Vehicle Maneuvers Research Articles

Unsteady Aeroelastic Characterization and Scaling Relations of Flexible Membrane Wings

We present a numerical study to characterize nonlinear unsteady aeroelastic interactions of two-dimensional flexible wings at high angles of attack. The coupled fluid–flexible wing system is solved by a body-fitted variational aeroelastic solver based on the fully coupled Navier–Stokes and nonlinear structural equations. Using the coupled fluid–structure analysis, this study is aimed to provide physical insight and correlations for the aeroelastic behavior of flexible wings in the parameter space of the angle of attack and the aeroelastic number. The phase diagrams of the aerodynamic performance are established to obtain the envelope curves of the optimal performance and determine the transition line of the drag variation. The effects of the angle of attack and the aeroelastic number on the aeroelastic behaviors are systematically examined. The time-averaged membrane deformation is positively correlated with a nondimensional number, the so-called Weber number. A new scaling relation is proposed based on the dynamic equilibrium between the aerodynamic force fluctuation and the combined inertia–elastic fluctuation. The unsteady aerodynamic force can be adjusted by manipulating the membrane vibration, the mass ratio, the Strouhal number, and the aeroelastic number. The numerical investigations provide design guidelines and have the potential to enhance the maneuverability and flight agility of micro air vehicles with flexible wing structures.

Combined hydrodynamic and control analysis on optimal kinematic parameters for bio-inspired autonomous underwater vehicle manoeuvring

To investigate the manoeuvring performance of a body-caudal fin robot fish, a numerical framework combining computational fluid dynamics and multi-body dynamics with a closed-loop control algorithm was established in this study. Within this framework, we modelled a body-caudal fin swimmer as a multi-body system with the shape of a NACA0012 hydrofoil. The manoeuvring performance was investigated by using different curvature magnitudes and distributions along the centre line (the curvature is defined by means of a curvature envelop function as part of the general body undulation equation). To characterize the turning performance, a new parameter named cost of manoeuvring (CoM) is proposed. This parameter provides a combined assessment of the turning radius, linear and angular velocity components, and power. It is found that when the body curvature is introduced, the swimmer switches from straight-line swimming to quasi-steady turning at a constant speed. Further investigations were conducted to study contributions of head and tail deformations on the turning performance by comparing predominantly head and tail curved envelopes. Results reveal that a tail-dominated envelope improves performance, whereas a head-dominated envelope has a negative effect.

Multi-source motion constrained model predictive control for tractor-trailer trucks with coupled dynamics

This paper proposes a constrained model predictive control (MPC) for tractor-trailer trucks with the complicated physical characteristics, where motion constraints can be considered to govern the vehicle maneuver. Firstly, a targeted theoretical derivation method is developed to establish a more accurate nonlinear model for articulated vehicles, with expressly considering the articulation coupling effects. As an essential basis, the kinematic coupling behavior is further investigated. Secondly, multi-source motion constraints are introduced in particular with the analysis of nonholonomic constraints on the underactuated trailer: (i) keeping trucks traveling in the feasible domain away from collision; (ii) maintaining the vehicle states in a stable field through the steady-state response and side-slip thresholds. Thirdly, a constrained MPC controller is constructed for the automatic tracking operation, wherein vehicle demands of position security and yaw stability will be taken into reasonable consideration. For this purpose, vehicle states information can be fully utilized in a parallel approach to optimize quadratic programming (QP) in MPC: model prediction and updated constraints. In the end, the contrasted-simulation analysis is carried out to verify the accuracy of derived model and effectiveness of the designed controller, along with the feasibility of the additive multi-source constraints.

