This study systematically examines the potential for integrating crowd logistics (CL) with rail transport to enhance the efficiency, sustainability and multimodal performance of first and last-mile urban freight operations. It synthesizes the conceptual and empirical foundations of this emerging research area, identifies dominant scholarly trends and highlights gaps that constrain practical implementation of Rail-CL systems.

A systematic literature review was conducted following PRISMA 2020 guidelines. Fifty peer-reviewed publications from 2009 to 2025 were selected from major academic databases and evaluated using the 2018 Mixed Methods Appraisal Tool (MMAT). Extracted data covered study design, research aims, geographic scope, transport modes, technologies, sustainability outcomes, integration strategies and reported barriers. The evidence was synthesized using thematic and descriptive analysis.

The literature reveals a strong bias toward last-mile crowdshipping, with comparatively limited attention to first-mile operations and rail-based multimodal integration. Although environmental, economic and social benefits are frequently reported, most studies remain conceptual with limited real-world validation. Core challenges include regulatory uncertainty, inadequate rail-terminal infrastructure, coordination difficulties among stakeholders and persistent concerns regarding trust, liability and service reliability. Only a small number of studies propose integrated Rail and CL frameworks, confirming a substantial research gap.

This review offers the first comprehensive assessment of literature directly linking CL with rail freight transport. It establishes Rail and CL integration as an emerging research domain and outlines a forward-looking agenda focused on empirical testing, digital platform development and context-specific models particularly relevant for developing countries pursuing sustainable and resilient freight systems.

The expansion of the railway network and the increase in operation and maintenance intensity have rendered the durability, applicability and standardization of bridge guardrails key bottlenecks for ensuring personnel safety, improving the efficiency of maintenance windows, reducing the full life cycle cost, and promoting the high-quality development of railways. It is urgent to systematically sort out the domestic technological evolution, quantitatively evaluate the material performance, establish a full life cycle management framework, fill the gaps in the current standards regarding material selection, manufacturing and acceptance, and provide a scientific basis for the formulation of new standards.

(1) Literature and case study research - summarize the application characteristics and failure modes of steel, concrete, and fiber composite materials. (2) Material and process testing - measure the mechanical, corrosion resistance, and aging resistance properties of polyurethane pultruded composite materials. (3) Structural calculation - check the displacement of each railing post and handrail, and verify the safety margin. (4) Standard comparison - identify the gaps between domestic and international standards and the improvement paths.

Polyurethane railings are lightweight, high-strength, weather-resistant, maintenance-free, have minimal deformation and are suitable for coastal and cold regions. Steel railings corrode rapidly, are costly to repaint, and are difficult to maintain. Concrete is prone to cracking, frost peeling and rust expansion, and has a short lifespan. The current standards lack durability indicators, process control and full-life cycle evaluation, which restricts the promotion of new materials.

Establish polyurethane as the preferred option in complex environments; offer optimization directions for steel and concrete anti-corrosion structures; supplement durability indicators, process key points and cost models, and promote the standardization, lightweighting and long service life of ancillary facilities.

This paper presents a comprehensive systematic review of low-carbon solid waste materials applied in railway sub-ballast layers, aiming to critically assess their mechanical performance, durability, environmental benefits and regulatory readiness. The study addresses the growing need to decarbonize rail infrastructure while reducing dependence on natural aggregates, positioning sub-ballast as a strategic layer for circular economy implementation in ballasted track systems.

A PRISMA-based systematic review methodology was adopted to identify, screen and analyses peer-reviewed studies published between 2000 and 2025. The final database comprises experimental, numerical and field investigations covering mining residues, steel slags, construction and demolition waste, rubberized composites, alkali-activated materials and other industrial by-products applied to railway sub-ballast. Mechanical behavior under cyclic loading, resilient modulus, permanent deformation, hydraulic performance, durability and environmental indicators were extracted and synthesized. In parallel, an international regulatory analysis was conducted to compare sub-ballast specifications across Europe, North America, Asia-Pacific and Brazil, enabling identification of performance-regulation gaps and barriers to implementation.

