving vehicular loads was investigated. Due to the coupling effect between the vehicle and the bridge, the vibration information of the vehicle encompassed the vibration information of the bridge. Consequently, the dynamic response of the vehicle could be utilized to extract the dynamic information of the composite beam. A moving mass-spring-damping system and composite beam elements considering interfacial slips were used for the interaction vibration of a vehicle-composite bridge. A finite element program for the interaction vibration analysis of the vehicle-composite beam bridge was developed. The program was used to extract the vibration information of the composite beam bridge by analyzing the vehicle displacement, velocity, and acceleration in the interaction vibration of the beam and the vehicle. Taking the Hangzhou Jiubao Bridge as the engineering background, the influences of structural parameters such as shear stiffness of connections, prestress magnitude, as well as vehicle parameters, including vehicle stiffness, damping, and mass, on frequency identification were analyzed. Furthermore, the influences of road roughness, disturbance force generated by vehicle random vibrations, and interference signals generated by signal transmission on frequency identification of the bridge were investigated. Full article
(This article belongs to the Special Issue Digital and Intelligent Solutions for Transportation Infrastructure)
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18 pages, 6669 KiB  
Article
Construction Control and Monitoring Platform of a Large-Segment Steel Box Girder with Hoisting Installation
by Feng Wen, Xu Liang, Chunlei Chen, Linghua Xu and Qian Feng
Appl. Sci. 2023, 13(17), 9573; https://doi.org/10.3390/app13179573 - 24 Aug 2023
Cited by 2 | Viewed by 1363
Abstract
The large-segment hoisting construction technology for bridges is increasingly widely used due to its flexibility and efficiency, although it also poses challenges to construction monitoring. Traditional monitoring technology is unitary with low data processing efficiency, making it difficult to meet the accuracy requirements [...] Read more.
The large-segment hoisting construction technology for bridges is increasingly widely used due to its flexibility and efficiency, although it also poses challenges to construction monitoring. Traditional monitoring technology is unitary with low data processing efficiency, making it difficult to meet the accuracy requirements of large-segment hoisting. The application of digital technology has brought about an opportunity for innovation in bridge construction monitoring technology. To address existing challenges and explore digital applications, this paper takes the integral hoisting construction control of the large-segment steel box girder in a large cross-sea bridge as an example, developing an alignment, stress, and temperature monitoring scheme by taking the key points of hoisting construction control into consideration. A monitoring platform was developed, and the workflow of large-segment hoisting construction monitoring is systematically summarized from the viewpoint of practical engineering, which provides a valuable reference for achieving precise and efficient construction monitoring and control in similar projects. Full article
(This article belongs to the Special Issue Digital and Intelligent Solutions for Transportation Infrastructure)
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14 pages, 4646 KiB  
Article
Conceptual Design and Preliminary Verification of Distributed Wireless System of Weigh-in-Motion
by Yun Wang, Lei Gong, Bingde Bao, Jianchao Pan, Qian Feng and Rongqiao Xu
Appl. Sci. 2023, 13(4), 2467; https://doi.org/10.3390/app13042467 - 14 Feb 2023
Cited by 1 | Viewed by 1752
Abstract
In this paper, the concept of a distributed wireless system of weigh-in-motion is proposed. A wireless sensor for weigh-in-motion (WIM) based on piezoelectric materials is designed. The corresponding prototype for indoor testing is made according to the design. It aims to realize the [...] Read more.
In this paper, the concept of a distributed wireless system of weigh-in-motion is proposed. A wireless sensor for weigh-in-motion (WIM) based on piezoelectric materials is designed. The corresponding prototype for indoor testing is made according to the design. It aims to realize the main functions of dynamic pressure sensing, charge signal amplification and conversion, wireless signal transmission and reception, etc. The material properties of the mechanical properties and the piezoelectric properties in the analyses are provided in detail. Through the indoor test platform, the feasibility of the wireless sensor for WIM designed in this paper is preliminarily verified, which provides a basic tool for the realization of the distributed self-powered wireless system of WIM in the next step. Full article
(This article belongs to the Special Issue Digital and Intelligent Solutions for Transportation Infrastructure)
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Other

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14 pages, 5836 KiB  
Technical Note
A Low-Complexity Accurate Ranging Algorithm for a Switch Machine Working Component Based on the Mask RCNN
by Lili Wei, Lingkai Kong, Zhigang Liu, Zhenglong Yang and Hua Zhang
Appl. Sci. 2023, 13(16), 9424; https://doi.org/10.3390/app13169424 - 19 Aug 2023
Cited by 1 | Viewed by 1037
Abstract
According to the intelligent development needs of railway operation and maintenance, turnout maintenance also needs an efficient and intelligent means of detection. It is the main method used to measure the access depth of static contact manually. In order to change the disadvantages [...] Read more.
According to the intelligent development needs of railway operation and maintenance, turnout maintenance also needs an efficient and intelligent means of detection. It is the main method used to measure the access depth of static contact manually. In order to change the disadvantages of the low efficiency and strong subjectivity of traditional schemes, a low-complexity accurate ranging algorithm of the Mask RCNN is proposed to measure the on–off working parts. Firstly, the Mask RCNN and an interactive iterative method are used to segment the region of interest accurately twice. Secondly, the graph distortion is corrected according to the vertex mapping principle. Finally, the accurate actual distance is calculated through fitting the linear distance transformation equation. Through the secondary segmentation and correction algorithm, the accurate calculation of a small target is completed. The experimental results show that the algorithm can accurately measure the distance of different working parts; the average processing time is 0.8 s/amplitude and the measurement error is ±1 mm. Full article
(This article belongs to the Special Issue Digital and Intelligent Solutions for Transportation Infrastructure)
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