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This study explores the effectiveness of vertical force control in in-wheel motors (IWMs) to enhance ride comfort in electric vehicles (EVs). A dynamic vehicle model and a proportional ride-blending controller were used to reduce vertical vibrations of the sprung mass. By converting the state-space model into a transfer function, the system's frequency response was evaluated using road profiles generated according to ISO 8608 standards and converted into Power Spectral Density (PSD) inputs. The frequency-weighted acceleration ( a w ) was calculated based on ISO 2631 standards to measure ride comfort improvements. The results showed that increasing the proportional gain ( K p ) effectively reduced the frequency-weighted acceleration and the RMS of the vertical acceleration of the sprung mass. However, the proportional gain could not be increased indefinitely due to the torque limitations of the IWMs. Optimal proportional gains for various road profiles demonstrated significant improvements in ride comfort. This study concludes that advanced suspension technologies, including the proportional ride-blending controller, can effectively mitigate the challenges of increased unsprung mass in IWM vehicles, thereby enhancing ride quality and vehicle dynamics. [ABSTRACT FROM AUTHOR]

Hybrid wheel–track systems have found extensive applications due to the advantages a combination of wheels and tracks. However, the coupling influence between the wheeled and tracked mechanisms poses a challenge to stable and efficient controller design and implementation. This paper focuses on the lateral dynamic control of a vehicle in scenarios where both tracks and wheels are in contact with the ground. A dynamic model of a vehicle is first established based on the tire brush model and linearized general track model. Based on the dynamic model, a novel adaptive model predictive control (AMPC) method is designed considering the coupling and nonlinearity of the wheels and tracks to simultaneously regulate both mechanisms. Compared with traditional model predictive control approaches, the AMPC controller takes the side-slip angle and slip ratio as constraints to prevent the vehicle from reaching unstable states. Simulations are conducted to validate the effectiveness of the controller, and the results indicate that the controller has the capacity to optimize the objective's yaw-rate response while maintaining lateral vehicle stability and preventing slip by imposing constraints. [ABSTRACT FROM AUTHOR]

The hybrid system can extend the range of special vehicles and meet the electrical requirements of on-board equipment. In this paper, the driving force plummet problem of a new two-gear power-split hybrid system was studied during gear switches in a hybrid mode. The dynamic model of a hybrid electric system was established, and the effects of the engine angular acceleration and angular jerk on vehicle power and ride performance were obtained. The optimal ratio of the torque change rate of the motor and engine in the mode switch process was proposed. Considering the battery limitation and the external characteristics of the engine, the method of determining the target speed of the engine during shifting was proposed. Considering the response characteristics of each power source, the dynamic coordinated control strategy of multiple power sources in the mode switch process was proposed. The vehicle dynamics model was established based on the Matlab/Simulink 2020b and verified by simulation and a hardware-in-the-loop (HIL) test. The results show that the dynamic coordinated control strategy can reduce the peak impact by 80.33%, effectively improve the vehicle power and ride performance, and prevent the occurrence of high-current battery charging. [ABSTRACT FROM AUTHOR]

Considering the requirements pertaining to the trafficability of off-road vehicles on rough roads, and since their roll stability deteriorates rapidly when turning violently or passing slant roads due to a high center of gravity (CG), an efficient anti-slip control (ASC) method with superior instantaneity and robustness, in conjunction with a rollover prevention algorithm, was proposed in this study. A nonlinear 14 DOF vehicle model was initially constructed in order to explain the dynamic coupling mechanism among the lateral motion, yaw motion and roll motion of vehicles. To acquire physical state changes and friction forces of the tires in real time, corrected LuGre tire models were utilized with the aid of resolvers and inertial sensors, and an adaptive sliding mode controller (ASMC) was designed to suppress each wheel's slip ratio. In addition, a model predictive controller (MPC) was established to forecast rollover risk and roll moment in reaction to the change in the lateral forces as well as the different ground heights of the opposite wheels. During experimentation, the mutations of tire adhesion capacity were quickly discerned and the wheel-hub drive motors (WHDM) and ASC maintained the drive efficiency under different adhesion conditions. Finally, a hardware-in-the-loop (HIL) platform made up of the vehicle dynamic model in the dSPACE software, semi-active suspension (SAS), a vehicle control unit (VCU) and driver simulator was constructed, where the prediction and moving optimization of MPC was found to enhance roll stability effectively by reducing the length of roll arm when necessary. [ABSTRACT FROM AUTHOR]

The rail vehicle industry wants to produce vehicles with higher speeds, to maintain and increase its market share. However, when the speed of the vehicle increases, it may have an undesirable effect on ride comfort, in terms of ride dynamics. Recent developments towards lighter and faster vehicles make the problem of ride comfort at higher speeds increasingly important. Focusing on the behavior of flexible rather than rigid body behavior should not be neglected when designing long and light car bodies. There are several approaches to incorporate body flexibility in multibody simulations and they have some superiorities and weaknesses. In this study, an efficient and accurate vertical dynamic model for the ride comfort analysis is developed and implemented in a commercial object-oriented modeling (OOM) software Dymola (2015 FD01) which uses the open-source code Modelica. This model includes car body flexibility with the assembling of a rigid body approach. The developed model is compared to a three-dimensional vehicle model in the commercial Vampire software (Pro V5.50) at different velocities. For the vertical ride comfort analysis, the ISO 2631-1 standard was used for both the developed model and the three-dimensional model. The results are presented as acceleration history and a w r m s —weighted r.m.s (root mean square) of accelerations—as required by the standard. The developed model has shown its feasibility in terms of its efficiency and accuracy for the vertical ride comfort analysis. The accuracy of the model is evidenced by the fact that the car body vibration level at high speeds shows minor differences compared to the results of the Vampire, which is a validated commercial software in the area of rail vehicle dynamics. The approach involving the assembly of rigid bodies is applied for the first time for high-speed trains in dynamical modelling, with flexible car bodies for ride comfort analysis. Furthermore, it can be used for parametrical studies focusing on ride comfort, thereby offering a quite beneficial framework for addressing the challenges of ride comfort analysis in high-speed rail vehicles. Improvements for and analyses of other aspects are also possible, since the optimization and other useful libraries are readily available in Dymola/Modelica. [ABSTRACT FROM AUTHOR]

