Jul 2026· International Conference on Control, Decision and Information Technologies· pp. 3156-3160· 0 citations· 19 references
Abstract
This paper proposes a novel level crossing (LC) control architecture designed for railway systems operating under ERTMS Levels 2 and 3. The approach aims to prevent identified hazardous scenarios and to facilitate the integration of LCs into the ERTMS/ETCS framework by moving from passive control schemes to a supervised, communication-based paradigm. The proposed strategy specifically addresses two critical issues: excessive level crossing closure time (ELCCT) and overly short opening durations (OSOD), both of which may lead to unsafe road user behavior. A formal behavioral model based on Time Petri Nets (TPN) is developed using a modular approach to represent the interactions between LC control and railway traffic. The model is enriched with observers to express safety requirements as temporal logic properties, which are verified using model-checking techniques with the TINA tool. The results show that the proposed architecture effectively prevents the considered risky scenarios.
This framework proves an autonomous decision-making system that organically links inspection data with maintenance regulations by transforming static, manual-labor-centered maintenance workflows into intelligent automated models and increases the efficiency of railway infrastructure management while providing a scalable technical foundation for overall asset management of future smart-city infrastructure.
Minjae Jeon, Yong-Gyun Kim, Seok-Han Kim· Smart Cities· 0 citations
A refined stochastic model-based evaluation framework is presented to aid in comparing various IPS redundant architectures with respect to dependability characteristics, mainly focusing on reliability and availability metrics.
S. Chiaradonna, Felicita Di Giandomenico, G. Masetti· European Transport Research...· 0 citations
This project advances connected vehicle applications by developing and testing an enhanced RampCast system, a comprehensive traffic management system using C-V2X technology for Indiana highways. The system features a dual-mode architecture integrating both short-range (PC5) and long-range cellular (Uu) Cellular Vehicle-to-Everything (C-V2X) communication pathways, utilizing commercial-grade Cohda MK6 hardware and adhering to SAE J2735 standards to ensure interoperability. A key innovation is the integration of an AI-based prioritization framework, which leverages a large language model to enhance the contextual relevance of traffic messages. This AI system introduces two intelligent agents: one to dynamically estimate the appropriate display distance for an event based on its severity, and another to prioritize the order of messages based on urgency and potential driver impact. Field tests conducted on I-65 and I-70 in Indianapolis validated the system’s hybrid design. Results confirmed that the PC5 link provides very low latency (around 25 ms), ideal for time-critical alerts, while the Uu link ensures highly reliable coverage in complex environments, albeit with higher latency (around 45 ms). The AI framework was successfully shown to reorder and present messages based on real-time context, improving the clarity and usefulness of information provided to the driver. These findings support a hybrid C-V2X architecture as a robust model for future smart highway deployments.
Abin Mathew, A. Sundar, Juntong Peng et al.· 0 citations
The digitalisation of operational train commands represents a major step in the transformation of railway operations and fundamentally changes safety-critical communication between dispatchers and train drivers. Traditionally, commands are issued through written or verbal procedures based on strictly standardised rules, ensuring clarity and reliability, particularly in disruption scenarios. With the introduction of digital train commands, these procedures are increasingly replaced by interface-based transmission and acknowledgement mechanisms, raising new questions regarding usability, comprehensibility, and human–system interaction.This paper presents a human factors–oriented methodological framework for the systematic evaluation of digital train commands in railway operations. The focus lies on research design and evaluation methods suitable for early deployment and transition phases, rather than on operational performance outcomes. The proposed approach combines simulator-based studies, task and process analyses, semi-structured interviews, questionnaires, mockups, and thinking-aloud techniques to investigate cognitive workload, acceptance, and safety-critical communication under realistic operating conditions. Particular attention is given to transitional environments in which traditional and digital command procedures coexist, potentially increasing cognitive demands and the risk of human error.The framework examines how factors such as stress, time pressure, prior experience, and interaction design influence user behaviour and trust in digital acknowledgement mechanisms. By systematically addressing both technical and human aspects, the approach supports early identification of usability issues and interaction risks before large-scale implementation. The paper contributes a transferable methodological basis for evaluating digital command systems in the railway domain and other safety-critical transportation contexts, highlighting the need to integrate human factors alongside technological innovation to maintain established safety standards.
A demand-driven signal control strategy is developed to allocate green time based on real-time vehicle demand, eliminating wasted signal phases and providing a scalable and intelligent solution for modern smart city traffic systems.
Friday Idakwo David, S. T. Apeh, Oduware Okosun· E3S Web of Conferences· 0 citations
Railway level crossings remain a persistent source of accidents and fatalities on mixed road-rail networks, particularly where crossings are unmanned or rely on manual gate operation. This paper presents the design, structural validation, and prototype implementation of an automated railway barricade in which a Programmable Logic Controller (PLC) drives an underground rack-and-pinion mechanism to raise and lower a physical barrier in response to sensor-detected train movement. The underground placement minimizes visual obstruction relative to conventional above-ground boom barriers while a robust mechanical drive is intended to withstand repeated, high-cycle outdoor operation. A structural analysis using Finite Element Analysis (FEA) is used to validate the mechanical integrity of the rack-and-pinion drive under expected loading, and shaft design calculations confirm an adequate safety margin. A fabricated prototype demonstrates the automation cycle end-to-end, including a manual push-button override for fail-safe operation. To situate the contribution, a focused review of thirteen directly relevant studies retrieved from a bibliographic export is presented; it indicates that existing automated level-crossing work concentrates on sensing and control logic, while structurally validated mechanical actuator design for the barrier itself is comparatively under-addressed. The proposed system is offered as a scalable, low-cost step toward reducing manual dependency and human error at level crossings.
Akhil A. Deshpande, Vinayak V. Kulkarni, Vaidehi P. Deshpande et al.· International journal of com...· 0 citations