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Infrastructures
Special Issues
Smart Transportation Infrastructure: Optimization and Development
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Smart Transportation Infrastructure: Optimization and Development

A special issue of Infrastructures (ISSN 2412-3811). This special issue belongs to the section "Smart Infrastructures".

Deadline for manuscript submissions: 10 May 2026 | Viewed by 3298

Special Issue Editors

Prof. Dr. Jianqing Wu

E-Mail Website
Guest Editor
School of Qilu Transportation, Shandong University, Jinan 250061, China
Interests: intelligent roadside facilities; vehicle-road cooperative system; traffic safety; differentiated charging; intelligent monitoring system; smart transportation
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zhenhua Mou

E-Mail Website
Guest Editor
School of Transportation Engineering, Shandong Jianzhu University, Jinan 250101, China
Interests: habit; perceived behavioral control; mode choice; public transport; accessibility; transit; bus transportation; motor vehicles; travel time
Prof. Dr. Lidong Zhang

E-Mail Website
Guest Editor
School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 250357, China
Interests: traffic flow modelling; car-following model; intelligent transportation system; artificial intelligence; carbon footprint
Dr. Yuan Tian

E-Mail Website
Guest Editor
School of Qilu Transportation, Shandong University, Jinan 250061, China
Interests: intelligent transportation system; traffic signal control timing; road test laser radar traffic perception system; vehicle-road collaboration system; point cloud data processing and trajectory extraction; geographic information system

Special Issue Information

Dear Colleagues,

Smart transportation infrastructure integrates sensing technologies, digital platforms, and adaptive management into the design, construction, and operation of roads, railways, tunnels, and other critical facilities. By emphasizing optimization and development, it aims to improve their performance, durability, operational efficiency, and long-term value. Research in this area explores methods to enhance monitoring, planning, maintenance, and asset management, addressing increasing mobility demands and infrastructure aging.

This Special Issue, “Smart Transportation Infrastructure: Optimization and Development”, invites submissions on smart sensing and monitoring, digital modeling and simulation, sustainable design, and innovative strategies for construction, operation, and maintenance. Potential topics include, but are not limited to, the following:

  • Advanced assessment technologies: non-destructive evaluation techniques for monitoring infrastructure conditions;
  • Data-driven performance optimization: AI, machine learning, and predictive modeling for infrastructure deterioration, performance evaluation, and maintenance planning;
  • Infrastructure development and retrofitting: strategies for upgrading roads, bridges, and tunnels through adaptive design, lifecycle planning, and innovative construction or maintenance methods;
  • Materials and construction innovations: sustainable, recycled, or modified materials to improve structural performance and extend service life;
  • Monitoring and control systems: Internet of Things (IoT)-enabled sensor networks, automated data collection, and real-time monitoring and management;
  • Decision support and simulation tools: digital twins, modeling, and visualization for planning, maintenance, and optimization.

Prof. Dr. Jianqing Wu
Prof. Dr. Zhenhua Mou
Prof. Dr. Lidong Zhang
Dr. Yuan Tian
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 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Infrastructures is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 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

  • advanced assessment technologies
  • data-driven performance optimization
  • infrastructure development and retrofitting
  • materials and construction innovations
  • monitoring and control systems
  • decision support and simulation tools