The development of intelligent transportation technology has provided a significant impetus for autonomous driving technology. Currently, autonomous vehicles based on Model Predictive Control (MPC) employ motion control strategies based on sampling time, which fail to fully utilize the spatial information of obstacles. To address this issue, this paper proposes a dual-layer MPC vehicle collision-free trajectory tracking control strategy that integrates spatial kinematics and vehicle dynamics. To fully utilize the spatial information of obstacles, we designed a vehicle model based on spatial kinematics, enabling the upper-layer MPC to plan collision avoidance trajectories based on distance sampling. To improve the accuracy and safety of trajectory tracking, we designed an 8-degree-of-freedom vehicle dynamic model. This allows the lower-layer MPC to consider lateral stability and roll stability during trajectory tracking. In collision avoidance trajectory tracking experiments using three scenarios, compared to two advanced time-based algorithms, the trajectories planned by the proposed algorithm in this paper exhibited predictability. The proposed algorithm can initiate collision avoidance at predetermined positions and can avoid collisions in predetermined directions, with all state variables within safe ranges. In terms of time efficiency, it also outperformed the comparative algorithms. [ABSTRACT FROM AUTHOR]

With the advancement of technology, mining trucks are gradually becoming larger, imposing higher performance requirements on the front suspension. There is a need to transform the original integral non-independent front axle of mining dump trucks with a payload exceeding 300 tons into an independent front suspension with a double-wishbone suspension. The changing of the front suspension is bound to have an impact on the overall vehicle's handling stability and ride comfort. Therefore, the following research is conducted to investigate and analyze these effects. Firstly, the paper proposes a method for optimizing the parameters of the double-wishbone front suspension. The double-wishbone front suspension is modeled, and a comparison with a kinematic model is conducted to validate the accuracy of the model. Secondly, unreasonable hardpoint parameters are optimized. Thirdly, a dynamic model of the entire vehicle is established based on the optimized parameters, and an analysis of handling stability and ride comfort for the entire vehicle is performed. Finally, simulation results are compared and analyzed against experimental data. The results indicate that the optimized positioning parameters not only effectively enhance the suspension performance of the mining dump truck but also meet the requirements for handling stability and smoothness. The overall smoothness of the vehicle is significantly improved after the modification. This study not only holds significant engineering value in reducing vibrations in dump trucks and enhancing driver comfort, but also provides theoretical support for subsequent research and development in the industry. [ABSTRACT FROM AUTHOR]

Despite its excellent performance in path tracking control, the model predictive control (MPC) is limited by computational complexity in practical applications. The neural network control (NNC) is another attractive solution by learning the historical driving data to approximate optimal control law, but a concern is that the NNC lacks security guarantees when encountering new scenarios that it has never been trained on. Inspired by the prediction process of MPC, the deviation sequence neural network control (DS-NNC) separates the vehicle dynamic model from the approximation process and rebuilds the input of the neural network (NN). Taking full use of the deviation sequence architecture and the real-time vehicle dynamic model, the DS-NNC is expected to enhance the adaptability and the training efficiency of NN. Finally, the effectiveness of the proposed controller is verified through simulations in Matlab/Simulink. The simulation results indicate that the proposed path tracking NN controller possesses adaptability and learning capabilities, enabling it to generate optimal control variables within a shorter computation time and handle variations in vehicle models and driving scenarios. [ABSTRACT FROM AUTHOR]

This paper proposes a monitoring procedure based on characterizing state probability distributions estimated using particle filters. The work highlights what types of information can be obtained during state estimation and how the revealed information helps to solve fault diagnosis tasks. If a failure is present in the system, the output predicted by the model is inconsistent with the actual output, which affects the operation of the estimator. The heterogeneity of the probability distribution of states increases, and a large proportion of the particles lose their information content. The correlation structure of the posterior probability density can also be altered by failures. The proposed method uses various indicators that characterize the heterogeneity and correlation structure of the state distribution, as well as the consistency between model predictions and observed behavior, to identify the effects of failures.The applicability of the utilized measures is demonstrated through a dynamic vehicle model, where actuator and sensor failure scenarios are investigated. [ABSTRACT FROM AUTHOR]

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]

Braking control of urban rail vehicles with multiple carriages is critical to ensure the safe operation of urban rails. However, existing decentralized braking control methods lead to the inconsistent speed and excessive coupler force among carriages, which compromises the operation safety of urban rails. To address this issue, a cooperative braking strategy is proposed for urban rail vehicles based on Koopman model predictive control method. First, a cyber‐physical model is established, where the physical layer characterizes the dynamic model of multiple carriages using the Koopman operator. The cyber layer represents the communication topology of carriages with graph theory. Second, a cooperative braking controller is designed with the distributed model predictive control method. An optimisation problem is formulated to minimize the speed inconsistency and relative displacement difference among carriages. Third, extensive simulations under various scenarios, including normal and extreme operating conditions, are conducted to verify the effectiveness of the proposed method. Simulation results show that, compared with the classical decentralized method, the proposed braking method reduces the average relative displacement by 78% while reducing the speed error by 29%. [ABSTRACT FROM AUTHOR]

In this paper, the authors investigate the issue of constructing and incorporating an accurate vehicle dynamic model for model predictive control (MPC) with an application to autonomous vehicle path following. To achieve the desired performance, MPC employs a precise dynamic model. However, the uncertainty of complex systems and their operating environments presents a challenge to the development of an adequately accurate vehicle dynamic model. This paper proposes a Deep Gaussian Process Regression (DGPR) method to improve model precision. Meanwhile, the learning model is incorporated into a novel MPC framework to enhance closed‐loop performance. High‐fidelity simulations using CarSim‐MATLAB demonstrate the validity of the proposed approach in terms of enhancing the path following performance and lateral stability under the condition of large curvature at medium to high speeds on roads with different friction coefficients when compared to the nominal MPC approach. [ABSTRACT FROM AUTHOR]

