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A simulation investigation of emergency evasive maneuvers of the type experienced during obstacle avoidance is conducted for long combination vehicles at highway speeds. The dynamic model includes a commercial truck with a configuration that is typical of what is used in the U.S., with two 28-ft trailers connected to the tractor through a fifth wheel, and to each other by an A-dolly. The model is validated against test data and used for evaluating distance and time needed to safely perform a steering maneuver to avoid an obstacle on the road. The simulation results indicate a significant difference in both the required time and distance for safely exercising an emergency obstacle avoidance, ranging from approximately 151–276 ft in distance and 1.7–2.4 s from the start of the driver action. The reaction time of the driver will add to both measures by an amount corresponding to the lapse in time between the moment the driver recognises the obstacle and when a steering action is initiated. To the extent that the lighting and road condition add to the reaction time, a significantly larger distance and longer time are needed during nighttime driving as compared with daytime, under similar road and loading conditions. [ABSTRACT FROM AUTHOR]

In this article, the development of a bat-ray-inspired underwater vehicle is presented; although the propulsion of the vehicle is based on traditional thrusters, the shape of the ray's fins was used as a model to design the body of the vehicle; this architecture allows the independent control of the forward velocity and the full attitude of the vehicle using only two thrusters and two articulated fins. The compact design of the robot, along with the high dexterity of the architecture, allows the vehicle to submerge and emerge vertically as well as navigate horizontally. The mathematical model of the proposed vehicle, including dynamics and propulsion system, is presented and validated using numerical simulations. Finally, experimental tests are presented to demonstrate the capabilities of the proposed design. [ABSTRACT FROM AUTHOR]

During loading and driving, the wheels bear the vertical load from the body mass and the excitation load generated by uneven road surface on the one hand, and bear the driving torque on the other hand. The load-bearing methods of wheels are generally divided into bottom load-bearing and top load-bearing. This paper describes the structural characteristics of the track system of the articulated track vehicle and the interaction relationship between the main components of the track system. Finite element calculation is carried out based on ANSYS software to obtain the stress distribution of each key component under various loading methods. It can be seen from the results that all key components of the track system can meet the strength and rigidity requirements; although there are also areas with large local stress, they are all within the safe range, which is mainly caused by stress concentration. Safe life is obtained through fatigue analysis. [ABSTRACT FROM AUTHOR]

The electrification of towing and trailing units creates new torque allocation alternatives among different units of articulated heavy vehicles. To increase the power and energy efficiency, control algorithms can request propulsion or regenerative braking from a single unit while keeping the other units unbraked or unpropelled. However, this may lead to safety problems, such as jackknifing or trailer swing. This paper uses a high-fidelity simulation tool to formulate safe operating envelopes for a tractor and semitrailer combination for braking-in-turn cases. The effects of different vehicle and environment parameters on the safe operating envelope are studied. The safe operating envelope obtained is then validated using real vehicle tests and can be used with any control algorithm to avoid requesting unsafe unit force combinations. [ABSTRACT FROM AUTHOR]

Articulated heavy vehicles exhibit poor lateral stability, which may lead to unstable motion modes, e.g., trailer-sway and jackknifing, causing severe accidents. Varying relevant vehicle parameters improves the static stability but degrades the dynamic stability. The past studies focused either on the static or dynamic stability alone. However, little attention has been paid to exploring the trade-off between the static and dynamic stabilities. To gain design insights for active safety systems for AHVs, this article studies this trade-off systematically. To this end, a systematic method is proposed to conduct the linear stability and trade-off analysis. To implement and demonstrate the proposed method, a linear three-degrees-of-freedom yaw-plane model is generated to represent a tractor/semi-trailer. A trade-off analysis is conducted considering two tractor rear-axle configurations and three trailer payload arrangements. In each case, simulation is performed in both steady-state and transient testing maneuvers. To validate the linear stability analysis based on the linear yaw-plane model, two nonlinear TruckSim models are introduced, and the corresponding simulation is conducted. Insightful understanding of the trade-off is gained through analyzing the simulation results, and the linear stability analysis will provide valuable guidelines for the design and development of active safety systems for AHVs. [ABSTRACT FROM AUTHOR]