Perceptions of novice driver education needs; Development of a scale based on the Goals for driver education using young driver and parent samples

Professional driver education and training has traditionally been used to improve the driving skills of young people with the expectation that they will drive more safely and therefore be less likely to crash. Despite this, much research has failed to find such an effect. The Goals for Driver Education (GDE) is a theoretical framework developed to improve the effectiveness of driver education. The GDE seeks to draw attention to a broader array of factors that may influence the driving of young people and hence increase the scope of what is included in driver education and training. Within the GDE, factors affecting driving and driver education are grouped into combinations of four hierarchical levels that represent influences on driving at increasing levels of abstraction (GDE level 1: Vehicle manoeuvring; GDE level 2: Mastery of traffic situations; GDE level 3: Goals and contexts of driving; GDE level 4: Goals for life and skills for living) and three types of individual competencies (Knowledge and skills; Risk-increasing factors; Self-evaluation skills). However, to date there have been few, if any, attempts to operationalise the GDE in a quantitative way. In response, the Perceptions of Driver Education Scale (PDES) was developed to gain an understanding of what two important stakeholder groups in the driver education and training ecosystem perceived to be important to be taught to novice drivers. Understanding these perceptions may lead to greater acceptance of the driver education and training that is designed and make it more effective. Following rigorous scale development procedures, thirty-five items were developed a priori using expert opinion and deployed, via an online survey, to a sample of parents of novice drivers (N = 518) and a separate sample of novice drivers (N = 247), both from Queensland, Australia. Exploratory Factor Analysis was performed on the parent responses and Confirmatory Factor Analysis was performed using the novice driver responses. A 29-item 9 factor solution was judged to be the best fit with the overall scale and each of the factors displaying strong levels of internal consistency. The 9 factors cover most hierarchical level and competency combinations, although removal of items meant that there is no representation concerning perceptions of Self-evaluation skills related to Level 3: Goals and contexts of driving within the PDES. Overall, the PDES is a valid and reliable instrument for investigating the aspects of driver education and training that are perceived as important by novice drivers and parents. The scale may also be applicable for use with other stakeholder groups and could also be used to evaluate pre-existing driver education and training programs.

Subtask-masked curriculum learning for reinforcement learning with application to UAV maneuver decision-making

Unmanned Aerial Vehicle (UAV) maneuver strategy learning remains a challenge when using Reinforcement Learning (RL) in this sparse reward task. In this paper, we propose Subtask-Masked curriculum learning for RL (SubMas-RL), an efficient RL paradigm that implements curriculum learning and knowledge transfer for UAV maneuver scenarios involving multiple missiles. First, this study introduces a novel concept known as subtask mask to create source tasks from a target task by masking partial subtasks. Then, a subtask-masked curriculum generation method is proposed to generate a sequenced curriculum by alternately conducting task generation and task sequencing. To establish efficient knowledge transfer and avoid negative transfer, this paper employs two transfer techniques, policy distillation and policy reuse, along with an explicit transfer condition that masks irrelevant knowledge. Experimental results demonstrate that our method achieves a 94.8% success rate in the UAV maneuver scenario, where the direct use of reinforcement learning always fails. The proposed RL framework SubMas-RL is expected to learn an effective policy in complex tasks with sparse rewards.

A Combined Reinforcement Learning and Model Predictive Control for Car-Following Maneuver of Autonomous Vehicles

Model predictive control is widely used in the design of autonomous driving algorithms. However, its parameters are sensitive to dynamically varying driving conditions, making it difficult to be implemented into practice. As a result, this study presents a self-learning algorithm based on reinforcement learning to tune a model predictive controller. Specifically, the proposed algorithm is used to extract features of dynamic traffic scenes and adjust the weight coefficients of the model predictive controller. In this method, a risk threshold model is proposed to classify the risk level of the scenes based on the scene features, and aid in the design of the reinforcement learning reward function and ultimately improve the adaptability of the model predictive controller to real-world scenarios. The proposed algorithm is compared to a pure model predictive controller in car-following case. According to the results, the proposed method enables autonomous vehicles to adjust the priority of performance indices reasonably in different scenarios according to risk variations, showing a good scenario adaptability with safety guaranteed.