The high-speed collision issue brought on by railway vehicles' intensive and high-speed operation has become a critical concern for operational safety. Therefore, it is necessary to research the high-speed collision problem of trains. Firstly, a train collision dynamic model suitable for higher collision velocities is established. This model includes a 38-degree-of-freedom (DOF) three-dimensional vehicle model and a three-layered vibrating fixed-track model. Corresponding mathematical models are developed for nonlinear factors such as wheel–rail contact, car–end contact, and coupler overload representation in the model. Then, the Train Collision State Score (TCSS) is proposed, enabling quantitative safety evaluation under different collision conditions. Finally, the influence of the energy-absorbing device's initial attitude and leading car parameters on collisions is studied. The results indicate that initial vertical height difference and pitching angle significantly increase TCSS. As the force level of the energy-absorbing device of the leading car increases, the effects of two intermediate coupler overload states on TCSS show opposite trends. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of path following and dynamic obstacle avoidance for an underwater biomimetic vehicle-manipulator system (UBVMS). Firstly, the general kinematic and dynamic models of underwater vehicles are presented; then, a nonlinear model predictive control (NMPC) scheme is employed to track a reference path and collision avoidance simultaneously. Moreover, to minimize the tracking error and for a higher degree of robustness, improved extended state observers are used to estimate model uncertainties and disturbances to be fed into the NMPC prediction model. On top of this, the proposed method also considers the uncertainty of the state estimator, while combining a priori estimation of the Kalman filter to reasonably predict the position of dynamic obstacles during short periods. Finally, simulations and experimental results are carried out to assess the validity of the proposed method in case of disturbances and constraints. [ABSTRACT FROM AUTHOR]

The advanced modeling and estimation of overall system dynamics play a vital role in electric vehicles (EVs), as the selection of components in the powertrain and prediction of performance are the key market qualifiers. The state-space averaged model and small-signal transfer function model are useful for assessing long-term behavior in system-level analysis and for designing the controller parameters, respectively. Both models take less computation time but ignore the high-frequency switching dynamics. Therefore, these two models could be impractical for the development and testing of EV prototypes. On the other hand, the multi-domain model in available simulation tools gives in-depth information about the short-term behavior and loss analysis of power electronic devices in each subsystem, considering the switching dynamics in a long computation time. In this paper, a general mathematical framework for the dynamical analysis of complete EVs is presented using a unified, switched nonlinear model. This equation-based model runs faster than the available module-based simulation tools. Two other models, namely the time domain state-space averaged model and frequency domain small-signal transfer function model, are also developed from the switched nonlinear model for the analysis with less computation time. The design and performance of an EV with two different motors and its controllers are evaluated using the general mathematical framework. [ABSTRACT FROM AUTHOR]

This work is focused on the simulation of a complete hybrid bus vehicle model performing a real-world driving cycle. The simulation framework consists of a coupled co-simulation environment, where all the vehicle sub-system models are linked to achieve a real time exchange of input and output signals. In the vehicle model also the electric devices of the powertrain and accumulation system are included. This co-simulation platform is applied to investigate the hybridization of a 12-m city bus, performing a typical urban driving mission. A comparison between the conventional powertrain is performed against the hybridized version, to highlight the advantages and challenges. In particular, the novelty of this modeling approach is that the IC engine simulation does not rely on pre-processed look-up tables, but exploits a high-fidelity one-dimensional thermo-fluid dynamic model. However, it was necessary to develop a fast simulation methodology to exploit this predictive tool, achieving a low computational cost. The 1D engine model is first validated against the experimental engine map data available, showing a good model predictivity. Then the 1D engine model and the other models of the powertrain are coupled to the vehicle model, in order to follow the prescribed velocity profile of the driving cycle. The complete model is applied under different conditions, to evaluate the impact on performance and emissions and assess the simulation predictivity. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the control of differential steering for four-in-wheel-motor electric vehicles. The so-called differential steering means that the front wheel steering is realized through the differential driving torque between the left and right front wheels. With the consideration of tire friction circle, a hierarchical control method is proposed to realize the differential steering and the constant longitudinal speed simultaneously. Firstly, the dynamic models of the front wheel differential steering vehicle, the front wheel differential steering system and the reference vehicle are established. Secondly, the hierarchical controller is designed. The upper controller is to obtain the resultant forces and resultant torque required by the front wheel differential steering vehicle tracking the reference model through the sliding mode controller. In the middle controller, the minimum tire load ratio is selected as the objective function. Combined with the constraints, the resultant forces and resultant torque are decomposed into the longitudinal and lateral forces of four wheels by the quadratic programming method. The lower controller provides the required longitudinal forces and tire sideslip angles for the front wheel differential steering vehicle model through the tire inverse model and the longitudinal force superposition scheme. Simulation results show that the hierarchical controller can guarantee the vehicle to track the reference model well on both of the high and low adhesion coefficient road with all of the tire load ratios smaller than 1. It can be drawn that the control strategy proposed in this paper is effective. [ABSTRACT FROM AUTHOR]

The intelligent tracing car is a complex system with high linearity, and the design of path tracking strategy is one of the most important technologies in intelligent tracing car field. This paper proposed a novel path tracking strategy based on control dynamic model of the intelligent tracing car. The vehicle dynamic models are established separately according to the vehicle parameters and kinetic equation. The traditional path tracking strategy used the distance between the desired and actual displacements to compute the error for position control. However, the paper utilized the past and current states of the desired displacement to figure out a motion vector. The error was acquired through calculating the difference between the desired and current displacements along this motion vector. Simulation results showed excellent performance in position control and speed control for the intelligent tracing car. [ABSTRACT FROM AUTHOR]

The irregular ocean environment brings difficulties to observation and affects the movement state of underwater vehicles. Multisource information fusion can provide more reliable results on information-rich datasets. This paper proposes a multisource information fusion-based environment perception and dynamics model for underwater vehicles in irregular ocean environments. First, the multisource observation data is decomposed by the latent feature disentanglement learning model into the latent stable and dynamical features. The dynamical feature is predicted by the retrospect regression method and then integrated with the latent stable feature to predict the ocean field. After that, the environment-vehicle coupling effect is explored by thermodynamics and statics simulation. Then, a real-time dynamic model of the underwater vehicle is constructed by combining multisource information from physical principles, environmental perception, and sensor observations. Finally, extensive experiments are performed on a novel underwater glider and a publicly available South China Sea dataset to verify the proposed method. • An environment perception model is proposed for the underwater vehicle array. • A real-time dynamic model is proposed for the underwater vehicle. • Environment-vehicle coupling effect is explored. [ABSTRACT FROM AUTHOR]