Featured Application: This paper proposes a computationally efficient algorithm for base placement in automatic multi-robot vehicle painting. The proposed algorithm incorporates the CAD model of the vehicle the manufacturer is interested in painting and the kinematic parameters of the robotic manipulators (e.g., their Denavit–Hartenberg parameters). The algorithm computes the robot's optimal fixed base positions. The base positions can subsequently be utilized by already available robotic path/motion planners. This paper investigates the problem of optimal base placement in collaborative robotic car painting. The objective of this problem is to find the optimal fixed base positions of a collection of given articulated robotic arms on the factory floor/ceiling such that the possibility of vehicle paint coverage is maximized while the possibility of robot collision avoidance is minimized. Leveraging the inherent two-dimensional geometric features of robotic car painting, we construct two types of cost functions that formally capture the notions of paint coverage maximization and collision avoidance minimization. Using these cost functions, we formulate a multi-objective optimization problem, which can be readily solved using any standard multi-objective optimizer. Our resulting optimal base placement algorithm decouples base placement from motion/trajectory planning. In particular, our computationally efficient algorithm does not require any information from motion/trajectory planners a priori or during base placement computations. Rather, it offers a hierarchical solution in the sense that its generated results can be utilized within already available robotic painting motion/trajectory planners. Our proposed solution's effectiveness is demonstrated through simulation results of multiple industrial robotic arms collaboratively painting a Ford F-150 truck. [ABSTRACT FROM AUTHOR]

At present, most of the turbofan engine use the articulated link mount to connect the engine to the wing. The mechanical modeling, analysis and experimental research of articulated link mount are important means in the development of engine mount. In this paper, multibody dynamics method is used to establish the dynamic theory equation for a certain type of turbofan engine mount, and the low-frequency approximation method of the MNF file is proposed, which greatly improves the calculation speed on the basis of ensuring the calculation accuracy. In addition, a full-scale engine mounting system vibration isolation performance test platform was developed, and the vibration isolation efficiency of a certain type of engine mount at the high and low pressure rotor frequency was obtained. The results show that the simulation and test results agree well, the error is within 15% at the low-frequency, and 5% at the high-frequency. This work provides theoretical method and test evaluation means for the design and improvement of large passenger aircraft engine installation devices. [ABSTRACT FROM AUTHOR]

A controller is proposed to guide a multi-articulated robot vehicle (MARV) moving backwards, following a certain path. The ability to avoid fixed and moving obstacles is included, using the null space-based control technique to manage the conflicting tasks of following a path and avoiding obstacles. Additionally, control gains are modulated, thus reducing the risk of jackknifing. These new approaches are the contributions of the article. Results of laboratory-scale experiments with a MARV pushing one and two trailers are presented and discussed, which validate the proposed controller. Simulation results are also presented considering a MARV with three trailers, showing that the proposed controller can be adopted for larger articulated chains and another experiment that shows that it is possible to avoid moving obstacles. • Control of a multi-articulated robotic vehicle to follow a path when moving backwards. • Evasive maneuvers to avoid static or dynamic obstacles in the desired path. • Dynamic compensation to reduce the position errors for the rear of the last trailer. • Null space-based control approach hierarchic execution of complimentary subtasks. • Controller gain modulation as a tool to reduce the possibility of jackknife. [ABSTRACT FROM AUTHOR]

This paper introduces a novel fuzzy logic switched model predictive control (MPC) algorithm for articulated steering vehicles, addressing significant path tracking challenges due to varying road conditions and vehicle speeds. Traditional single-model and parameter-based controllers struggle with tracking errors and computational inefficiencies under diverse operational conditions. Therefore, a kinematics-based MPC algorithm is first developed, showing strong real-time performance but encountering accuracy issues on low-adhesion surfaces and at high speeds. Then, a 4-DOF dynamics-based MPC algorithm is designed to enhance tracking accuracy and control stability. The proposed solution is a switched MPC strategy, integrating a fuzzy control system that dynamically switches between kinematics-based and dynamics-based MPC algorithms based on error, solution time, and heading angle indicators. Subsequently, simulation tests are conducted using SIMULINK and ADAMS to verify the performance of the proposed algorithm. The results confirm that this fuzzy-based MPC algorithm can effectively mitigate the drawbacks of single-model approaches, ensuring precise, stable, and efficient path tracking across diverse adhesion road conditions. [ABSTRACT FROM AUTHOR]