The review demonstrates that several low-carbon waste-derived materials exhibit mechanical performance comparable to or exceeding that of conventional granular sub-ballast, particularly in terms of stiffness retention, resistance to permanent deformation and degradation under repeated loading. Steel slags, recycled concrete aggregates, slate waste and rubber-modified blends consistently show favorable resilient behavior and enhanced damping capacity, while certain mining residues and alkali-activated granular systems present promising strength and durability characteristics. Life-cycle evidence indicates substantial reductions in embodied carbon and natural aggregate consumption when these materials are adopted. However, current railway standards remain largely prescriptive and index-based, rarely incorporating cyclic performance criteria or carbon metrics, creating a structural disconnect between scientific evidence and regulatory acceptance. This gap significantly limits large-scale implementation despite growing technical maturity.

This study provides the first integrated synthesis focused exclusively on low-carbon solid waste materials for railway sub-ballast, combining mechanical performance, environmental assessment and international regulatory comparison within a unified analytical framework. By explicitly linking laboratory evidence to policy and standardization challenges, the paper advances performance-based pathways for sustainable railway substructure design. The findings offer actionable guidance for infrastructure managers, regulators and researchers seeking to accelerate the transition toward circular, low-carbon rail systems through sub-ballast innovation.

This paper presents an investigation of the innovative “Dual Configuration” management model implemented in China’s high-speed rail comprehensive inspection and test train initiative. Against the backdrop of continuous iteration in global railway technology, an evaluation is conducted of the advancements in organizational structure, resource allocation, and process standardization facilitated by this framework.

A systematic analysis is employed of multi-tiered collaborative mechanisms anchored in a matrix-based joint working group, complemented by a value-tree analytical method to quantify cost-benefit optimization across the full lifecycle of train assets. This integrated approach encompasses dynamic resource-scheduling protocols and comprehensive risk-control systems.

Results indicate the “Dual-Configuration” model achieves dual operational functionality within a unified platform, effectively compressing project duration and reducing lifecycle costs. Value tree analysis reveals multidimensional cost-saving mechanisms through platform sharing, consolidated maintenance systems, and parallel management processes. Field implementation validates that this model significantly enhances equipment utilization and mission responsiveness while supporting integrated Electric Multiple Unit (EMU) and inspection technologies.

Transferable management paradigms for high-speed rail system development and safety assurance are established in this research paper. The value-tree model provides a systematic framework for evaluating the economic benefits of dual-use platforms, offering quantitative decision-making support for complex infrastructure investments. Furthermore, concrete optimization strategies and cross-industry applications for the “Dual-Configuration” framework are proposed.

High-speed railway development in Vietnam requires an early assessment of wheel-rail degradation mechanisms. This study investigates wheel wear evolution and rolling contact fatigue (RCF) risk under representative high-speed operating conditions.

A numerical framework integrating multibody vehicle dynamics and wear prediction modelling is developed. Vehicle-track interaction is simulated in VI-Rail using a standard ERRI passenger bogie model. Key wheel-rail contact parameters, including normal forces, creepages and contact locations, are extracted and used in an Archard-based wear model to predict wheel profile evolution, while RCF risk is assessed using Hertzian contact stress indicators.

The results show that wheel wear alters tread geometry, with a maximum wear depth of approximately 0.2–0.4 mm, affecting vehicle dynamics. The critical speed varies non-monotonically, increasing by about 3–5% at early stages and decreasing by 10–15% with further wear. Track irregularities raise creepage to the order of 10?³ and increase wear rate by 20–30%. These effects also indicate an elevated risk of RCF.

The study provides a multibody dynamics-based framework for analysing wheel wear and RCF in prospective Vietnamese high-speed railway applications. The proposed framework also provides a scientific basis for assessing wheel degradation and supporting infrastructure design, operational planning and predictive maintenance in high-speed railway systems.

The study aims to analyze the relationship between seismic damage to various railway infrastructures and seismic intensity through historical seismic damage investigations of conventional railways, thereby addressing the issues of a lack of focus in post-earthquake inspections and prolonged train service restoration times after seismic events.