This research introduces an innovative strategy to impede and lessen lateral and rear-end vehicular collisions by consolidating braking systems with active emergency steering controls. This study puts forward a T-type active emergency steering method, designed to circumvent both lateral and rear-end collisions at vehicular intersections. To secure vehicular stability and condense the time required for steering during the T-type active emergency process, this research formulates a nonlinear dynamic model for the vehicle, in addition to a nonlinear tire model. This study also engages in a thorough analysis of the constraints linked to the initial and terminal states of the steering process. The issue at hand is articulated as an optimization control problem with boundary value restrictions, which is subsequently resolved using the Radau pseudospectral method. Simulation results corroborate that the prompt commencement of the anti-collision strategy can effectively deter potential collisions. This pioneering approach shows considerable promise in augmenting the active safety of intelligent vehicles and bears meaningful implications for high-precision automotive collision evasion systems. [ABSTRACT FROM AUTHOR]

This study presents a dynamic model of a passenger vehicle and analyzes its dynamic characteristics and responses. A dynamic vehicle model with seven degrees of freedom was established to analyze the behavior of a driving vehicle. The vehicle model had three degrees of freedom for the sprung mass's motion and four degrees for the unsprung masses. For this model, the equations of motion were derived using Lagrange's equation. To verify the model, the suspension deformations computed using the model were compared with those measured through three actual vehicle driving tests: the slalom, double lane change, and step steer tests. Furthermore, we investigated the effects of suspension stiffness, suspension damping, and anti-roll bar torsional stiffness on the dynamic characteristics and responses of the vehicle model. This study presented a new full-car model that can analyze a turning vehicle's behavior in response to changes in the steering angle input. The developed dynamic vehicle model may help vehicle designers predict the dynamic responses of a vehicle through simulation without performing a driving test. [ABSTRACT FROM AUTHOR]

Deep-sea mining vehicles (DSMVs) are highly prone to sinking and slippage when traveling on extremely soft seafloor sediments. In addition, DSMVs can be vulnerable to dangerous situations such as overturning due to the non-homogeneous characteristic of the seafloor sediments, the heavy loads carried by DSMVs, and the complex and varied topography of the seafloor. When the terrain is uneven, four-tracked DSMVs can show excellent traveling abilities and safety performances compared with conventional dual-tracked vehicles, thus having a broad range of applications. Consequently, modeling and simulation of a four-tracked DSMV are essential for the study of DSMV traveling performance. To enhance adaptability to uneven terrain, the tracks are designed to be rotatable. First, a multi-body dynamics model is built in the Recurdyn software based on the actual structural properties of a specially designed four-tracked DSMV prototype. Then, the model's forces are modified to reflect the actual circumstances of seafloor travel. Applying a more accurate shear model, a user subroutine is written to modify the track–soil force. Moreover, internal resistance and water resistance are considered and applied to the model in the form of external loads. Then, based on the multi-pass effect, the track–soil force to the rear track is modified. Moreover, considering the relationship between soil forces and velocity, a velocity coefficient is summarized and added to the resistance estimation equation. Consequently, a more realistic dynamic model of the mining vehicle has been developed. On this basis, simulations of straight-line travel on flat ground are performed. In addition, to investigate the effects of rotatable tracks, a straight-line travel simulation with tracks fixed is also performed. By analyzing the simulation results, the motion features and dynamic characteristics of a four-tracked DSMV with rotatable tracks when traveling in a straight line on flat ground can be studied. [ABSTRACT FROM AUTHOR]

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The differential steering can be used not only as the backup system of steer-by-wire, but also as the only steering system. Because the differential steering is realized through the differential moment between the coaxial left and right driving wheels, the sharp reduction of the load on the inner driving wheel will directly lead to the failure of the differential steering when the four-wheel independent drive electric vehicle approaches the rollover. Therefore, this paper not only realizes the trajectory tracking of autonomous ground vehicle through the differential steering, but also puts forward the body attitude control to improve the handling stability. Firstly, the dynamic and kinematic models of differential steering autonomous ground vehicle (DSAGV) and its roll model are established, and the linear three-degree of freedom vehicle model is selected as the reference model to generate the ideal body roll angle. Secondly, a model predictive controller (MPC) is designed to control the DSAGV to track the given reference trajectory, and obtain the required differential moment and the resulting front-wheel steering angle. Then, a sliding mode controller (SMC) is adopted to control the DSAGV to track the ideal body roll angle, and obtain the required roll moment. The simulation results show that the proposed MPC and SMC can not only make the DSAGV realize the trajectory tracking, but also achieve the body attitude control. [ABSTRACT FROM AUTHOR]

Vehicle mass is an important parameter for motion control of intelligent vehicles, but is hard to directly measure using normal sensors. Therefore, accurate estimation of vehicle mass becomes crucial. In this paper, a vehicle mass estimation method based on fusion of machine learning and vehicle dynamic model is introduced. In machine learning method, a feedforward neural network (FFNN) is used to learn the relationship between vehicle mass and other state parameters, namely longitudinal speed and acceleration, driving or braking torque, and wheel angular speed. In dynamics-based method, recursive least square (RLS) with forgetting factor based on vehicle dynamic model is used to estimate the vehicle mass. According to the reliability of each method under different conditions, these two methods are fused using fuzzy logic. Simulation tests under New European Driving Cycle (NEDC) condition are carried out. The simulation results show that the estimation accuracy of the fusion method is around 97%, and that the fusion method performs better stability and robustness compared with each single method. [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]

In complex driving scenarios, automated vehicles should behave reasonably and respond adaptively with high computational efficiency. In this paper, a computational efficient motion planning method is proposed, which considers traffic interaction and accelerates calculation. Firstly, the behavior is decided by connecting the points on the unequally divided road segments and lane centerlines, which simplifies the decision-making process in both space and time span. Secondly, as the dynamic vehicle model with changeable longitudinal velocity is considered in the trajectory generation module, the C/GMRES algorithm is used to accelerate the calculation of trajectory generation and realize on-line solving in nonlinear model predictive control. Meanwhile, the motion of other traffic participants is more accurately predicted based on the driver's intention and kinematics vehicle model, which enables the host vehicle to obtain a more reasonable behavior and trajectory. The simulation results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In order to improve the safety and reliability of the hypersonic flight vehicle, a sliding mode observer-based fault detection scheme is applied in this paper to handle the actuator fault detection issue, including stuck fault detection and PLOE fault detection. A dynamic linear model with uncertainty is first derived from the original nonlinear hypersonic flight vehicle model by using Taylor's linearization approach at the equilibrium point. Secondly, the actuator fault model, reflecting stuck faults and PLOE faults, is constructed. Then, a sliding mode-based fault detection observer, considering system decomposition, is developed based on the linearized hypersonic flight vehicle model. At last, the designed sliding mode observer is applied to the original nonlinear hypersonic flight vehicle for single-input, single-style actuator fault detection. The simulation results show that stuck faults and big proportion PLOE faults can be timely and accurately detected at the fault time, and the stuck actuator fault from input 3 can cause a deadly impact to the hypersonic flight vehicle, which deserves much more attention than the actuator faults from the other three inputs. Meanwhile, the detection of a small proportion of PLOE faults encounters some difficulties and needs special attention and further investigation. [ABSTRACT FROM AUTHOR]