The path tracking control of electric mining articulated vehicles (EMAVs), critical equipment commonly used for mining and transportation in underground mines, is a research topic that has received much attention. The path tracking control of EMAVs is subject to several system constraints, including articulation angle and articulation angular velocity. In light of this, many researchers have initiated studies based on model predictive control (MPC). The principal design schemes for existing MPC methods encompass linear MPC (LMPC) utilizing a single reference point, so named the single reference point LMPC (SRP-LMPC), and nonlinear MPC (NMPC). However, NMPC exhibits suboptimal real-time performance, while SRP-LMPC demonstrates inferior accuracy. To simultaneously improve the accuracy and real-time performance of the path tracking control of EMAV, based on the SRP-LMPC, a path tracking control method for EMAV based on nonlinear compensated multiple reference points LMPC (MRP-LMPC) is proposed. The simulation results demonstrate that MRP-LMPC simultaneously exhibits a commendable degree of accuracy and real-time performance. In all simulation results, the displacement error amplitude and heading error amplitude of MRP-LMPC do not exceed 0.2675 m and 0.1108 rad, respectively. Additionally, the maximum solution time in each control period is 5.9580 ms. The accuracy of MRP-LMPC is comparable to that of NMPC. However, the maximum solution time of MRP-LMPC can be reduced by over 27.81% relative to that of NMPC. Furthermore, the accuracy of MRP-LMPC is significantly superior to that of SRP-LMPC. The maximum displacement and heading error amplitude can be reduced by 0.3075 m and 0.1003 rad, respectively, representing a reduction of 65.51% and 73.59% in the middle speed and above scenario. [ABSTRACT FROM AUTHOR]

In this article, we consider the equations of motion for an articulated n$$ n $$‐trailer vehicle with different masses and inertias in the presence of force and torque commands. We design a second‐order optimal filter to estimate the pose of the first vehicle and of the trailers exploiting the Lie group structure and the nonholonomic and hooking constraints. We consider the filtering problem from three different perspectives: in the first masses and inertias are time‐varying and perfectively known, in the second they are known only in the first part of the maneuver, but they are not updated over time. In the last case masses and inertias are considered within the state vector and therefore estimated by the filter. Depending on the needs in real‐life applications (e.g., whether the masses and inertias remain fixed or change during the maneuver and are unknown), the best‐performing filter can be used. The sensing system consists of a GPS‐like configuration (global positioning system) obtained by using an antenna attached to the leading car. [ABSTRACT FROM AUTHOR]

Trajectory-following control is the basis for the practical application of an articulated virtual rail train transportation system. In this paper, a planar nonlinear dynamics model of an articulated vehicle is derived using the Euler–Lagrange method. A trajectory-following control strategy based on the first following point is proposed, and a feedback linearization control algorithm is designed based on the vehicle dynamics model to achieve the trajectory following of the rear vehicle. Based on the target trajectory formed by the first following point and measured by virtual sensors, a vector analysis method grounded in geometric relationships is proposed to solve in real time for the desired position, velocity, and acceleration of the vehicle. Finally, a MATLAB/SIMPACK dynamics virtual prototype is established to test the vehicle's trajectory-following effectiveness and dynamics performance under lane change and circular curve routes. The results indicate that the control algorithm can achieve trajectory following while maintaining good vehicle dynamics performance. It is robust to variations in vehicle mass, vehicle speed, tire cornering stiffness, and road friction coefficient. [ABSTRACT FROM AUTHOR]

The electrification of commercial vehicles has led to new wheel torque allocation options for propulsion and braking of articulated heavy vehicles. Each unit or axle can be individually braked or propelled whilst the other units or axles are excluded from such action. This may achieve the best energy efficiency. However, this can also lead to potential yaw stability problems such as jackknifing and trailer swing, especially under bad loading and weather conditions. This paper describes the above instabilities and introduces a nonlinear single-track model to study the vehicle dynamics of the tractor-semitrailer combination. The effects of different vehicle and environment parameters are analysed with this vehicle model. A safe operating envelope for limiting the wheel forces is obtained using this vehicle model. Since the vehicle model introduced in this paper is computationally effective, it can be run online in real vehicles, with an instantaneous safe operating envelope obtained for the momentary conditions. Thus, yaw instabilities such as jackknifing and trailer swing may be avoided. [ABSTRACT FROM AUTHOR]

The Virtual Track Train (VTT) represents an innovative urban public transportation system that combines tire-based running gears with rail transit management. Effective control of such a system necessitates precise state estimation, a task rendered complex by the multi-articulated nature of the vehicles. This study addresses the challenge by focusing on state estimation for the first unit under significant interference, introducing a fusion state estimation strategy utilizing Gaussian Process Regression (GPR) and Interacting Multiple Model (IMM) techniques. First, a joint model for the first unit is established, comprising the dynamics model as the main model and a residual model constructed based on GPR to accommodate the main model's error. The proposed fusion strategy comprises two components: a kinematic model-based method for handling transient and high-acceleration phases, and a joint-model-based method suitable for near-steady-state and low-acceleration conditions. The IMM method is employed to integrate these two approaches. Subsequent units' states are computed from the first unit's state, articulation angles, and yaw rates' filtered data. Validation through hardware-in-the-loop (HIL) simulation demonstrates the strategy's efficacy, achieving high accuracy with an average lateral speed estimation error below 0.02 m/s and a maximum error not exceeding 0.22 m/s. Additionally, the impact on VTT control performance after incorporating state estimation is minimal, with a reduction of only 3–6%. [ABSTRACT FROM AUTHOR]

