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The probability of electric vehicle rollover accident can be effectively reduced by shortening the prediction time interval and improving the prediction accuracy. Based on a multilayer neural network, an improved time-to-rollover method is presented in this paper. Firstly, the force model of vehicle rollover is established and analyzed where the structure and mass of a battery box have an important influence on the occurrence of rollover. Then, the rollover indexes considering hyperparameters are divided into five categories, and the multi-layer neural network is used to simplify the algorithm structure of the time to rollover, and quickly calculate the operating state parameters with a variation step size in real time. Finally, the influence of the hyperparameters on the prediction results of neural network is studied, and higher efficiency is obtained by comparing with traditional methods.

To improve rollover prevention and rollover warning systems, indicators for detecting rollover risks are extremely important. Vehicle rollover accidents occur in one of two ways: tripped and untripped rollovers. For detecting tripped rollovers, the traditional rollover index is ineffective; most precise rollover indicators depend on dynamic models that must identify all the parameters for computations. In this study, we focused on exploring a new index for detecting tripped and untripped rollovers using a neural network (NN). Four types of NNs, i.e., FNN, Tanh, long short-term memory, and gated recurrent unit (GRU), were examined to develop models for estimating rollover indices. The results demonstrated that the GRU and large Tanh network are the most suitable NNs for untripped and tripped rollover prediction, respectively. Moreover, the untripped rollover prediction model having a small GRU network could precisely anticipate the trend of the untripped rollover indicators for up to 0.2 s in advance. Moreover, the created tripped rollover anticipation model with a large Tanh network could precisely forecast the trend of the tripped rollover index up to 0.5 s in advance. Based on these results, rollover prediction in future can be advantageous for rollover prevention and warning systems.

Frequent product introductions emphasize the importance of product rollover strategies. With single rollover, when a new product is introduced, the old product is phased out from the market. With dual rollover, the old product remains in the market along with the new product. Anticipating the introduction of the new product and the potential markdown of the old product, strategic customers may delay their purchases. We study the interaction between product rollover strategies and strategic customer purchasing behavior and find that single rollover is more valuable when the new product's innovation is low and the number of strategic customers is high. Interestingly and counter to intuition, the firm may have to charge a lower price for the old product as well as receive a lower profit with a higher value disposal (outside) option for the old product under single rollover. Facing a market composed of both strategic and myopic customers, the firm does not necessarily reduce the stocking level as more myopic customers become strategic. This paper was accepted by Yossi Aviv, operations management.

The rollover of road vehicles is one of the most serious problems related to transportation safety. In this article, a novel rollover prevention control system composed of rollover warning and integrated chassis control algorithm is proposed. First, a conventional time-to-rollover warning algorithm was presented based on the 3-degree of freedom vehicle model. In order to improve the precision of vehicle rollover prediction, a back-propagation neural network was adopted to regulate time to rollover online by considering multi-state parameters of the vehicle. Second, a rollover prevention algorithm based on integrated chassis control was investigated, where the active front steering and the active yaw moment control were coordinated by model predictive control methodology. Finally, the algorithms were evaluated under several typical maneuvers utilizing MATLAB/Simulink and Carsim co-simulation. The results show that the proposed neural network time-to-rollover metrics can be a good measure of the danger of rollover, and the roll stability of the simulated vehicle is improved significantly with reduced side slip angle and yaw rate by the proposed integrated chassis control rollover prevention system.

This article is devoted to modelling results of pipe-layers loading during the major overhaul of main pipeline linear sections. Basic loads affecting the pipe-layer in operation are considered in this research. The results obtained prove that at the major overhaul of the main pipeline linear section, efforts of hoisting the pipe constitute only 60% of overall process duty, 20-40% are variable and depend on the weight of technological vehicles in operation. The suggested model of loads calculation allows to improve accuracy of loads calculation, affecting the pipe-layer during the technological process which, in its turn, allows both to select appropriate vehicles for linear pipeline section repair and to increase operational safety by forecasting possible conditions of pipe-layers rollover.