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

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Research

21 pages, 6733 KB  
Article
Effect of Structural Parameters on Pantograph–Catenary Interaction Performance in High-Speed Railways
by Tong Xing, Xufan Wang, Like Pan, Yang Song, Dehai Zhang and Qun Yu
Infrastructures 2026, 11(3), 88; https://doi.org/10.3390/infrastructures11030088 - 9 Mar 2026
Viewed by 353
Abstract
With the rapid development of high-speed railways, the dynamic performance of the pantograph–catenary system plays a crucial role in ensuring the safe and stable operation of trains. This study investigates the effect of the structural parameters of the pantograph–catenary system to achieve good [...] Read more.
With the rapid development of high-speed railways, the dynamic performance of the pantograph–catenary system plays a crucial role in ensuring the safe and stable operation of trains. This study investigates the effect of the structural parameters of the pantograph–catenary system to achieve good dynamic interaction performance under high-speed conditions. A finite element model of the catenary system, incorporating nonlinear cable and truss elements, and a lumped mass model of the pantograph are developed. The penalty function method is employed to simulate the pantograph–catenary interaction. A total of 2187 dynamic simulations are performed, with seven variables—pantograph parameters, span length, contact wire tension, messenger wire tension, number of droppers, stitch wire length, and stitch wire tension. The comprehensive effect of these parameters is evaluated based on dynamic performance indicators, such as pantograph–catenary contact force, pantograph head lift, and support point lift. The results indicate that increasing the number of droppers, contact wire tension, and messenger wire tension enhances dynamic performance, while an increase in span length negatively affects performance. Stitch wire tension has little to no effect. Full article
(This article belongs to the Special Issue Smart Transportation Infrastructure: Optimization and Development)
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18 pages, 1639 KB  
Article
A Hybrid Optimization Approach for Multi-Criteria Decision Making in Emergency Response Coordination
by Ning Zhang, Jikai Wang, Shengtao Zhang, Fei Meng, Chuanyi Ma, Yuan Tian and Jianqing Wu
Infrastructures 2026, 11(2), 61; https://doi.org/10.3390/infrastructures11020061 - 11 Feb 2026
Viewed by 462
Abstract
Optimizing the allocation of emergency vehicles is essential for enhancing route-planning efficiency and ensuring road safety during traffic incidents. Traditional dispatch methods often struggle with complex scenarios due to their inability to integrate and balance multiple conflicting factors. This study proposes a multi-objective [...] Read more.
Optimizing the allocation of emergency vehicles is essential for enhancing route-planning efficiency and ensuring road safety during traffic incidents. Traditional dispatch methods often struggle with complex scenarios due to their inability to integrate and balance multiple conflicting factors. This study proposes a multi-objective dispatch framework for emergency vehicles that integrates regression analysis, deep learning, and an enhanced ant colony algorithm. Key environmental factors (e.g., weather, visibility) are selected through logistic regression, and a BP neural network predicts the impact ranges of accidents. The adaptive ant colony algorithm optimizes dynamic routing through innovations such as adjusting state transition probability and implementing pheromone reward—penalty strategies. It achieves faster convergence (with a comprehensive index of 86 in 8 iterations compared to 158 in 20 iterations) and superior path quality (a 9% reduction in rescue time and a 12% decrease in costs). Compared with existing hybrid frameworks, this study is the first to integrate logistic regression-selected environmental factors with BP neural network-predicted accident impact ranges, and further proposes adaptive state transition and pheromone reward-penalty update mechanisms, thereby achieving faster convergence speed and superior path quality in dynamic multi-objective rescue route planning. Full article
(This article belongs to the Special Issue Smart Transportation Infrastructure: Optimization and Development)
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18 pages, 6924 KB  
Article
Analysis of Subgrade Disease Mechanism Based on Abaqus and Highway Experiment
by Jianfei Zhao, Zhiming Yuan, Yuan Qi, Fei Meng, Kaiqi Zhong, Zhiheng Cheng, Yuan Tian and Cong Du
Infrastructures 2026, 11(2), 37; https://doi.org/10.3390/infrastructures11020037 - 23 Jan 2026
Viewed by 398
Abstract
The subgrade is a critical component of highway infrastructure that directly affects pavement performance and traffic safety. With the rapid expansion of highway networks and increasing heavy-truck traffic, latent subgrade distresses, such as insufficient base strength, uneven settlement, and base cracking, have become [...] Read more.
