Keywords
Advanced Driver Assistance Systems (ADAS)
Digital Twins
V2X technologies
Condition-Based Maintenance (CBM)
Sensor Fusion
FRACAS
How to Cite
Abstract
This paper aims to substantiate a deterministic, engineering-first approach to incident prevention in industrial logistics and freight transport, where heavy vehicles, pedestrians, and dense maneuvering zones create high-consequence risk. The study employs a systems-engineering and cybernetic risk-management approach, using comparative analysis of safety architectures (from passive barriers to integrated digital ecosystems), cognitive-ergonomics reasoning to address warning effectiveness and alarm fatigue, and reliability engineering methods (P–F interval logic, FRACAS feedback, and condition-based maintenance) to connect operations with predictive control. A 15-year operational retrospective from an enterprise fleet (350 units of specialized heavy machinery) is used to assess changes in near-miss dynamics after deploying the proposed controls. Results indicate that coupling smart infrastructure (flow segregation and proximity enforcement via UWB/LiDAR/radar and dynamic projection), vehicle-level assistance (ADAS, sensor fusion, and V2X-type messaging), and predictive diagnostics (IoT monitoring and digital-twin-supported anomaly detection) reduces exposure to conflict scenarios while improving operational continuity. Scientific novelty lies in the author’s proprietary “Chuikov’s Multi-Contour Safety System” as a unified interaction algorithm across the man–machine–environment triad, including a haptic feedback protocol (seat/steering vibration) that replaces non-actionable acoustic alarms in high-noise environments. The practical value is a transferable technical roadmap for designing, implementing, and auditing safety controls at industrial sites, enabling safety to be managed as an engineered process rather than a probabilistic outcome. The paper notes deployment constraints (cost, legacy integration, and AI liability) and indicates directions for further research.
References
Al‑Hadhrami, S., Al‑Salman, A., Al‑Khalifa, H. S., Alarifi, A., Alnafessah, A., Alsaleh, M., & Al‑Ammar, M. A. (2014). Ultra wideband positioning: An analytical study of emerging technologies. In Proceedings of the 8th International Conference on Sensor Technologies and Applications (SENSORCOMM 2014) (pp. 66–74). IARIA. https://lnk.ua/lx3HEbCOW
Borgia, E. (2014). The Internet of Things Vision: Key Features, Applications and Open Issues. Computer Communications, (54), 1–31. http://dx.doi.org/10.1016/j.comcom.2014.09.008
Dey, K. C., Rayamajhi, A., Chowdhury, M., Bhavsar, P., & Martin, J. (2016). Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication in a heterogeneous wireless network – Performance evaluation. Transportation Research Part C: Emerging Technologies, (68), 168–184. https://doi.org/10.1016/j.trc.2016.03.008
Dhillon, B. S. (2012). Safety and Human Error in Engineering Systems (1st ed.). CRC Press. https://doi.org/10.1201/b12534
Fonseca, T., & Ferreira, S. (2025). Monitoring Technologies for Truck Drivers: A Systematic Review of Safety and Driving Behavior. Applied Sciences, 15(12), 6513. https://doi.org/10.3390/app15126513
Hollnagel, E. (2014). Safety-I and Safety-II: The Past and Future of Safety Management (1st ed.). CRC Press. https://doi.org/10.1201/9781315607511
Jardine, A.K.S., Lin, D. and Banjevic, D. (2006) A Review on Machinery Diagnostics and Prognostics Implementing Condition-Based Maintenance. Mechanical Systems and Signal Processing, (20), 1483–1510. http://dx.doi.org/10.1016/j.ymssp.2005.09.012
Kletz, T. (2020). An engineer’s view of human error. Taylor & Francis. https://doi.org/10.1201/9781003072072-2
Lee, J., Bagheri, B. & Kao, H.A. (2015) A Cyber-Physical Systems Architecture for Industry 4.0-Based Manufacturing Systems. Manufacturing Letters, (3), 18–23. https://doi.org/10.1016/j.mfglet.2014.12.001
Lohani, M., Payne, B. R., & Strayer, D. L. (2019). A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving. Frontiers in human neuroscience, (13), 57. https://doi.org/10.3389/fnhum.2019.00057
Manzoor, B., Charef, R., Antwi-Afari, M. F., Alotaibi, K. S., & Harirchian, E. (2025). Revolutionizing Construction Safety: Unveiling the Digital Potential of Building Information Modeling (BIM). Buildings, 15(5), 828. https://doi.org/10.3390/buildings15050828
Michels, E. A. M., Gilbert, S., Koval, I., & Wekenborg, M. K. (2025). Alarm fatigue in healthcare: a scoping review of definitions, influencing factors, and mitigation strategies. BMC nursing, 24(1), 664. https://doi.org/10.1186/s12912-025-03369-2
Moubray, J. (1997). Reliability Centered Maintenance. Butterworth-Heinemann, Oxford.
Ochoa-de-Eribe-Landaberea, A., Zamora-Cadenas, L., & Velez, I. (2024). Untethered Ultra-Wideband-Based Real-Time Locating System for Road-Worker Safety. Sensors, 24(8), 2391. https://doi.org/10.3390/s24082391
Qian, H., Wang, M., Zhu, M., & Wang, H. (2025). A Review of Multi-Sensor Fusion in Autonomous Driving. Sensors, 25(19), 6033. https://doi.org/10.3390/s25196033
Rasheed, A., San, O., & Kvamsdal, T. (2019). Digital Twin: Values, Challenges and Enablers from a Modeling Perspective. IEEE Access, (8), 21980–22012. https://doi.org/10.1109/ACCESS.2020.2970143
Shaout, A., Colella, D., & Awad, S. (2011). Advanced driver assistance systems - Past, present and future. In Proceedings of the Seventh International Computer Engineering Conference (ICENCO 2011) (pp. 72–82). IEEE. https://doi.org/10.1109/ICENCO.2011.6153935
Smith, A. M., & Hinchcliffe, G. R. (2004). RCM: Gateway to World Class Maintenance. Elsevier.
Smith, D. J., & Simpson, K. G. L. (2020). Safety Critical Systems Handbook: A Straightforward Guide to Functional Safety, IEC 61508 (2010 Edition) and Related Standards (5th ed.). Elsevier. https://doi.org/10.1016/C2010-0-65791-9
Żuchowicz, P., & Lewczuk, K. (2025). Leveraging Immersive Technologies for Safety Evaluation in Forklift Operations. Applied Sciences, 15(20), 11048. https://doi.org/10.3390/app152011048
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright (c) 2025 Stanislav Chuikov