# A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles
## 6 Comparative Analysis and Future Directions  
### Comparisons of Roll Stability Control Between Road and Off-Road Vehicles  
There are significant differences between on-road and off-road vehicles in terms of vehicle roll state monitoring, rollover warning, and stability control. These differences primarily stem from variations in their operating environments, working conditions, and control requirements. Both types use IMUs, gyroscopes, and accelerometers to monitor parameters like the roll angle, lateral acceleration, and load transfer ratio [68, 122, 144]. However, on-road vehicle state estimation assumes stable tire-road contact and minimal load variation, enabling effective use of Kalman-based filtering methods [61]. In contrast, off-road vehicles operate in rugged, uneven terrains with variable loads and low-frequency vibrations, posing greater challenges. To address these, their systems often integrate terrain slope sensors, LiDAR, and GNSS to enhance perception and accuracy [145, 146, 147, 148]. Additionally, due to frequent changes in the center of gravity--such as when different implements are mounted--off-road vehicles require higher estimation thresholds and adaptive algorithms to maintain monitoring accuracy [149, 150]. Rollover warning systems for on-road vehicles are primarily based on the vehicle yaw motion, speed, and steering conditions. Methods such as the load transfer ratio and static stability factor are commonly used to assess rollover risks [76, 81]. The ESP typically utilizes real-time data, such as the vehicle speed, steering angle, and lateral acceleration, to predict potential instability situations and intervene when necessary [4, 151]. In contrast, rollover warning for off-road vehicles requires the integration of more complex environmental variables. While operating vehicles typically have lower speeds, they may experience significant slopes. Even at static or low speeds, these vehicles may roll over due to uneven terrain or load variations. Therefore, rollover warning systems for off-road vehicles must integrate real-time terrain information, changes in the vehicle's center of gravity, and tire-ground contact states [39]. In terms of roll stability control, on-road and off-road vehicles employ significantly different control strategies, due to their distinct working environments and dynamic characteristics. On-road vehicles primarily rely on ESPs, active suspension systems, and active steering systems to control roll stability. The control objective of these systems is to improve vehicle stability while maintaining handling performance, and to provide real-time intervention under extreme driving conditions, such as emergency lane changes and high-speed cornering [152]. Off-road vehicles, with their lower speeds, typically face rollover risks primarily due to terrain undulations and load distribution changes. As such, roll stability control for off-road vehicles is more dependent on active steering, center of gravity adjustment, and hydraulic suspension systems [59, 136]. For example, tractors often use a hydraulic suspension system with coordinated control to optimize vehicle posture by adjusting the suspension stiffness and tilt angle. Slope-working machines may use an automatic leveling system that adjusts track width or vehicle posture to maintain stability [13]. Additionally, off-road vehicle roll control systems generally require higher robustness and environmental adaptability to handle complex disturbances in extreme conditions. For instance, some advanced agricultural machines have begun to employ electro-hydraulic servo suspension control, integrated with intelligent perception and adaptive control algorithms, to enhance adaptability to complex terrain. In summary, on-road vehicles focus on real-time stability control under high-dynamic driving conditions, relying on an ESP, active suspension, and steering control to enhance driving maneuverability. Off-road vehicles, however, face more complex terrain and load variations.