Angle-Constrained Formation Maneuvering of Unmanned Aerial Vehicles

In a global positioning system (GPS)-denied environment, unmanned aerial vehicles (UAVs) rely on local sensing-based formation maneuvering approaches for collective motion. To improve mission efficiency by reducing the total sensing requirements on all UAVs, this article proposes a leader–follower formation maneuvering framework with two leaders, where the followers will track the two leaders and maintain a desired angle-constrained formation with respect to the leaders using direction-only measurements, i.e., removing the need for inter-UAV distance measurements for the followers. To enable the UAV formation to maneuver in translation, rotation, and scaling simultaneously, the desired formation shape is specified by a set of interior angle constraints. By assigning each UAV’s yaw angle and position as the four controllable variables, an estimation-based attitude control algorithm is designed. For the UAVs’ position control, the designed formation maneuvering algorithm consists of a velocity tracking part and a formation shape control part that enables the first leader UAV to control the translational maneuvering, the second leader UAV to control the rotational and scaling maneuvering, and all the follower UAVs to maintain the formation shape. Simulations and experiments on UAVs’ formation maneuvering are conducted to illustrate the effectiveness of the proposed approach.

A Maneuvering Model for an Underwater Vehicle Near a Free Surface—Part II: Incorporation of the Free-Surface Memory

Using energy-based modeling techniques, we propose a nonlinear, time-dependent, parametric motion model for an underwater vehicle maneuvering near an otherwise undisturbed free surface. By augmenting the system Lagrangian used to derive Kirchhoff's equations for a rigid body moving through an unbounded fluid, we directly incorporate the free surface into the derivation of the equations of motion. This is done using a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">free-surface Lagrangian</i> , which accounts for the instantaneous energy stored within the free surface due to an impulsive vehicle motion as well as fluid memory effects. The system Lagrangian then enables us to derive the six-degree-of-freedom nonlinear equations of motion using the Euler–Lagrange equations. The model structure is similar to standard maneuvering models for surface ships, although additional complexities are present since the hydrodynamic parameters are shown to depend on the vessel position and orientation relative to the free surface. For the proposed model, the vessel motion is unrestricted. This is in contrast to traditional seakeeping models, which use convolution integrals to incorporate memory effects for a vessel, which experiences only small perturbations from steady, forward motion. The proposed motion model is amenable to real-time simulation, design performance analysis, and nonlinear control design. Other important hydrodynamic effects due to viscous flow, for example, may then be incorporated into a robust, nonlinear, closed-loop control system as lumped parameter effects or model uncertainties.

A Hybrid of Random Forests and Generalized Path Analysis: A Causal Modeling of Crashes in 52,524 Suburban Areas.

Determining suburban area crashes' risk factors may allow for early and operative safety measures to find the main risk factors and moderating effects of crashes. Therefore, this paper has focused on a causal modeling framework. A cross-sectional study. In this study, 52524 suburban crashes were investigated from 2015 to 2016. The hybrid-random-forest-generalized-path-analysis technique (HRF-gPath) was used to extract the main variables and identify mediators and moderators. This study analyzed 42 explanatory variables using a RF model, and it was found that collision type, distinct, driver misconduct, speed, license, prior cause, plaque description, vehicle maneuver, vehicle type, lighting, passenger presence, seatbelt use, and land use were significant factors. Further analysis using g-Path demonstrated the mediating and predicting roles of collision type, vehicle type, seatbelt use, and driver misconduct. The modified model fitted the data well, with statistical significance ( χ230 =81.29, P<0.001) and high values for comparative-fit-index and Tucker-Lewis-index exceeding 0.9, as well as a low root-mean-square-error-of-approximation of 0.031 (90% confidence interval: 0.030-0.032). The results of our study identified several significant variables, including collision type, vehicle type, seatbelt use, and driver misconduct, which played mediating and predicting roles. These findings provide valuable insights into the complex factors that contribute to collisions via a theoretical framework and can inform efforts to reduce their occurrence in the future.