The present paper is concerned with the wayset-based guidance of underactuated multirotor aerial vehicles (MAVs). A hierarchical guidance and control structure is first established, in which the guidance is realized as a supervisory loop. The lower-level stabilizing attitude and position control laws are assumed to be available. On the other hand, the outer-loop guidance is designed based on a fixed-horizon tube-based robust model predictive control (MPC), which conducts the MAV to visit a given sequence of waysets, without violating their state and control bounds, and allowing the vehicle to rest in each wayset for a specified period. The MPC is designed using a reduced-order closed-loop dynamic model describing the vehicle's translation, which is derived considering the stabilizing position and attitude control laws and the assumption of a time-scale separation between the closed-loop translational and rotational dynamics. This model is put into a discrete-time linear state–space representation subject to additive bounded random disturbance and measurement noise. The properties of the proposed method, which includes the MPC recursive feasibility and robust stability as well as the overall guidance feasibility, are analytically studied. The method is also numerically evaluated using a realistic quadrotor dynamic model, showing its effectiveness and confirming its properties. • Wayset-based supervisory guidance loop for underactuated multirotor aerial vehicles. • Wayset transitions based on dual-mode tube-based robust model predictive control. • Proof of recursive feasibility, robust stability, and overall guidance resolvability. • Obtained performance and low computational burden encourage real-time implementation. [ABSTRACT FROM AUTHOR]

Based on the predigestion of the dynamic model of the intelligent firefighting vehicle, a linear 2‐DOF lateral dynamic model and a preview error model are established. To solve the problems of a highly non‐linear vehicle model, time‐varying parameters, output chattering, and poor robustness, the Radial Basis Function neural network sliding mode controller is designed. Then, different driving speeds are used to conduct simulation tests under standard double‐shifting and smooth curve road conditions, and the simulation results are used to analyse the tracking effect of the lateral motion controller on the desired path. The simulation results reveal that the controller designed has high accuracy in tracking the desired path and has good robustness to the disturbance of intelligent firefighting vehicle speed changes. [ABSTRACT FROM AUTHOR]

A path following control strategy for a four-wheel-independent-drive electrical vehicle (4WID-EV) based on backstepping and model predictive control is presented, which can ensure the accuracy of path following and maintain vehicle stability simultaneously. Firstly, a 2-DOF vehicle dynamic model and a path following error model are built and the desired yaw rate is obtained through backstepping. Then, a model predictive controller is adopted to track the desired yaw rate and obtain the optimal front wheel steering and external yaw moment. Meanwhile, an optimal torque distribution algorithm is carried out to allocate it to each tire. Finally, the effectiveness and superiority of the strategy is validated via CarSim–Simulink joint simulation. Results show that the strategy has higher following accuracy, smaller sideslip angle, and better yaw rate tracking. [ABSTRACT FROM AUTHOR]

To improve the multidirectional motion control accuracy and driving stability of Distributed Drive Autonomous Vehicles (DDAVs) under extreme conditions, the extreme speed estimation method based on dynamic boundary and the multidirectional motion coupling control law design method based on multi degrees of freedom vehicle dynamic model are proposed. The extreme speed estimation method identifies the stable state of DDAVs by the dynamic boundary composed of yaw rate, sideslip angle and roll angle, and then estimates the extreme speed of the vehicle. The design method of multidirectional motion coupling control law adopts eight-degrees-of-freedom (8-DOF) vehicle dynamic model to design path tracking control law, speed tracking control law, yaw stability control law, and active suspension control law at the same time, so as to realize multidirectional motion coupling control. Based on the above method, the Multidirectional Motion Coupling Control System (MMCCS) of DDAVs is designed. The effectiveness of the proposed method is verified by double-line-shifting and serpentine driving simulations under different road adhesion conditions. The superiority of the method is proved by comparing the existing integrated control method. [ABSTRACT FROM AUTHOR]

Rule-based traditional motion planning methods usually perform well with prior knowledge of the macro-scale environments but encounter challenges in unknown and uncertain environments. Deep reinforcement learning (DRL) is a solution that can effectively deal with micro-scale unknown and uncertain environments. Nevertheless, DRL is unstable and lacks interpretability. Therefore, it raises a new challenge: how to combine the effectiveness and overcome the drawbacks of the two methods while guaranteeing stability in uncertain environments. In this study, a multi-constraint and multi-scale motion planning method is proposed for automated driving with the use of constrained reinforcement learning (RL), named RLTT, and comprising RL, a topological reachability analysis used for vehicle path space (TPS), and a trajectory lane model (TLM). First, a dynamic model of vehicles is formulated; then, TLM is developed on the basis of the dynamic model, thus constraining RL action and state space. Second, macro-scale path planning is achieved through TPS, and in the micro-scale range, discrete routing points are achieved via RLTT. Third, the proposed motion planning method is designed by combining sophisticated rules, and a theoretical analysis is provided to guarantee the efficiency of our method. Finally, related experiments are conducted to evaluate the effectiveness of the proposed method; our method can reduce 19.9% of the distance cost in the experiments as compared to the traditional method. Experimental results indicate that the proposed method can help mitigate the gap between data-driven and traditional methods, provide better performance for automated driving, and facilitate the use of RL methods in more fields. [ABSTRACT FROM AUTHOR]