The subgrade is a critical component of highway infrastructure that directly affects pavement performance and traffic safety. With the rapid expansion of highway networks and increasing heavy-truck traffic, latent subgrade distresses, such as insufficient base strength, uneven settlement, and base cracking, have become key factors limiting pavement serviceability. These distresses are often difficult to detect at early stages and may evolve into sudden structural failures if not properly identified. This study investigates the evolution mechanisms and spatial characteristics of representative subgrade distresses through an integrated framework combining FWD screening, GPR imaging, core sampling, and Abaqus-based finite element simulation. Field data were collected from the Changshen Expressway. Potential weak zones were first identified using FWD testing and further localized by GPR, while multilayer constitutive parameters were obtained from core sample analyses. The field-derived material parameters were then incorporated into an FE model to simulate pavement responses under loading and to interpret the underlying distress mechanisms. The proposed framework enables identification of dominant distress types, quantification of stiffness degradation, and clarification of deterioration pathways within the subgrade system. The results provide practical support for condition assessment, health monitoring, and maintenance decision-making in highway infrastructure. Full article
(This article belongs to the Special Issue Smart Transportation Infrastructure: Optimization and Development)
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27 pages, 18434 KB  
Article
A Numerical Simulation Study on Vertical Vibration Response for Rail Squat Detection with a Train in Regular Traffic
by Zhicheng Hu and Albert Lau
Infrastructures 2025, 10(11), 313; https://doi.org/10.3390/infrastructures10110313 - 19 Nov 2025
Viewed by 576
Abstract
Squat is a type of rail defect that frequently poses challenges for railway tracks, as they generate dynamics and accelerate track degradation. Detecting rail squats is resource-intensive, given their relatively small size compared to the railway track. Often, by the time they are [...] Read more.
Squat is a type of rail defect that frequently poses challenges for railway tracks, as they generate dynamics and accelerate track degradation. Detecting rail squats is resource-intensive, given their relatively small size compared to the railway track. Often, by the time they are detected, damage has usually already occurred in other track components. Currently, rail squats are primarily detected using dedicated railway measurement vehicles. There has been a recent trend in research towards utilizing trains in regular traffic to monitor the condition of railway tracks. However, there is a lack of research and general guidelines regarding the optimal placement of accelerometers or sensors on trains for squat detection. In this study, multibody simulation software GENSYS Rel.2209 is employed to simulate a passenger train traversing rail squats under various scenarios, with each scenario characterized by a distinct set of typical feature values for the squats. The results demonstrate that the front wheel set, positioned closest to the defects, exhibits the highest sensitivity to vertical accelerations. Squat length is much more sensitive than depth for detection at typical speeds, and accelerometers on bogies or the car body require speeds below 40 km/h to ensure reliability. The acceleration response mechanism during squat traversal is explored, revealing the effects of varying squat geometries and train speeds. This finding enables a detection method capable of locating squats and estimating their length with over 90% accuracy. Practical recommendations are provided for optimizing squat detection systems, including squat width detection, sensor selection criteria, and suggested train speeds. It offers a pathway to detect squat more efficiently with optimized installation locations of accelerometers on a train. Full article
(This article belongs to the Special Issue Smart Transportation Infrastructure: Optimization and Development)
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15 pages, 2171 KB  
Article
A New Approach for Multiple Loads Identification Based on the Segmental Area of the Influence Lines
by Ping Liu, Weiwei Qiu and Sakdirat Kaewunruen
Infrastructures 2025, 10(11), 308; https://doi.org/10.3390/infrastructures10110308 - 16 Nov 2025
Cited by 1 | Viewed by 851
Abstract
The dynamic responses of bridges under multi moving loads are an essential precursor for their structural health monitoring (SHM). To enable the precise identification of the main moving load(s) among multiple moving loads, this study proposes an improved multi-source dynamic load [...] Read more.
The dynamic responses of bridges under multi moving loads are an essential precursor for their structural health monitoring (SHM). To enable the precise identification of the main moving load(s) among multiple moving loads, this study proposes an improved multi-source dynamic load identification algorithm based on the segmental area of the influence line (SAI). Firstly, the segmental area of the influence line was calculated according to the velocity of loads and the distance between two loads, and then, the moving load could be isolated based on the law of the minimal error combining the base area of the original influence line. In addition, experiments were conducted employing laser displacement sensor systems to acquire structural dynamic responses. The results showed the following for the segmental area of the influence line: (1) identification errors for a single moving load could be controlled within 5%, while an error within 10% was achieved under two moving loads; (2) vehicle displacement identification error remained consistently below 5%; and (3) the proposed algorithm exhibited a speed-insensitive characteristic, enabling effective load identification across varying vehicle speeds. The experimental findings confirm that this method accurately identifies the main moving loads in a small deformation condition and can be extended to similar applications. Full article
(This article belongs to the Special Issue Smart Transportation Infrastructure: Optimization and Development)
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