Post-earthquake railway inspection data were collected from 6 historical earthquakes in Xinjiang and 4 in the Sichuan-Yunnan region through field surveys and data research. Longitude and latitude coordinates of damaged sections were calculated according to their kilometer markers (K marks) and visualized on maps. The approximate seismic intensity at each damage site was estimated using intensity attenuation relationships or instrumental intensity data from adjacent stations, and empirical patterns of seismic damage modes were summarized.

Through investigations of historical seismic data and actual railway damage in Xinjiang and the Sichuan-Yunnan region, results indicate that in areas with seismic intensity greater than Level V (I > V), main structural damage to conventional railway infrastructure occurs. This includes cracking of bridge piers and abutments, differential settlement at bridge ends, track distortion, fracture of tunnel portals, and edge collapse, all of which disrupt train operations. In contrast, in areas with seismic intensity of Level Vor below (I 5 V), no records indicate that earthquakes caused main structural damage to conventional railway infrastructure. Only damage to ancillary facilities was observed, such as concrete spalling from girders, cracking of transverse diaphragms, damaged protective cones, deformed limiters, and cracks in subgrade slopes—none of which affect train passage.

Based on investigations into the post-earthquake infrastructure conditions of conventional-speed railways in earthquake-prone regions of China such as Xinjiang, Sichuan and Yunnan after 10 historical earthquakes, this study analyzed the correlation between seismic damage and corresponding seismic intensities using instrumental intensity data from surrounding seismic stations and intensity attenuation laws. A conclusion was drawn that train operation remains unaffected in areas with seismic intensity no higher than V (I 5 V). For the first time, this research established a correlation between post-earthquake damage to conventional-speed railways and seismic intensity, and identified the safety threshold at seismic intensity V. The findings enable railway personnel to conduct targeted post-earthquake inspections, significantly reduce inspection workload, and alleviate the pressure on post-earthquake operation recovery.

This paper presents an integrated technical and economic assessment of hot axle box detectors (HABD) and hot wheel detectors (HWD) important components of derailment prevention strategies, whose role extends beyond auxiliary monitoring to become cornerstones of derailment prevention and operational resilience. Building upon the International Union of Railways (UIC) Network Monitor Phases 1–3, the study synthesises international benchmarking evidence, cost–benefit analysis and operational practice to provide a coherent framework for decision-making, deployment and harmonisation.

The methodology combines three layers: (1) international benchmarking of national rules, detector spacing and alarm thresholds across Europe, North America, Asia and Australia; (2) a cost–benefit model based on avoided accidents, fatalities and disruption, tested through sensitivity analyses of detector density and false-alarm rates; and (3) operational doctrines covering alarm logic, reliability, availability, maintainability and safety requirements, operations control centre integration and lifecycle maintenance. The findings are aligned with European Union Agency for Railways guidance, UIC International Railway Solution (IRS) 70729 and lessons from Demonstration of Railway Infrastructure Reliability and Sustainable Railway projects.

Findings confirm that HABD/HWD systems provide significant safety and economic value when integrated into operational rulebooks, maintenance workflows and digital platforms. Multi-sensor and AIenabled detectors reduce false positives and enhance early detection, while international harmonisation efforts (e.g. IRS 70729 and EHMS) support cross-border interoperability. This study provides evidence-based guidance for risk-based deployment and lifecycle optimisation within modern railway safety frameworks.

This paper provides a comprehensive international synthesis that connects benchmarking, cost–benefit and operational safety frameworks into a structured doctrine for HABD/HWD deployment. It provides infrastructure managers and railway undertakings with evidence-based guidance on risk-based siting, lifecycle optimisation and international harmonisation. The work also contributes to the forthcoming UIC IRS, positioning HABD/HWD as globally relevant digital safety assets within the broader agenda of railway innovation, digitalisation and socio-economic resilience.

The purpose of this study is to reduce wheel–rail vibration noise (with the noise level increasing by approximately 9 dB for every doubling of train speed) by enhancing wheel damping. Besides, it verifies the performance of the damping wheel and provides support for the engineering application of low-noise wheels.