To improve the overall performance of four-wheel steering vehicles under different working conditions and solve the problem of the unbalanced comprehensive control effect of a single controller, a multi-mode optimal decision control system is proposed based on the linear 2-DOF dynamic model of the vehicle, which can make the vehicle have better performance under different working conditions. The system is composed of multiple controllers, in which the self-tuning dual yaw rate feedback controller can create timely feedback and make adjustments according to the driving state of the vehicle, which is optimal under the condition of a small rotation angle at medium and high speeds. The system can match the corresponding controller according to the optimal performance of different control strategies at different speeds and angles. The simulation results show that the multi-mode optimal selection system can make the vehicle perform optimally under different working conditions, and that comprehensive performance is more prominent than that of a single controller. [ABSTRACT FROM AUTHOR]

As a vital means of transportation to alleviate urban traffic congestion, the metro vehicle has been developing rapidly in China during recent years. For the violent vibration and shock under the frequent switches between traction and braking conditions, higher requirements are put forward in the drive system. The dynamic performance of the traction motor and gearbox, which are the key elements in the drive system of the metro vehicle, is worthy of attention. Based on the classical vehicle–track coupled dynamics and the gear dynamics theory, a vertical–longitudinal dynamics model for a metro vehicle with frame-hung motors and gearboxes is developed in this paper. This model enables the consideration of some complicated excitations, such as external excitations (the track vertical irregularity) and internal excitations (the mesh stiffness and the dynamic transmission error). The established dynamics model is then validated by comparing the simulated results with the field test results in both time domain and time–frequency domain under traction conditions. Consequently, the established dynamics model is demonstrated to be capable of revealing the dynamic performance of the metro vehicle effectively, especially for the traction and transmission system in the entire vehicle vibration environment of a metro. In turn, the results indicate that the gear transmission has a great and lasting effect on the force state of the traction motors and gearboxes compared to its effect on the axle load transfer. [ABSTRACT FROM AUTHOR]

This study proposes an improved dynamic substructuring model using the estimated frequency response function information at coupling points between substructures. An assembled system generally consists of two or more substructures connected by a bolt. Individual substructure evaluation excluding the effects of other components is important in the development stage of a general mechanical system because the vibro-acoustic performance of the system depends on the specific combination of substructures. Therefore, this study predicted the final coupling system performance using information from the initial evaluation of the individual substructures. Accurate measurements of the joint properties are required to accurately estimate the dynamic assembled system characteristics; however, physical constraints typically limit such measurements at actual coupling points. Accordingly, a method that utilizes generalized coupling properties to estimate the dynamic characteristics of a new coupling system based on the characteristics of an original substructure is proposed. Virtual point transformation is then used to estimate accurate frequency response functions at the coupling points of the assembled system based on convenient measurements. The proposed method was validated using a vehicle suspension that was hard mounted in a test jig and onto an actual vehicle body to estimate the vibration characteristics of the assembled system. The findings of this study contribute to the accurate estimation of the dynamic properties of many real-world bolt-assembled systems. [ABSTRACT FROM AUTHOR]

An advanced LKS (lane keeping system) for use on curving roads is presented to maintain autonomous vehicle driving within the target lane, without unintentional lane departure. There are the following two main objectives in designing this system: one is performing perfect lane keeping and the other is ensuring the dynamic stability of the vehicle, especially when driving on a curving and low-friction road with time-varying high speed. In this paper, a combined vehicle model, consisting of a lane keeping model and a vehicle lateral dynamic model, is firstly introduced. Then, a novel adaptive-weight predictive controller is used to calculate the desired steering angle and the additional yaw moment which provide coordinated control forlane keeping and dynamic stability control. Meanwhile, a square-root cubature Kalman filter-based vehicle sideslip angle observer, with a strong tracking theory modification (ST-SRCKF), is established to estimate the sideslip angle during the driving process. Finally, HIL (hardware-in-the-loop) tests and field tests are constructed, and the results show the effectiveness of our proposed LKS controller and ST-SRCKF sideslip angle estimation. [ABSTRACT FROM AUTHOR]

To enhance vehicle stability and safety, the four-wheel independent steer-by-wire (4WISBW) system has garnered significant attention. However, the characteristics of corner modules, including model parameters uncertainty and disturbance torque, directly contribute to the deterioration of dynamic response in tracking control. And the differences in the characteristics leading to reduced synchronization performance in the 4WISBW system and hindering effective coordination. To enhance the synchronization and tracking control performance of the 4WISBW system, a novel control strategy, coupled with the fictitious master-generalized mean deviation coupling structure (FMGMDCS), is proposed. Firstly, the corner module dynamic model and the vehicle dynamic model are established. Subsequently, the impact of the differences in the characteristics on the system's tracking and synchronization control is analyzed. Next, the FMGMDCS and the angle synchronization controller based on a new reaching law sliding mode control (NRLSMC) are proposed to compensate for synchronization errors in the 4WISBW system caused by the differences in the characteristics of corner modules. Finally, a radial basis function neural network fast terminal sliding mode control (RBF-FTSMC) steering angle tracking controller is designed to enhance the tracking performance of corner modules. Simulation and experimental results indicate that the proposed control strategy can effectively solve the synchronization problem of the 4WISBW system and improve the system's tracking performance. [ABSTRACT FROM AUTHOR]

The goal of this work is the development of a general nonlinear single-track model for the cases of curved flat or banked road paths and the identification of the fundamental "handling bricks" or vehicle "DNA", extending an existing theory for flat road tracks. The handling bricks are related to specific design parameters of the vehicle. It is confirmed (both theoretically and numerically), that two structurally different vehicles, with the same handling bricks, exhibit very similar or identical handling behavior. The current nonlinear model accepts general steering input, and arbitrary axle characteristic functions and can be used for general (flat or banked) road tracks. If necessary, various types of constraints can be easily enforced, linking the dynamic parameters of the model. For example, given a complex steering input, the vehicle's (center of gravity) velocity and (or) the vehicle heading, can be related to the direction of the banked road path. On the other hand, the road path can be given independently of the steering data to check the deviation between the intended and the obtained road paths. An implicit nonlinear Crank-Nicolson time marching technique (with additional internal iterations at each time step), has been developed and implemented for the set of (nonlinear) ordinary differential equations (in a homemade VBA framework). The numerical results, using magic formula-based axle characteristic functions, confirm the robustness of the model formulation. • Development of a general nonlinear single-track model. • Identification of the fundamental "handling bricks" or vehicle "DNA". • Applications in curved flat or banked road paths. • General steering input and arbitrary axle characteristic functions. • Development of a novel implicit nonlinear Crank-Nicolson time marching technique. [ABSTRACT FROM AUTHOR]

