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This paper presents a new type of monorail rapid transit vehicle, which can operate in formation. In order to optimize the dynamic performance of the formation vehicles when passing through the small radius curve, this paper first analyzes the structure of the new monorail rapid transit vehicle, and establishes the vehicle dynamic model and multibody dynamics simulation model. Then the improved artificial potential field algorithm is used to build the formation vehicle operation controller. Finally, the dynamic performance evaluation index of the new monorail rapid transit formation vehicle is formulated, and the formation vehicle passing through the small radius curve scene is simulated. The simulation results show that the controller of the formation vehicle with dynamic optimization control can effectively optimize the load transfer coefficient of running wheels, unbalanced centrifugal acceleration and roll angle of vehicle body when passing through the curve. Through this control method, the dynamic performance of formation vehicles passing through small radius curve lines can be optimized. [ABSTRACT FROM AUTHOR]

For traditional predictor-corrector guidance algorithm for reentry glide vehicle, it cost a lot of time to obtain predicted flight range with a slow speed to iterate. In this paper, according to residual network (ResNet)'s block and dynamic model of vehicle, through analyzing the characteristics of predicted flight range with constraints, the flight range prediction block and flight range prediction neural network are designed, which can obtain the predicted range accurately and quickly; then aiming at the separation between guidance logic and no-fly zone avoidance logic, which may lead to guidance failure and increasing of the sign variation number of the bank angle, the no-fly zone crossrange and the no-fly zone mapping crossrange are proposed in this paper. According the repulsion force of artificial potential field, an adaptive crossrange corridor combining guidance logic and no-fly zone avoidance logic is proposed, and the convergence of the corridor is analyzed theoretically. Through simulation, the block number of flight range prediction network is determined firstly. By this method, the efficiency of lateral guidance can be improved. Then, through the simulation with the different no-fly zones under different disturbed conditions, the stability and validity of the guidance method are verified. Finally, compared with other predictor-corrector algorithms, the proposed method can realize guidance with less sign variation number of bank angle and better avoidance for no-fly zones. [ABSTRACT FROM AUTHOR]

A positioning system estimates the position and orientation of a vehicle. Autonomous driving systems plan paths and control the vehicle based on the information from the positioning system. Recently, methods of estimating the position in urban areas have been actively studied. In U-turn sections, which are common in urban areas, vehicles perform a rotation to reverse the direction of travel. Through these sections, drivers can reduce the travel distance and save time but with a high risk of an accident. Despite there being a need for the development of autonomous driving schemes for U-turn sections, the existing research is limited. This study proposes an interacting multiple model (IMM) filter-based position estimation algorithm for urban U-turn sections. To reflect the dynamic characteristics of a vehicle during U-turn maneuvers, a multiple vehicle model was used. This model includes kinematic and dynamic vehicle models. The state estimates of the vehicle model and gyroscope are combined using an IMM filter. The position estimation algorithm developed in this study is verified via experiments. The experimental results indicate that, during urban U-turn maneuvers, the position estimation accuracy of the IMM filter-based algorithm is improved than that of the single vehicle model. [ABSTRACT FROM AUTHOR]

The supercavitating vehicle is a new generation of high-speed underwater vehicles enveloped by a large bubble of gas or vapor (i.e., a supercavity) to reduce navigation resistance by an order of magnitude, except for the head and tail. However, due to the limited hydrodynamic forces, it is difficult to ensure stable motion. The overall shape of the vehicle is not only the critical factor to ensure a suitable relative position between the vehicle and its supercavity for stable motion, but also directly affects the ease of generation and development of the supercavity. Therefore, this study focuses on the characteristic parameters of the overall shape of the vehicle and first establishes a multi-objective optimization model based on the dynamic model of the supercavitating vehicle with the incipient supercavitation number and the vehicle volume as the optimization objectives. Then, given the relatively good global, robust and universal characteristics of the adaptive genetic algorithm compared to other algorithms, a multi-objective optimization algorithm is developed and improved using the subsection optimization method for the main optimization variable. The characteristic parameters of the overall shapes are optimized for natural and ventilated supercavitating vehicles using the algorithm based on the multi-objective optimization model so that it is easier to create a supercavity under the conditions of the same flow and force equilibrium and the vehicle has a larger volume. By optimizing the vehicles under different navigation depths and slenderness ratios, the design rules for the characteristic parameters of the overall shape and the control surface parameters are obtained based on the optimization objectives, and the motion state and hydrodynamic characteristics of the optimized vehicles are revealed. • A multi-objective optimization model is established for the SCAV's overall shape. • An adaptive multi-objective optimization algorithm is improved and developed. • Natural and ventilated SCAVs' overall shapes are optimized to achieve the optimal solution sets. • Design rules for the SCAV's overall shape and control surface parameters are obtained. • Motion state and hydrodynamic characteristics of the optimized SCAVs are revealed. [ABSTRACT FROM AUTHOR]

• The paper presents a simple, reliable and fast dynamics model of off-road track vehicle. • The numerical model was formulated by a new method – DBD (Discrete Body Dynamics). • The proposed method was demonstrated using an M113 track vehicle. • The time computation of the new code was faster compared with that obtained from commercial Multi-Body Dynamic programs. • The method is simple enough to be used in prediction of trafficability for off-road applications. The paper presents a simple, fast, and reliable dynamic model for an off-road track vehicle operating on terrain with obstacles. The method has been proven previously for wheeled-vehicle formulation. The model is based on a discrete body dynamics (DBD) method, which leads to simplistic linear decoupled motion equations. In this method, joints and bodies with relatively small mass are replaced with stiff springs and dampers, eliminating the system's constraints and reducing the number of system bodies; this is important for accelerating the simulation runtime of the track vehicle model. The track in this approach is based on modeling each link as a point-mass. Two consecutive links are connected by stiff springs and dampers. This approach reduces the calculation time and increases system stability. The track–soil interaction was modeled using Bekker's and Janosi's formulation (Bekker, 1956; Hanamoto and Janosi, 1961). Specific soil properties were obtained for each link–soil interaction from soil classification and GIS. The link–ground contact was determined from topographic surface and adjustment of the force and direction acting on the track. The results of the simulation using the DBD method were compared with Siemens' VL commercial multibody dynamics program and with experiments reported in the literature. Results using the proposed method were found to be similar to the commercial program based on published experiments. The solution runtimes obtained for unpaved soil were two orders faster with the DBD method compared with the Siemens' VL program. The model was written as an independent software infrastructure, enabling easy integration with any other software component, such as a control system. The algorithm is in a suitable form for parallel processing calculation to speed up the runtime simulation close to real-time. [ABSTRACT FROM AUTHOR]