Driving articulated heavy vehicles (AHVs) at high-speeds is complicated due to their unstable motion modes. Accelerated motion trajectory planning is essential for collision avoidance (CA) maneuver in dynamic traffic conditions. This article proposes a new trajectory planning strategy for collision-free and feasible maneuver of a tractor semi-trailer truck in critical conditions in which the truck and the obstacles are moving with non-constant speeds. For this purpose, a convenient optimal practical trajectory for different tire-road frictional conditions, the physical limitation of the tires, and the stability status of the truck is suggested. The main strategy of the trajectory planning is to increase the capability of the control system using the longitudinal and lateral forces of the tires. A robust integrated controller is then proposed to control the longitudinal and lateral directions of the AHV of which the longitudinal controller is configured to track the longitudinal position considering the vehicle stability conditions, and the lateral controller is organized to follow the yaw rate, the lateral position of the tractor, and the articulation angle. The results show that the proposed novel strategy with integrated longitudinal and lateral control has convenient performance in high-speed and low friction conditions as well as normal situations. [ABSTRACT FROM AUTHOR]

The prominent problem of articulated steering structure of engineering vehicle is that there is pressure oscillation in the hydraulic system during steering, which seriously affects the performance of steering system. To solve this problem, the maximum stroke difference of left and right cylinders and the minimum maximum cylinder pressure are the optimization objectives, and the position of cylinder hinge point is the design variable. The multi-objective optimization design of articulated steering system is carried out by using the particle swarm optimization algorithm. After optimization, the maximum pressure of the steering system is reduced by 13.5%, and the oscillation amplitude is reduced by 16%, so the optimization effect is obvious. The dynamic characteristics of the hydraulic steering system under different loads, such as pressure and flow rate, are obtained through field steering tests of wheel loaders. The results show that the load has an important effect on the pressure response of the system, and the causes and influencing factors of pressure and flow fluctuation are determined. The relationship between mileage and hydrogen consumption is obtained, which provides data support for vehicle control strategy. The high-pressure overflow power consumption accounts for 60% of the total work, and the work lost on the steering gear reaches 36 kJ. The test results verify the rationality and correctness of the optimization method of steering mechanism and provide data support for the improvement in steering hydraulic system. [ABSTRACT FROM AUTHOR]

The dynamic behaviors of articulated buses during braking and steering processes are exceedingly complex due to the transmission of various forces and torques by the articulated device. The coupling of forces between the front and rear carriages often renders the bus prone to yaw instability under extreme operating conditions. In this paper, according to the characteristics of the structure and parameter matching of an electrically driven articulated bus, a dynamic model of longitudinal and transverse coupling applied on an articulated bus is established, and the influence of the articulated structure on the yaw stability of the drive vehicle is analyzed. Combined with the relationship between the driving motor, the hinge device, and the vehicle motion, a cruise simulation model of the bus is developed, enabling a comparative analysis and verification of vehicle stability under typical road conditions. The results offer a theoretical foundation for the design and control of highly reliable articulated buses. [ABSTRACT FROM AUTHOR]

Tilt rotor is a thrust force vectoring actuation strategy, mainly employed on aircraft to increase the control degrees of freedom. On multi-rotors, this strategy can be profitable for control purposes in terms of stability and maneuverability. Therefore, the present paper presents the design, model, and control of a 3 DOF tilt-rotor bi-copter test bench. The resulting apparatus is composed of a tilt-rotor bi-copter attached to an articulated arm that enables the vehicle to shift its position vertically, laterally, and rotate about its axis. Therefore, different control strategies for vehicles with tilting capability can be evaluated, ensuring safety and repeatability. In particular, the considered control task consists of tracking position references with proper enforcement of input constraints. For this purpose, a dual-mode control strategy, composed of a linear quadratic regulator and a model predictive controller, is adopted. Experimental results are compared to numerical simulations to corroborate the effectiveness and robustness of the proposed control system in the presence of model uncertainties and external disturbances. [ABSTRACT FROM AUTHOR]