• A navigation accuracy compensation algorithm for INS is proposed for low-cost USVs. • An event-triggering mechanism is introduced, and the thrust models of the USVs are adopted to design the event trigger. • According to different events, various weights can be assigned to various integrators and PF. • Field experiments are conducted to verify the navigation performance of our algorithm. Integrated navigation is often used for navigation of unmanned surface vehicles (USVs). For a class of cost-sensitive USVs, it is desirable to compose integrated navigation by low-cost inertial navigation systems (INS) and global positioning systems (GPS). In the cases of GPS signal failure or interference, only INS onboard can be used for navigation, which often leads to the navigation accuracy deteriorating and may fail to meet application requirements. Therefore, a navigation accuracy compensation algorithm for low-cost USVs is proposed. An event-triggering mechanism is introduced, and the thrust models of the USVs are adopted to design the event trigger. According to different events, various weights can be assigned to the integrator based on INS, and measurement-based linear velocity V INS and heading angle ψ I N S can be obtained. Moreover, based on dynamic models, the model-based linear velocity V m and heading angle ψ m also can be calculated. Meanwhile, the event trigger is combined with the Particle Filter (PF) algorithm to accurately estimate the linear velocity V ^ P F and heading angle ψ ^ PF for navigation. Finally, field experiments are conducted and the differential GPS (DGPS) is used as the benchmark for comparison. The results show that our algorithm can improve navigation performance for the low-cost USVs. [ABSTRACT FROM AUTHOR]

Reverse Horizontal Curves (RHCs) are among the most accident-prone road points, with many annual fatalities and injuries. These fatalities can increase dramatically if the RHCs and longitudinal slopes are combined. The importance of increasing the safety of RHCs, especially in mountainous routes, is doubled due to the possibility of combining RHCs with vertical extensions or combining them with so-called steep slopes. This study used vehicle dynamic modeling to evaluate the lateral friction of various vehicles. Including the E-Class Sedan, E-Class SUV, Truck, and Bus, moving on RHCs combined with a longitudinal slope (downgrade, upgrade, and direct distance). Then, the RHC lateral friction model was presented using the multiple regression model based on the effective parameters, including design speeds, direct distance, and different longitudinal slopes. The results showed that speed, longitudinal slope, and vehicle type had the most impact, and direct distance had the most negligible impact in friction coefficient models. Based on the modeling results, the higher the design's speed and the shorter the direct distance, the lower the lateral friction coefficient for the Sedan and SUV. Hence, the safety of the vehicles is greater. For trucks, reduced speed, increased direct distance, and reduced slope led to increased safety. In the results, the most critical state was the lateral friction coefficient at a speed of 80 km/h and a direct distance of 116 m for the SUV. [ABSTRACT FROM AUTHOR]

In this work a parameter optimization method is applied to determine the best values of damping and stiffness properties which will minimize the magnitude of the vertical acceleration of the ambulance stretcher. Thus, an 8-DOF vehicle dynamic model was developed to be used for the parameter optimization method. Subsequently, the results obtained by the model were compared to a full vehicle multi-body model of Carsim software. Damping and stiffness properties, which are obtained by a parameter optimization method, contribute to reducing the magnitude of the vertical acceleration of the ambulance stretcher. The approach developed in this study provides sources for designing a mechanism to reduce the vertical acceleration to which the patient is exposed during transportation in an ambulance. [ABSTRACT FROM AUTHOR]

• Based on the variable wheelbase characteristics, this study examines the impact of wheelbase changes on the response characteristics of sideslip angle and heading angle relative to the front wheel angle. • A control strategy for adaptive heading tracking is formulated by adjusting the wheelbase under different working conditions. • Considering the influence of noise interference and time delay, a robust active disturbance rejection control (r-ADRC) method is proposed by combining ADRC with a robust term. • A torque distribution method for tire load rate is utilized, and the real-time vertical load of each wheel is calculated, taking into account the change in wheelbase. • The theory of wheelbase-changing and heading tracking strategy are verified through co-simulation of the UGV and experiments of the scaled prototype. In order to fully exploit the variable wheelbase characteristics of the unmanned ground vehicle (UGV) with variable configuration, this paper proposes an adaptive heading tracking control strategy based on wheelbase changes. This strategy involves adjusting the wheelbase according to different working conditions to optimize various driving performance aspects. Firstly, the impact of changing wheelbase on the response characteristics of sideslip angle and heading angle relative to the front-wheel steering angle is analyzed by using a lateral vehicle dynamic model. The configurations where the 2nd axle moves forward by 0.5 m, remains unchanged, and moves backward by 0.5 m are defined as the 'stable configuration', 'balanced configuration', and 'maneuverable configuration', respectively. Considering time lag effects of hydraulic systems and external random noise interference, a robust-active disturbance rejection control (r-ADRC) method is developed by incorporating a robust term into active disturbance rejection control (ADRC) in order to achieve desired front-wheel steering angle. Additionally, a torque distribution method based on the tire load rate and the real-time vertical load of each wheel is applied to ensure uniform tire wear and enhance longitudinal driving stability. Finally, simulations under various typical working conditions as well as scaled prototype experiments are conducted, and both the theory behind the changing wheelbases and the effectiveness of proposed control strategy are verified. According to different vehicle configurations and mission requirements, the maneuverability and stability of the ground unmanned vehicle are ensured respectively. [Display omitted] [ABSTRACT FROM AUTHOR]

The vertical alignment design method of road in scenic spots does not evolve enough along the vehicle's rapid variation. Values of the maximum longitudinal slope (MLS) and longest slope length (LSL) applicable to scenic roads used by the environmental-friendly vehicle (EFV) are not provided. To compensate for this shortage, a multibody vehicle dynamic model in uphill traving is built, providing the static equilibrium state and dynamic balancing process of a typical vehicle. MLS and LSL values in scenic roads are obtained based on this model through numerical simulation, considering typical EFV, maximum velocity loss (MVL), and ideal velocity loss (IVL). Field experiments for verifying the results are also carried out in Huashan Mountain, Cuihua Mountain National Park, and Taiping Forest Park, using two EFV types. MLS and LSL values in scenic roads applicable to EFV obtained in this research vary from 7.8% to 10.2% and 200 to 955 m, respectively, and both are larger than the corresponding values in current criteria. According to verification results, relative errors of climbing velocity vary from 0.0104 to 0.0205, showing the dynamic model's accuracy and further proving the practicality of MLS and LSL values obtained. The results obtained in this research lay a foundation for establishing the scenic-road vertical alignment design method. [ABSTRACT FROM AUTHOR]

