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Sensor-based tractor rollover risk reduction: a review of stability indices and smart prevention systems
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: 2026 ASABE Annual International Meeting 2601564.(doi:10.13031/aim.202601564)Authors: Danilo Monarca, Prof., Maurizio Cutini, Dr., Domenico Pessina, Prof., Lavinia Eleonora Galli, Dr., Fabrizio Marra, Riccardo Colella, Elisa Cioccolo, Giorgia Di Domenico, Pierluigi Rossi, Eyerusalem Tesfay Gereziher, Leonardo Vita
Keywords: Agricultural tractors; Rollover prevention; Stability index; Sensor-based safety; Warning systems; Safety.
Abstract. Tractor rollover represents a serious safety issue in agricultural activities and recent regulatory updates in the European Union (EU) Machinery Regulation 2023/1230, even it is not applicable to tractor, have reinforced the requirements on broader arguments such as regarding safety control functions, robustness against faults and reasonably foreseeable misuse, and resilience against intentional or accidental software modifications that could result in hazardous work conditions. In this context, rollover risk reduction tools could rely on sensors and other digital solutions, but these are still fragmented across vehicle dynamics, sensing, human factors, safety culture and functional safety. This paper presents a PRISMA scoping review focused on sensor-based methodologies for rollover prevention and post-event response on agricultural tractors and comparable off-road machines. To better illustrate the key aspects of each methodology, authors have divided technologies into four different categories: (i) on-board risk-awareness and perception of terrain and obstacles; (ii) risk metrics and prediction using stability indices and lateral load transfer proxies; (iii) connected warning, logging, and emergency notification architectures designed for high availability and traceability; and (iv) wearable and in-cab sensing to support safer behavior, including smart seatbelt-use enabling and operator monitoring with context-aware alerts. Representative work includes portable device implementations that fuse data to estimate roll or pitch, compute stability indices and trigger warnings, including near-miss detection. This review also covers artificial intelligence (AI) approaches for monitoring safety-relevant operator actions in the cab such as camera-based posture or behavior recognition with high reported classification accuracy in controlled datasets. Wearable technologies have also been analyzed to foresee their use as an enabling layer for ergonomic support and real-world safety feedback, while highlighting adoption constraints related to comfort and long-term usability. Across all classes validation methods were collected and compliance, safety or design requirements were assessed to verify fault tolerability, limits of safety functions, logging, and cybersecurity functions to align with EU 2023/1230 regulation requirements in control-system provisions and functional-safety practice for off-road machinery control systems with a particular focus on ISO 19014 methodology regarding certifiable safety functions. The review highlights that gaps exist regarding shared validation protocols and the need to account for changes in mass distributions during operations, alongside the promotion of the use of seatbelts. Future systems should also include verifiable fail-safe behavior, event logging, and protection against software or cybersecurity-related faults.
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