A novel high-performance three-phase magnetic field energy harvester for powering up vehicle onboard electronics

The boosting development of vehicle electrification and onboard sensing networks in the intelligent vehicle era poses a significant challenge to conventional electrical power supply systems. This study developed a novel passive three-phase magnetic field energy harvester (TMEH) for reliable and sustaining power to drive vehicle onboard electronics, which recycles the induced magnetic field energy around the power lines of a permanent magnet synchronous motor (PMSM) on an electric vehicle (EV). A Y-Y topological connection pattern for three-phase coils was designed to enhance and stabilize the TMEH output performance. Furthermore, three auto-shift operating modes were assigned to the TMEH to tackle the dynamic changes of the captured power caused by unpredictable vehicle manoeuvres and road conditions. The theoretical model and numerical method were also established for structural optimization of the TMEH, followed by a series of experimental tests for highlighting the impacts of the power lines carrying alternating current on TMEH. The results have indicated that the proposed TMEH showed impressive energy conversion efficiency, providing an independent power supply for sensors and other electronics applications on a 4 kW-PMSM driven EV. Bench testing results and practical EV driving trials demonstrated the capability of the TMEH prototype to power up multiple types of sensors and electronic devices under most EV driving conditions. Specifically, an average power of 5.69 W and power density of 123.85 mW/cm3 were generated by the harvesting coils when excited by a 50 A current at 50 Hz. Furthermore, the maximum TMEH energy conversion efficiency of 41.9% at the excitation current frequency of 50 Hz is obtained in laboratory conditions. In EV driving tests at speeds of 20–30 km/h, the TMEH presented steady output power up to 5.98 W, capable of driving various loads such as an electronic resistor, Li-ion battery, GNSS/INS device, driving recorder, and cellphone, either with the employment of one or two sets of harvesting coils. The approach of this study offers a promising application scenario to power up numerous electronics on a commercial transport EV platform driven by a more powerful PMSM.

Steering angle sensorless control for four-wheel steering vehicle via sliding mode control method

This paper presents a new sensorless control method for four-wheel steering vehicles. Compared to the existing sensor-based control, this approach improved dynamic stability, manoeuvrability and robustness in case of malfunction of the front steering angle sensor. It also provided a software redundancy and backup solution, as well as improved fault tolerance. The strategy of the sensorless control is based on the sliding mode method to estimate the replacement of the front steering input from the errors between the vehicle’s measured and desired values of the vehicle’s sideslip angle and yaw rate. The simulation results demonstrate that the observer effectively estimated the front wheel steering angle at both low- and high-speed scenarios in the cornering and lane change manoeuvres. Furthermore, the sensorless control approach can achieve equivalent control performances to the sensor-based controller including a small and stable yaw rate response and zero sideslip angle. The results of the study offer a potential solution for improving manoeuvrability, stability and sensor fault tolerance of four-wheel steering vehicles.

Numerical and Experimental Investigation on Nosebleed Air Jet Control for Hypersonic Vehicle

A new idea of nosebleed air jets with strong coupled internal and external flow is put forward using the lateral jet control principle to improve the maneuverability and fast reaction capabilities of hypersonic vehicles. The hypersonic vehicle’s nose stagnant high-pressure and high-temperature gas is utilized as the drive source for long-term jet control. The significant coupled jet interaction of the internal and external flow changes the aerodynamic characteristics. As a result, the structure is basic and does not rely on any external source to achieve flight attitude control. The complicated flow characteristics of the nosebleed jet in supersonic crossflow surrounding the vehicle were numerically and experimentally investigated. The jet interaction characteristics and the aerodynamic characteristic changes generated by the nosebleed air jet are verified by comparing the flow field with and without the jet. Results indicate that the nosebleed air jet alters the center-of-pressure coefficient, which is subsequently coupled with the interference aerodynamic force. This results in a variation in pitch moment. The jet decreases the pitching moment coefficient when compared with the case without a jet. It is probable that combining nosebleed air jets with model centroid adjustment yields an optimal trim angle of attack.