Straddle-type monorail, as a unique technology, energy saving and environmental protection, is different from the subway of urban rail transit system. In order to study the curving performance of a new type of the straddletype monorail vehicle with single-axle bogies, the three-dimensional spatial dynamics model which consists of the vehicle model and track model designis proposed by the multibody dynamics soft ADAMS. The monorail vehicle dynamic model which consists of three types of tire -track contact model and the nonlinear model of the horizontal stop is established. Based on the dynamic model, the influences such as pre pressure and curve super-high rate parameters of the curve passing for the dynamic characteristics are discussed. The simulation results show that the suitable preload for the guide and stabilizer tires of straddle-type vehicle with single-axle bogies is 5KN and after selecting the appropriate pre-pressure, the super-high rate is recommended to be 8%-10%. [ABSTRACT FROM AUTHOR]

The ride comfort and the cargo safety are of great importance in the vibration design of heavy-duty vehicle. Traditional ride comfort design method based on the response of components of vehicles or interaction between human and seat overlooks the most direct criterion, the response of occupants, which makes the optimisation not targeted enough. It will be better to conduct the ride comfort design with the biodynamic response of driver. To this end, a 17-degrees-of-freedom (DOFs) vertical-pitch-roll vehicle dynamic model of a three-axle heavy-duty truck coupled with a 7 DOFs human model is developed. The ride comfort of human body under the vertical, the pitch, and the roll vibrations can be evaluated with the weighted root-mean-square (r.m.s.) acceleration of the driver in multiple directions. The flexibilities of chassis and carriage are also considered to improve the accuracy of the prediction of the ride comfort and to constrain the mounting optimisation of cab and carriage. After validation, the sensitivity analysis of the mounting system, the suspensions, and arrangement of sprung masses is carried out and significant factors to ride vibration are identified. The optimal combination of design parameters is obtained with the objective of minimizing the vibration of the driver and carriage simultaneously. The optimisation result shows that the weighted driver vibration is reduced by 27.9% and the carriage vibration is reduced by 31.8% at various speeds. [ABSTRACT FROM AUTHOR]

Further research on motion control of a 4WS4WD path-following vehicle is carried out in this paper. Focuses are placed on understanding and testing the vehicle path-following control models developed previously at a deep level. Control models are in relation to parameters introduced, and the effects of these parameters are discovered. Control models are interpreted by dynamic simulation using a 3DOF vehicle model with three cases. Three kinds of planned paths are considered in these cases to test control performances, which include the straight, circular, and sinusoidal paths. Interesting dynamic results are obtained and analyzed qualitatively, e.g., various steering modes. Simulation studies are extended with consideration of a fine vehicle dynamic model established in CarSim and a complex path composed of straight and curved segments. Control models are examined in a complex problem, and results obtained show that they are validated with robustness in dynamic environment. [ABSTRACT FROM AUTHOR]

To assess the effect of the mass-stiffness distribution of the cab and vibratory roller on the ride quality, the acceleration-frequency characteristics of the isolation systems are researched based on the nonlinear dynamic model of the vehicle. The complex domain is used to solve the vibration equations in the frequency region. The effect of the mass and stiffness parameters of the cab and vehicle is then analyzed via MATLAB software. The research results show that the resonant frequency of the cab's isolations and their acceleration-frequency is insignificantly affected by the mass-stiffness distributions in the case of without the excitation of the vibrator drum. Conversely, under an excitation 28 Hz of the vibrator drum, the mass-stiffness distributions strongly affect on the acceleration-frequency of the cab isolations, especially, when increasing the stiffness coefficient and reducing the cab mass with α = 1.5, the vehicle’s ride quality and structural durability of the vibratory rollers are greatly improved. [ABSTRACT FROM AUTHOR]

An optimized control approach for the distributed cooperative vehicular platoon was proposed in this paper, considering actuator delay and nonideal communication condition. A hierarchical structure is used to model the vehicular platoon, where the desired acceleration is optimized by CACC controller and the longitudinal tracking controller is proposed to follow it. In the design process of CACC controller, a parameter space approach and linear quadratic regulator (LQR) method are applied to guarantee the string stability and optimized performance. The influence of communication time delay and dropout rate is revealed by the changing of string stable region. Analytical results are verified by numerical simulations of a six-vehicle platoon where the leading vehicle follows the FTP-75 drive cycle speed profile. Furthermore, a Hardware-in-the-Loop (HIL) test is carried out with Carsim to simulate a high-fidelity vehicle dynamic model and dedicated short range communication (DSRC) modems as hardware in the loop as well as the control unit to achieve the inter-vehicle communication. The results show that the designed CACC platooning controller exhibits favorable performance in highway driving scenarios. The platooning vehicles display excellent car-following behavior with high accuracy, driving comfort and safety. [ABSTRACT FROM AUTHOR]

Absorption of impact energy by the passive safety elements of the vehicle body is the basic feature to ensure conditions of safety for the driver and passengers in transport. The parts especially designed for this objective in the self-supporting car body are longitudinals. Their energy-absorbing features are designed in different ways. Evaluation of the degree to which the vehicle (body) ensures safety during a collision is difficult and expensive. Usually, tests under impact conditions are required. The most advanced and costly are the tests carried out on a complete vehicle (whole real object for tests). Whole vehicle testing can be replaced by testing of individual car body elements (for example longitudinal). The main aim of this article is to present and compare the results of dynamic studies on model energy-consuming objects (new model longitudinals and model longitudinals repaired with welding methods). For the purpose of this study, models of vehicle passive safety elements (model longitudinals) were designed. On the basis of the conducted tests, it was found that it is worth considering the replacement of collision tests of the whole vehicle by tests of its individual components. This can be considered a new approach that is not widely used. Currently, most often, crash tests of entire vehicles are conducted (high costs) or computer simulations are performed (often with unsatisfactory accuracy). [ABSTRACT FROM AUTHOR]