Articulated heavy vehicles (AHVs) play a vital role in the economy of freight transport. Lateral stability control of AHVs during the immediate vicinity to loss of control (LOC) is a significant issue that has not been effectively addressed in the literature. This paper presents a novel approach to the lateral stability control of tractor semi-trailers under conditions leading to LOC. An active auxiliary axle is proposed to prevent trailer swing and snaking during severe lane change maneuvers. A linear 3-DOF model was developed to represent the effectiveness of the active auxiliary axle and tire cornering stiffness in yaw-rate control to provide an analytical basis. Nonlinear modeling of the axle and vehicle system was performed in TruckSIM. A Fuzzy Logic Controller (FLC) was developed to identify the required rate (magnitude per unit time) of actuation force, and a PID controller was introduced to regulate the magnitude of actuation force at the axle-wheel interface. Co-simulation was performed in MATLAB/SIMULINK in combination with TruckSIM. To simulate an LOC on a dry road with a coefficient of friction of 0.85, a double lane change (DLC) maneuver at 90 km/h was conducted. This resulted in a combined state of relative roll-over and trailer swing, facilitating the evaluation of the semi-active auxiliary axle's performance in regaining stability and eliminating transient overshoots in the vehicle combination's lateral response. Yaw rate rearward amplification was effectively controlled, and articulation angle oscillations were significantly diminished. This approach suggests a systematically minimal yet practicable retrofit to the trailer, contributing to a remarkable improvement in the traffic safety of AHVs. [ABSTRACT FROM AUTHOR]

A virtual rail train (VRT) is a multi-articulated vehicle as well as a novel public transportation system due to its low economic cost, environmental friendliness and high transit capacity. Equipped with all-wheel steering (AWS) and a tracking control method, the super long VRT can travel on urban roads easily. This paper proposed a tracking control approach using only interoceptive sensors with high scene adaptivity. The kinematic model was established first under reasonable assumptions when the sensor configuration was completed simultaneously. A hierarchical controller consists of a front axle controller and a rear axle controller. The former applies virtual axles theory to avoid motion interference. The latter generates a first-axle reference path with path segmentation and a data updating method to improve storage and computational efficiency. Then, a fast curvature matching rear axles control method is developed with an actuator time delay considered. Finally, the proposed approach is verified in a hardware in loop (HIL) simulation under various situations with predefined evaluation standards, which shows better tracking performance and applicability. [ABSTRACT FROM AUTHOR]

Effective emission control technologies and eco-friendly propulsion systems have been developed to decrease exhaust particle emissions. However, more work must be conducted on non-exhaust traffic-related sources such as tyre wear. The advent of automated vehicles (AVs) enables researchers and automotive manufacturers to consider ways to further decrease tyre wear, as vehicles will be controlled by the system rather than by the driver. In this direction, this work presents the formulation of an optimal control problem for the trajectory optimisation of automated articulated vehicles for tyre wear minimisation. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one to minimise tyre wear in fixed time cases. Specific boundaries and constraints are applied to the problem to ensure the vehicle's stability and the feasibility of the solution. According to the results, a small increase in the journey time leads to a significant decrease in the mass loss due to tyre wear. The employment of articulated vehicles with low powertrain capabilities leads to greater tyre wear, while excessive increases in powertrain capabilities are not required. The conclusions pave the way for AV researchers and manufacturers to consider tyre wear in their control modules and come closer to the zero-emission goal. [ABSTRACT FROM AUTHOR]

This paper considers an integrated control method combining autonomous driving and active steering. By using artificial flow guidance (AFG), the steering at all five axles on a tractor-semitrailer are synchronized for precise low-speed path tracking and improved lateral stability. AFG is a motion planning method which uses velocity vectors to guide the motion of the vehicle; here, two modification on AFG are proposed to form the integrated-AFG which improves the transient performance and generalizes the choice of the tracking points. Simulations rendered in TruckMaker show submillimeter level steady-state off-tracking for a broad speed range, with maximum deviation being 1 cm for a high-speed lane change; amplification of trailer lateral motion is also suppressed, with rearward amplification (RWA) < 1 maintained throughout. This control method is robust to changes in key parameters such as trailer mass and road friction coefficient. The methods presented provide a new foundation for implementing automated freight transportation on highways. [ABSTRACT FROM AUTHOR]

A vehicle system motion decoupling control method was proposed to address challenges in controlling articulated heavy vehicles (AHVs). The method, based on differential geometry theory, focused on distributed electric drive AHVs. Its objective was to separate the highly nonlinear and strongly coupled dynamics system into two relatively independent subsystems: longitudinal and lateral motions. Additionally, a robust controller was designed to improve the vehicle's resistance to external disturbances like side winds. Simulation tests using a TruckSim model of a distributed electric drive AHV show significant improvements compared to vehicles without decoupling control. The rearward amplification (RA) is reduced by 4.5%, the longitudinal velocity deviation by 67.5%, and the yaw rate deviation by 69.7%. The vehicle also demonstrates enhanced stability when subjected to strong breeze disturbances. To validate the control performance in real-time systems, the hardware-in-the-loop tests were conducted, which confirms the effectiveness of the proposed control approach in practical applications. [ABSTRACT FROM AUTHOR]