IMPROVING MANEUVERABILITY OF A WHEELED VEHICLE BY IMPROVING TURN CONTROL METHOD

A large number of scientific works and design developments are devoted to the study and improvement of the properties of maneuverability, which is also a complex (complex) property. At one time, the need to reduce the building volume required the installation of swivel wheels on the front steering axle of the car. However, in this case, additional resistance to the movement of the machine arose, which is due to the discrepancy between the trajectories of the movement of the front outer and inner guide wheels with their trajectories during an ideal turn. The development of the designs of electric vehicles and hybrid vehicles allows for separate control of the front wheels. The analysis of the whole variety of indicators and criteria of maneuverability in general and individual properties was carried out. Unlike other systematization of these indicators and criteria, it is proposed to divide these indicators and criteria into three main groups. All indicators and criteria used to assess the maneuverability of vehicles are also used to assess the maneuverability of wheeled tractors with a center of mass shifted to the rear axle and, therefore, have low controllability. Force and energy criteria can be used in the design of cars and tractors to ensure the ability of the latter to maneuver. In addition, as a result of the study, a combined method for controlling the movement of a two-axle swivel bogie of a wheeled vehicle has been improved due to the fact that its rotation is carried out by two torque control moments. The first of these control torques is generated by the driver through the steering and power cylinder. The second torque control moment is created due to the difference in torques on the wheels of the outer and inner sides of the two-axle swivel bogie. The implementation of these rules for regulating the distribution of traction forces between the sides makes it possible to overcome the resistance to rotation of a two-axle swivel bogie and improve the quality of motion control of the specified bogie and wheeled vehicle. Keywords: maneuverability, separate control, wheeled vehicle, control method, two-axle swivel bogie

Evaluating Right-Turn Flashing Yellow Arrow for Vehicle–Pedestrian Interactions Using a Non-Probabilistic Regression Approach

Using video, interactions between right-turning vehicles and pedestrians were documented for sites with a permissive circular green or a flashing yellow arrow (FYA) permissive right-turn indication. Timestamps associated with key vehicle and pedestrian positions were documented and used to calculate three metrics: time for driver to complete right turn (with and without a pedestrian presence) and the time for the pedestrian to arrive at the theoretical conflict point of vehicle–pedestrian interactions. Using timestamp data, multiple non-probabilistic linear regression models were created to describe the relationship between the position of the pedestrian within the crosswalk and the time for a right-turning vehicle maneuver to be completed. Model results implicitly describe the attitude of drivers toward pedestrian presence on the crosswalk. Larger right-turning maneuver completion times are arguably an indicator of greater respect toward pedestrian presence. Given the nature of the model’s output, a pedestrian respect indicator (PRI) based on the value of model parameters is introduced as a potential indicator of the safety of vehicle–pedestrian interactions. PRI values can be computed for individual sites thus allowing its use as a safety indicator. The higher the PRI, the more “respect” toward pedestrians. Proof-of-concept modeling results based on available timestamp data suggest that interactions controlled by a right-turn FYA indication have a higher PRI than interactions controlled by a circular green. An argument is made that PRI values can be potentially used to proactively evaluate the effectiveness of traffic control devices and other safety countermeasures without the need for crash data.