This study takes the damping ring-constraint layer composite wheel as the research object. First, it proposes a wheel scheme combining a damping ring and constrained damping. Then, it verifies the natural frequency and damping of the proposed wheel via 3D finite element modeling and modal analysis. Finally, in the laboratory, the wheel–rail relationship test setup is used to conduct tests on two types of wheel structures (nondamping wheel and damping wheel) under radial and axial excitation.

The damping wheel significantly reduces the corresponding radiated sound power level, with an overall noise reduction of approximately 10 dB or more, especially in the high-frequency region (around 3,150 Hz). The damping ring reduces high-frequency noise, while the constraint layer suppresses medium-low frequency noise. The combined structure outperforms single-component structures in the full frequency range, as it can suppress both high-frequency whistling noise and medium-low rolling noise.

The originality of this study lies in proposing a wheel scheme that combines a damping ring and constrained damping. The study’s value is to provide a theoretical basis and technical guidance for the engineering application of low-noise wheels in rail vehicles.

Rail freight is widely recognized for its economic and environmental advantages, yet it remains weakly integrated into firms’ supply chains, particularly in emerging economies. This study aims to investigate the conditions under which rail freight can be effectively integrated into multi-actor supply chains, with specific attention to the role of organizational coordination, information quality and artificial intelligence (AI) in shaping logistics integration outcomes.

The study draws on a quantitative survey of 3,185 stakeholders involved in rail-based and multimodal supply chains in Morocco. The data are analyzed using a combination of machine learning, deep learning and artificial neural network models. These methods are used not only to identify the main determinants of rail freight integration but also to capture non-linear relationships, interaction effects and potential integration trajectories that cannot be addressed through conventional linear models.

The results show that rail freight integration depends primarily on organizational and informational mechanisms rather than on infrastructure alone. Inter-organizational coordination and logistics information quality emerge as the most influential factors. AI contributes positively to rail freight integration, but its effect is conditional: AI tools significantly enhance integration only when adequate levels of coordination and information sharing are already in place. Scenario simulations further reveal that the strongest integration gains arise from the combined improvement of organizational practices and AI adoption.

This research contributes to the literature by shifting the focus from infrastructure-centered explanations toward a systemic understanding of rail freight integration. It is among the first studies to empirically combine machine learning, deep learning and artificial neural networks to analyze logistics integration in an emerging-economy context and to show that AI functions as a complementary and amplifying mechanism rather than a standalone solution.

The purpose of this study is to examine the determinants of modal shift intention from road freight transport to rail freight in Morocco, focusing on the perceived economic, energy and environmental performance of rail freight.

A quantitative survey was conducted among key freight transport stakeholders, including road carriers, industrial shippers, logistics operators and experts. A total of 483 valid questionnaires were collected. Measurement scales were derived from the literature and adapted to the Moroccan context. Data were analyzed using SPSS through descriptive statistics, reliability analysis, correlation tests and multiple linear regression.

The results indicate generally positive perceptions of rail freight, particularly regarding energy efficiency and environmental performance. All three perceived performance dimensions have a positive and significant effect on modal shift intention. Perceived energy performance emerges as the strongest predictor, followed by environmental impact, while economic performance shows a significant but more moderate influence. The model demonstrates strong explanatory power. Research limitations/implications – The study relies on perceptual data and a non-probabilistic sampling approach, which may limit the generalizability of the findings. Future research could integrate objective cost, energy and emission data; apply longitudinal designs or extend the model by incorporating institutional, infrastructural and policy-related variables to further explain rail freight adoption. Practical implications – The findings provide valuable insights for policymakers, rail operators and logistics managers by highlighting the key levers for promoting rail freight development. Strengthening rail energy efficiency, improving service reliability and enhancing intermodal integration can significantly increase stakeholders’ willingness to shift freight from road to rail. Social implications – By encouraging modal shift toward rail freight, the study supports broader societal objectives related to environmental protection, energy security and sustainable development. Increased use of rail freight can contribute to reduced greenhouse gas emissions, lower road congestion and improved quality of life in urban and industrial areas.

This study provides one of the first empirical investigations of rail freight modal shift determinants in Morocco, offering an integrated analysis of economic, energy and environmental factors within a single conceptual framework.