Based on an investigation of how vehicle structural characteristics and system parameters influence the motion stability of high-speed steering intelligent vehicle platooning, a control strategy for ensuring motion stability is proposed. This strategy is based on a virtual articulated concept and is validated using both characteristic equation analysis and time domain analysis methods. To create a system, any two adjacent front and rear vehicles in the intelligent vehicle platooning are connected using a virtual articulated model constructed through the virtual structure method. A ten-degrees-of-freedom model of the intelligent vehicle platooning system is established, taking into account the nonlinearities of the tire and steering systems, utilizing the principles of the second Lagrange equation theory. The system damping ratio is determined through characteristic equation analysis, and the system's dynamic critical speed is assessed by examining the relationship between the damping ratio and the motion stability of the intelligent vehicle platooning, serving as an indicator of system stability. By applying sensitivity analysis, control variable analysis, and time domain analysis methods, the influence of vehicle structural characteristics and system parameters on the system's dynamic critical speed and motion stability under lateral disturbances within the intelligent vehicle platooning is thoroughly investigated, thereby validating the soundness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Tracking the articulated poses of multiple individuals in complex videos is a highly challenging task due to a variety of factors that compromise the accuracy of estimation and tracking. Existing frameworks often rely on intricate propagation strategies and extensive exchange of flow data between video frames. In this context, we propose a spatiotemporal sampling framework that addresses the degradation of frames at the feature level, offering a simple yet effective network block. Our spatiotemporal sampling mechanism empowers the framework to extract meaningful features from neighboring video frames, thereby optimizing the accuracy of pose detection in the current frame. This approach results in significant improvements in running latency. When evaluated on the COCO dataset and the mixed dataset, our approach outperforms other methods in terms of average precision (AP), recall rate (AR), and acceleration ratio. Specifically, we achieve a 3.7% increase in AP, a 1.77% increase in AR, and a speedup of 1.51 times compared to mainstream state-of-the-art (SOTA) methods. Furthermore, when evaluated on the PoseTrack2018 dataset, our approach demonstrates superior accuracy in multi-object tracking, as measured by the multi-object tracking accuracy (MOTA) metric. Our method achieves an impressive 11.7% increase in MOTA compared to the prevailing SOTA methods. [ABSTRACT FROM AUTHOR]

This research investigates the development of risk-based performance requirements for the control of an automated driving system (ADS). The proposed method begins by determining the target level of safety for the virtual driver of an ADS. The underlying assumptions are informed by existing data. Next, geometric models of the road and vehicle are used to derive deterministic performance levels of the virtual driver. To integrate the risk and performance requirements seamlessly, we propose new definitions for errors associated with the planner, pose, and control modules. These definitions facilitate the derivation of stochastic performance requirements for each module, thus ensuring an overall target level of safety. Notably, these definitions enable real-time controller performance monitoring, thus potentially enabling fault detection linked to the system's overall safety target. At a high level, this approach argues that the requirements for the virtual driver's modules should be designed simultaneously. To illustrate this approach, this technique is applied to a research project available in the literature that developed an automated steering system for an articulated bus. This example shows that the method generates achievable performance requirements that are verifiable through experimental testing and highlights the importance in validating the underlying assumptions for effective risk management. [ABSTRACT FROM AUTHOR]

Featured Application: Path planning, navigation, and lateral control for autonomous vehicles. Development of control algorithm for truck platooning. This study introduces an advanced lateral control strategy for autonomous vehicles using a clothoid-based approach integrated with an adaptive lookahead mechanism. The primary focus is on enhancing lateral stability and path-tracking accuracy through the application of Euler spirals for smooth curvature transitions, thereby reducing passenger discomfort and the risk of vehicle rollover. An innovative aspect of our work is the adaptive adjustment of lookahead distance based on real-time vehicle dynamics and road geometry, which ensures optimal path following under varying conditions. A quasi-feedback control algorithm constructs optimal clothoids at each time step, generating the appropriate steering input. A lead filter compensates for the vehicle's lateral dynamics lag, improving control responsiveness and stability. The effectiveness of the proposed controller is validated through a comprehensive co-simulation using TruckSim® and Simulink®, demonstrating significant improvements in lateral control performance across diverse driving scenarios. Future directions include scaling the controller for higher-speed applications and further optimization to minimize off-track errors, particularly for articulated vehicles. [ABSTRACT FROM AUTHOR]