Fuel consumption at signalized intersections: Investigating the impact of different signal indication settings

The fuel consumption of vehicles depends on various factors including vehicle design, driving style, traffic management, and road design. Many manufacturers have been developing efficient and smart vehicles, which contributes to minimizing vehicle fuel consumption. However, traffic management and control could restrict the efficiency of having a sustainable mobility system. Intersections are considered as critical locations, in terms of fuel consumption, due to the significant impact of traffic control at these locations on the vehicle maneuver either by stopping or acceleration to clear these bottleneck points. Analyzing the effect of different intersection signal settings is, therefore, important to optimize vehicle fuel consumption. In this study, we used simulator data of sixty-six drivers going through signalized intersections equipped with two different signal indication settings, namely, control and flashing green conditions. We calculated total fuel consumption using the VT-CPFM and COPERT models and then applied GLME with two different model distributions: normal and log-normal to study the correlation between the two treatments and fuel consumption. Results showed that by displaying the remaining green time, flashing green treatment (i.e., signals with traffic light sequence: green, flashing green, yellow and red-green) produced a lower fuel consumption in comparison to control condition (green, yellow and red sequence), yielding to a similar performance of eco-driving. It was found that as drivers become aware ahead of time when the traffic light will be turning red due to the flashing green signal indication, eventually they either speed up a little to cross the intersection in time, or they early start decelerating, which creates a more optimal deceleration pattern. Results also showed that the VT-CPFM model resulted in more realistic results than COPERT due to its ability to capture the transient changes in speed and acceleration.

An improved body force method for simulation of self-propulsion AUV with ducted propeller

The body force method (BFM) is an efficient computational method used for maneuvering simulations of marine vehicles with ordinary propellers. In this paper, an improved BFM is proposed to perform maneuvering simulations of a self-propelled AUV with a ducted propeller. Initially, the conventional BFM is applied to numerically investigate the open water performance of a ducted propeller(No. 19A+Ka4-70). However, significant prediction errors have been observed, which were mainly caused due to ignorance of the interaction between the duct and the propeller. To increase the prediction accuracy, an improved BFM is proposed to perform maneuvering simulations of the ducted propeller AUV by considering the mass flow correction. In addition, the external diameter of the actuator is proposed to be a function of real-time advance velocity. To investigate the efficacy of the proposed method, the simulated results have been compared with the model testing carried out in a towing tank and with the discretized propeller method. The proposed improved BFM is used to simulate the 20°/20° zigzag tests of AUV in both vertical and horizontal planes with different advance speeds. Simulated results, particularly propeller thrust, advance speed, pitch (or yaw), resistance, and especially duct thrust of AUV have significantly improved as compared to the conventional BFM. The improved BFM results were found in close agreement with discretized propeller method and thus, the proposed method is considered a highly efficient and computationally cost-effective method to perform maneuvering simulations of ducted-propeller marine vehicles. The present work can contribute to the fast optimization of the manoeuvrability of marine vehicles with ducted propeller.

Safety-Critical Containment Maneuvering of Underactuated Autonomous Surface Vehicles Based on Neurodynamic Optimization With Control Barrier Functions.

This article addresses the safety-critical containment maneuvering of multiple underactuated autonomous surface vehicles (ASVs) in the presence of multiple stationary/moving obstacles. In a complex marine environment, every ASV suffers from model uncertainties, external disturbances, and input constraints. A safety-critical control method is proposed for achieving a collision-free containment formation. Specifically, a fixed-time extended state observer is employed for estimating the model uncertainties and external disturbances. By estimating lumped disturbances in fixed time, nominal containment maneuvering control laws are designed in an Earth-fixed reference frame. Input-to-state safe control barrier functions (ISSf-CBFs) are constructed for mapping safety constraints on states to constraints on control inputs. A distributed quadratic optimization problem with the norm of control inputs as the objective function and ISSf-CBFs as constraints is formulated. A recurrent neural network-based neurodynamic optimization approach is adopted to solve the quadratic optimization problem for computing the forces and moments within the safety and input constraints in real time. It is proven that the error signals in the closed-loop control system are uniformly ultimately bounded and the multi-ASVs system is guaranteed for input-to-state safety. Simulation results are elaborated to substantiate the effectiveness of the proposed safety-critical control method for ASVs based on neurodynamic optimization with control barrier functions.

