Risk Assessment of Rollover and Skidding due to Pavement Roughness and Differential Settlement for Enhancing Transportation Safety

In this paper, a closed-loop simulation of vehicle dynamics in CarSim is utilized as surrogate measures to study the effect of pavement roughness and differential settlement on risk of vehicle rollover and skidding. It is found that the influence of pavement roughness on vehicle rollover is significant and the influence of pavement roughness on vehicle skidding is insignificant. The influence of pavement roughness of grade A and B on safety margin of vehicle rollover can be negligible. Pavement roughness of grade C and D significantly reduces the safety margin of vehicle rollover. A 5 cm settlement difference on pavement reduces the safety margin of vehicle skidding on a good road. When the settlement difference is 5 cm, the vehicle rollover and skidding are greatly affected by the lane-changing speed. It provides an effective and general method based on vehicle dynamics for studying transportation safety as well as for setting up criteria for pavement maintenance.

Vehicle rollover warning system based on TTR method with Inertial Measurement

This paper presents a theoretical and experimental study conducted on the rollover warning of wheeled off-road operating vehicles. The time to rollover (TTR) warning algorithm was studied with real-time vehicle roll angle and roll angle velocity as the input variables, and lateral load transfer ratio (LTR) was used as the rollover determination index. Subsequently, a vehicle dynamics model was built using CarSim software, and a warning algorithm was established in the MATLAB/Simulink environment. The rollover joint simulation in CarSim and MATLAB/Simulink was conducted under typical working conditions. Finally, combined with inertial measurements, a rollover warning system was independently developed. In addition, the rollover warning system was installed on a light forest firefighting truck to verify the feasibility of the system via a real vehicle experiment, and the law of vehicle rollover motion was also studied. The serpentine experiment and steady-state rotation experiment were conducted. The experimental results showed that at identical front-wheel steering angles, the roll angle and lateral acceleration increased with an increase in the vehicle speed. Furthermore, for identical vehicle speeds, the roll angle and lateral acceleration of the vehicle increased with an increase in the front-wheel steering angle. The dangerous vehicle speed was 50 km/h in the serpentine condition and 40 km/h in the steady-state rotation condition. The risk trend and alarm signal obtained by the rollover warning system were consistent with the actual situation. Thus, this can assist drivers in judging the rollover risk and effectively improve the active safety of special vehicles. Furthermore, it also provides a reference for further research on active rollover control technology of special vehicles.

Research on Electric Vehicle Rollover Prevention System Based on Motor Speed Control

Vehicle driving safety is an important performance indicator for vehicles, and there is still much room for development in the active safety control of electric vehicles. A vehicle rollover is an important road traffic safety problem, as rollover accidents cause serious casualties and huge economic losses. It is very easy for vehicles in high-speed sharp turns or high-speed overtaking to roll over; in order to improve the vehicle in these conditions with the anti-rollover stability, this study proposed a real-time motor control strategy, mainly through the acquisition of vehicle attitude data and the use of multi-sensor fusion on the vehicle running state for real time. The lateral load transfer rate was used as the vehicle rollover evaluation index, and the test results indicate that when the real-time rollover index exceeds the set limit safety threshold, the motor speed is reduced through active control so that the vehicle avoids rollover accidents, or the risk of rollover is reduced. The STM32F103RET6 was used as the main chip for hardware design, control board fabrication, control program software design, and joint testing of software and hardware. The tests and data analysis prove that the motor control strategy is reliable in real time and can significantly improve the active safety of electric vehicles.

Rollover Prevention and Motion Planning for an Intelligent Heavy Truck

It is very necessary for an intelligent heavy truck to have the ability to prevent rollover independently. However, it was rarely considered in intelligent vehicle motion planning. To improve rollover stability, a motion planning strategy with autonomous anti rollover ability for an intelligent heavy truck is put forward in this paper. Considering the influence of unsprung mass in the front axle and the rear axle and the body roll stiffness on vehicle rollover stability, a rollover dynamics model is built for the intelligent heavy truck. From the model, a novel rollover index is derived to evaluate vehicle rollover risk accurately, and a model predictive control algorithm is applicated to design the motion planning strategy for the intelligent heavy truck, which integrates the vehicle rollover stability, the artificial potential field for the obstacle avoidance, the path tracking and vehicle dynamics constrains. Then, the optimal path is obtained to meet the requirements that the intelligent heavy truck can avoid obstacles and drive stably without rollover. In addition, three typical scenarios are designed to numerically simulate the dynamic performance of the intelligent heavy truck. The results show that the proposed motion planning strategy can avoid collisions and improve vehicle rollover stability effectively even under the worst driving scenarios.

Model-Free Adaptive Control for Tank Truck Rollover Stabilization

Influenced by lateral liquid sloshing in partially filled tanks, tank vehicles are apt to encounter with rollover accidents. Due to its strong nonlinearity and loading state uncertainty, it has great challenges in tank vehicle active control. Based on the model-free adaptive control (MFAC) theory, the roll stability control problem of tank trucks with different tank shapes and liquid fill percentages is explored. First, tank trucks equipped with cylinder or elliptical cylinder tanks are modelled, and vehicle dynamics is analyzed. This dynamic model is used to provide I/O data in the controlled system. Next, the control objective of tank vehicle rollover stabilization is analyzed and the controlled variable is selected. Subsequently, differential braking and active front steering controller are designed by MFAC algorithm. Finally, the effectiveness of the designed controllers is verified by simulation, and difference between the controllers is analyzed. The controller designed by MFAC algorithm is proven to be adaptive to vehicle loading and driving states. The controlled system has great robustness.

Calculation of the Roadside Clear Zone Width along Highways Based on the Safe Slope

International crash data indicate that roadside characteristics contribute to more than half of all roadside accidents involving serious injury or death. Therefore, research on roadside safety is urgently needed. Based on the vehicle departure speed, pavement height (i.e., the difference between pavement elevation and ground elevation), slope gradient, and horizontal curve radius, this study uses PC-Crash simulation software to carry out tests of trucks and cars exiting a road. A chi-squared automatic interaction detection (CHAID) decision tree is used to explore the causative mechanism of vehicle rollover, and the concept of a “safe slope” to ensure that vehicles do not roll over is proposed. Aiming at straight and curved sections, discriminant functions of vehicle rollover and nonrollover are fitted through Bayesian discriminant analysis, and safe slope calculation models for trucks and cars are then constructed. Based on the obtained safe slope models, calculation methods for the safe slope and the roadside clear zone width involving different traffic compositions are proposed by calibrating the lateral distance from the final position of nonrollover vehicles to the road edge. The results show that the factors affecting vehicle rollover are, in descending order of importance, the slope gradient, pavement height, vehicle type, departure speed, and horizontal curve radius. For a section with a large proportion of cars, the slope gradient should not be steeper than 1:3.5. The horizontal curve radius should not be less than 600 m for a section with a large proportion of trucks and a slope gradient steeper than 1:3.5 or shallower than 1:2.5. Additionally, for a section with a pavement higher than 0.5 m and a slope gradient steeper than 1:2.5, the operating speed limit should be lower than 60 km/h. These research results have theoretical value and practical significance to improve the driving safety level and reducing the risk of roadside accidents.