Virtual track trains are a new type of rail transportation because the multisection formation structure leads to more degrees of freedom of the vehicle, which may cause unstable phenomena, such as tailing, cross-swing, and folding, affecting the stability and ride comfort of the vehicle driving. To explore the effect of damping coefficient of the articulated systems on vehicle dynamics performance, a vehicle system dynamics model is established based on the actual parameters of a three-module six-axle virtual track train. According to ISO14791: 2000, select typical working conditions such as straight line, lane change, and 1/4 circle curve, and optimize the damping coefficient of the articulated systems through co-simulation. The study shows that under straight-line conditions, increasing the damping coefficient can effectively suppress the yaw angular acceleration and improve the lateral ride comfort of the vehicle but has little effect on the vertical ride comfort. Under lane change conditions, too large or small damping coefficients will deteriorate the train's lateral stability, and a reasonable damping coefficient will improve the yaw damping ratio of the vehicle and reduce the lateral sway vibration between vehicles. Under the 1/4 circle curve conditions, the additional articulated system damper will reduce the vehicle's curve passing performance. In this paper, the articulation stability of multimodule fully connected vehicles is analyzed and optimized for the first time, and the damping coefficient control strategy is given based on the geometric tracking control method. The research results are of great significance for the parameter selection of virtual track trains' articulated system and the design and development of specialized articulated systems for related vehicles. [ABSTRACT FROM AUTHOR]

In this paper, an autonomous driving lateral control algorithm is introduced for bus rapid transit (BRT, with an articulated bus). The control algorithm includes an integration of model predictive control (MPC) for lateral control and PID control algorithms for longitudinal control considering the vehicle properties. To verify the algorithm in real-time, a model-in-the-loop system was developed using TruckSim in NI Veristand and Matlab/Simulink in Micro-AutoBox. In TruckSim, a BRT plant model was verified using vehicle tests and then applied. In addition, GPS data from a BRT route were acquired from the vehicle test and applied to a TruckSim scenario. In the Matlab/Simulink, the autonomous driving lateral control algorithm for MPC was developed. To communicate between the plant model and the control algorithm in real-time, a controller area network (CAN) protocol was defined and applied like a real vehicle. Therefore, a real-time verification environment was prepared to test the real-time autonomous driving lateral control algorithm for BRT. By using the verification environment, the control algorithm was verified using the ISO-11270 standard. Although many efforts have been made to develop an autonomous driving control algorithm, autonomous driving of BRT is expected more tangible because the BRT has its own lane and speed limitation. Therefore, this paper will introduce about study of real time feasibility, adaptation of vehicle variables, and precise prediction model for MPC algorithm. [ABSTRACT FROM AUTHOR]

Real-time collision risk prediction is essential for improving highway safety and reducing traffic accidents. However, previous studies have mainly used crash data and associated spatially discrete and temporally continuous traffic data, overlooking the potential of vehicle trajectory data, which provides comprehensive spatio-temporal information to characterize traffic near a specific location. Moreover, researchers have typically focused on either traffic flow characteristics or inter-vehicle microscopic kinematic characteristics for real-time risk prediction, with a dearth of studies integrating these two aspects. Given that risk events transpire more frequently than accidents and exhibit a strong correlation with them, it is imperative to concentrate more on risk events to proactively diminish crash probabilities. This study introduces a novel approach that extracts traffic flow and inter-vehicle kinematic features from risk events. It also provides a comparative analysis of the effectiveness of five machine-learning methods (Logistic Regression, K-Nearest Neighbors, eXtreme Gradient Boosting, Random Forests, and Multilayer Perceptron) and two data-processing strategies (oversampling and undersampling) in addressing risk identification and prediction issues. The results showed that (1) the synergistic use of traffic flow and inter-vehicle kinematic features surpasses the use of a single feature in identifying and predicting risks; (2) The eXtreme Gradient Boosting model, trained on the undersampled dataset, emerges as the optimal model for risk identification, boasting an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.976 and an F1 score of 0.604; (3) The RF model exhibits commendable performance under both risk prediction conditions (5 s ahead prediction and 10 s prediction), demonstrating the highest performance with F1 scores of 0.377 and 0.374, respectively. Additionally, it was discovered that the resampling strategy does not always prove effective in developing risk analysis models and should be chosen based on the model's characteristics and target metrics. This offers valuable insights into the selection of data-processing strategies when handling unbalanced data. Finally, the study's limitations and potential enhancements are discussed. [ABSTRACT FROM AUTHOR]

A path-following control method based on dual heuristic programming (DHP) is proposed to address the problem whereby unmanned articulated vehicles need to set different controller parameters to track complex routes and cannot adapt to complex routes. First, the path-following control system structure is designed based on the articulated vehicle experimental platform, and the error model is derived based on the kinematic model of the articulated vehicle. Second, the payoff function is designed considering the error and stability indices, and the actor and critic of the path-following control method based on the DHP algorithm are approximated using a multilayer feedforward neural network. Finally, the path-following quality of the method is verified using simulations and real vehicle tests and compared with the conventional pure tracking and linear-quadratic regulator methods. The results show that the DHP-based method is able to follow complex reference paths and obtain better control results than the traditional methods without iterative tuning of the controller parameters, which improves the adaptiveness of the articulated vehicle path-following control method to complex environments. [ABSTRACT FROM AUTHOR]