Wireless Distributed Consensus in Vehicle to Vehicle Networks for Autonomous Driving

Vital societal and industrial autonomous components are increasingly interconnected through communication networks to complete critical tasks cooperatively. However, as the reliability and trust requirements for connected autonomous systems continue to grow, the centralized communication and decision approaches that are in use today are reaching their limits. Focusing on autonomous driving applications, this paper proposes a resilient and trustworthy framework on wireless distributed consensus networks, where the communication links are less reliable or are even in the presence of incorrect local sensor readings/decisions. To accomplish that, a novel three stages consensus mechanism is proposed based on the practical Byzantine fault tolerance (PBFT), where the veto collection and gossip stages are designed to meet the stringent and complex requirements for a vehicle's maneuvers. A plan tree synthesis is also proposed to make consensus on a series of decisions while adopting network members' decision preferences. A detailed protocol including the distributed consensus, plan tree synthesis, dynamic grouping, etc. is proposed. Simulation results show that the proposed consensus mechanism is able to be reached and propagated through the network under poor wireless communication conditions and the presence of faulty vehicles with incorrect sensor readings. The result can be extended to other autonomous systems to significantly enhance safety in critical industrial applications.

Improving the maneuverability of vehicles by using front swivel axles with separate electric wheels

There is a need for vehicles to maneuver when there are traffic jams, to overcome narrow streets and various obstacles. This leads to increased requirements for dynamism and maneuverability of vehicles.&#x0D; The authors present the results of the development and research of the steering control of the vehicle, which provides increased maneuverability. Such circumstances significantly affect the increase in maneuverability of wheeled vehicles, including tractors, for which the use of front suspension axles is possible in terms of layout. The use of a front swing axle with electric motor-wheels with separate control will increase the maneuverability of a two-axle vehicle and minimize the steering effort when turning.&#x0D; When solving the task, a mathematical model of the movement of the vehicle on a turn was created. The forces in the contact of the wheels with the road surface were determined, which made it possible to determine the forces and moments of resistance to the rotation of the front axle. Rational laws of control of turning the front axle, providing minimal resistance to the movement of the vehicle, were obtained.&#x0D; A vehicle turning control option is proposed, in which the wheels of the outer and inner sides are alternately braked when the vehicle enters and exits the turn. In addition, it is possible to alternately create a torque difference on the wheels of the outer and inner sides of the front axle. Using the proposed turn control options, it is possible to create a multi-axle vehicle with a rocking axle.&#x0D; The materials of the article on the controllability of vehicles depending on the design of the steering and front axle are of interest to researchers, designers of mobile equipment, graduate students and students of engineering specialties

An unscented Kalman filter based velocity estimation method for articulated steering vehicle using a novel dynamic model

This paper presents a novel velocity estimation method for an articulated steering vehicle to improve the automation and safety of articulated steering vehicle. The estimation method process is done in three steps: First, the articulated steering vehicle's tire forces are calculated separately against articulated steering vehicle's asymmetric tire load transfers. Then the tire forces are used to build a concise dynamic model, which only needs to consider the single centroid's dynamics in a fixed direction of the vehicle body. Finally, an unscented Kalman filter estimator is developed further based on the articulated steering vehicle dynamics model for velocity estimation. The main contribution of this paper to the related literature lies in two aspects. On the one hand, by converting the velocity vectors of each vehicle body to a fixed coordinate system, a concise dynamic model is built to avoid complex calculations and high sensor costs. On the other hand, an additional moment equilibrium equation is introduced to assist the simplified estimator in calculating the asymmetric tire dynamics of articulated steering vehicle, which ensures the accuracy and universality of the method. The simulation results from ADAMS/MATLAB indicate that the proposed model can effectively reflect the dynamics of articulated steering vehicle even under obvious load transfer. In addition, the developed unscented Kalman filter estimator can obtain accurate and robust estimation results in several typical vehicle manoeuvres.