In off-road environments, the lateral rollover stability of articulated unmanned rollers (URs) is critical to ensure operational safety and efficiency. This paper introduces the concept of a rollover energy barrier (REB), a symmetry-based metric that quantifies the energy margin between the current state and the critical rollover threshold of articulated rollers. URs exhibit dynamic asymmetry due to their hydraulic steering systems, which differ significantly from traditional passenger vehicles. To address these challenges, we propose a hierarchical control framework inspired by the principles of dynamic symmetry. This framework integrates Nonlinear Model Predictive Control (NMPC) and Active Disturbance Rejection Control (ADRC): NMPC is used for trajectory planning by incorporating the REB into the cost function, ensuring rollover stability, while ADRC compensates for dynamic asymmetries, model uncertainties, and external disturbances during trajectory tracking. Simulation and experimental results validate the effectiveness of the proposed control strategy in enhancing the rollover stability and tracking performance of the URs under off-road conditions.

Purpose Rollover of a semi-trailer vehicle is a common type of instability that can occur when turning at high speeds on roads with high adhesion coefficients, or when colliding with other vehicles. In order to design effective early warning and anti-roll control systems, it is important to accurately determine the rollover thresholds. This research aims to determine the dynamic rollover thresholds of a tractor semi-trailer vehicle during turning maneuvers based on a dynamic model. Methods A full dynamic model of a semi-trailer vehicle with 48 degrees of freedom has been established using the Multibody Dynamic analysis method and Newton Euler equations. The non-linear tire model is used to determine tire-road interaction forces when affected by tire-road deformation, adhesion coefficient of road, road wheel angle, and vehicle velocity. To validate the accuracy of the model, experiments were conducted on a road with a radius of 40 m. The verified model was then used to investigate the vehicle’s dynamics during turning maneuvers at velocities ranging from 40 to 80 km/h and the magnitude of steering wheel angles ranging from 12.5 to 300 deg. Results The results show the combined impact of the magnitude of the steering wheel angle and initial velocity on the rollover condition of the tractor semi-trailer vehicle. The 3D maps and table of maximum values for load transfer ratio and lateral acceleration of the vehicle bodies reveal the regions of roll stability and rollover. The dynamic rollover instability threshold for the tractor ranges from 4.382 to 4.838 m/s 2 , while that of the semi-trailer ranges from 4.022 to 4.433 m/s 2 . Conclusions The article presents a method for determining the dynamic rollover threshold of tractor semi-trailer vehicles based on a full dynamic model. The dynamics rollover thresholds are the boundaries that separate the rollover region from the stability region of the lateral acceleration of the tractor and semi-trailer bodies. The research findings in this article serve as a basis for determining input parameters for early warning and anti-rollover control systems in tractor semi-trailer vehicles. These results will be further discussed in the next articles.

What makes an asset a “safe” asset? We study a model where two countries each issue sovereign bonds to satisfy investors’ safe asset demands. The countries differ in the float of their bonds and the fundamental resources available to rollover debts. A sovereign’s debt is safer if its fundamentals are strong relative to other possible safe assets, not merely strong on an absolute basis. If demand for safe assets is high, a large float enhances safety through a market depth benefit. If demand for safe assets is low, then large debt size is a negative as rollover risk looms large.

Although the probability of a rollover accident is lower than that of other forms of collision, rollover is a serious accident that can break the symmetry of the vehicle and cause serious loss of life and property. There are many factors affecting rollovers, such as the environment, the vehicle, and the driving control. A coach comprises a complex dynamic system; as such, the accuracy and rationality of the used mathematical model are decisive in the study of coach rollover warning and control. By analogy with the modeling method of an automobile collision accident, the general process of a coach rollover accident is analyzed in this study in combination with the contact form and freedom of motion characteristic of the coach body and external environment. According to the principle of conservation of energy, the mathematical models of critical rollover impact force in a collision between vehicles and obstacles and in a collision between two vehicles are established, allowing for analysis of the relationships between the critical tripped rollover impact forces required for a 90° rollover and the continuous action time and collision point height. During the collision between the vehicle and the obstacle, the occurrence of a vehicle rollover is related not only to the impact force in the collision process but also to the collision duration time. Even if the impact force is relatively small, the collision lasts long enough that a second collision may occur until the vehicle rolls over. In the process of a two-vehicle collision, the critical rollover impact force is not only related to the vehicle mass but also to the vehicle wheelbase and the height of the collision point. Based on the law of conservation of momentum, the mathematic models of 90-degree rollover and 180-degree rollover are established, and the critical rollover velocities are calculated. The purpose of this study is to provide reference and guidance for the research methods of vehicle rollover stability and anti-rollover control in the intelligent vehicle era.