One of the main problems of modern big city is the global crisis of normal urban environment operation as a result of structural growing of automobilization level, oversaturation of road-street network by the transport streams. Buses of the especially large size class occupy, at the least, 20% in the structure of a modern bus park. The buses of especially large size classes, with the aim of necessary maneuverability, as a rule are made articulated. One of the ways of improving the maneuverability of articulated buses is the usage of guided towed sections. Solving the mentioned problem usually needs the mathematic models for predicting the vehicle behavior. The aim of introducing the trailer direction is to increase the overall traffic lane of an articulated bus that ensures a necessary maneuverability. The aim is gained by a choice of a rational transmitting ratio of trailer axle gear and necessary value of braking moment on one of its wheels. The solving of the problem concerning the stability of an articulated bus with a guided trailer axle was made by the way of analyzing the linear approaching of stationary vehicle movement. An influence of the construction parameters of the bus and the trailer, a transmitting ratio of control gear and a value of braking moment on the parameters of bus maneuverability were analyzed. It was proved that for an articulated bus, the normal maneuverability parameters can be ensured at the trailer direction by a way of braking of one of the wheels. [ABSTRACT FROM AUTHOR]

A vehicle equipped with an articulated steering system is often used in a particular area, such as a mine or the construction field. These sealing or semi-sealing fields make autonomous driving by an ASV (Articulated Steering Vehicle) easier than in passenger cars. Path-tracking is essential for an autonomous vehicle. To improve the path-tracking ability of an ASV, a path-tracking model is established based on dynamic theory. Then, the slide-mode predictive-control (SMPC) strategy is initiated to design the path-tracking controller. The improvement in the path-tracking ability on roads with different adhesion coefficients is validated via the HIL (Hardware in Loop) platform. According to the simulation in HIL with the provided strategy, the path-tracking error during the typical condition decreased by 21.73~93.84%, demonstrating the SMC controller can be used to improve the path-tracking performance of an ASV. [ABSTRACT FROM AUTHOR]

How to improve the driving performance of the vehicle while carrying out path tracking control has become a hot issue in current research. In this paper, an MPC (Model predictive control) path tracking control algorithm incorporating differential braking control is proposed. By establishing a vehicle dynamics model of a semi-trailer train, the model predictive control theory is adopted for path tracking. Then, the vehicle dynamics model, considering the additional yaw moment, is established to design the differential braking control strategy. Under low-speed working conditions, the PID (Proportional Integral Derivative) algorithm is used to solve the additional yaw moment with the yaw rate of the tractor traveling alone as the desired value. Under high-speed working conditions, the Fuzzy PID algorithm is used to solve the additional yaw moment with the control objective of reducing the articulation angle. Simulation models are built using MATLAB/Simulink, and TruckSim for numerical experimental validation. The numerical experimental results show that the differential braking control method proposed in this paper can improve the maneuverability of vehicles driving in low-speed conditions and the stability of vehicles driving in high-speed conditions without decreasing the precision of path tracking control. [ABSTRACT FROM AUTHOR]

The realistic simulation of the dynamic responses of a moving articulated vehicle has attracted considerable attention in various disciplines, with the identification of the vehicle model being the prerequisite. To this end, a double-sensor hump calibration method (DHCM) was developed to identify both unladen and laden vehicle models, consisting of a sensor layout optimization step and a system identification step. The first step was to optimize the number and position of sensors via parameter sensitivity analysis; the second was to inversely identify the vehicle system based on sensor responses. For comparison, the DHCM and the existing single-sensor hump calibration method (SHCM) were used to calibrate a small-sized vehicle model and a multi-axle articulated vehicle model. Vertical accelerations of the vehicle models were then simulated and characterized by power spectral densities (PSDs). Validation against experimental measurements indicated that the PSDs of the models identified with the DHCM matched the measured PSDs better than those of the SHCM, i.e., the DHCM-identified model accurately simulated the dynamic response of an articulated vehicle with relative errors below 16% in the low-frequency range. Therefore, the DHCM could identify models of small-sized vehicles and multi-axle articulated vehicles, while the SHCM was only suitable for the former. [ABSTRACT FROM AUTHOR]

The evolution of the vehicle industry, as well as the sudden increase in competition between manufacturing companies, dictates the increase in the obligations of manufacturers to meet the increasingly complex requirements of users, in terms of ergonomics, comfort, safety, as well as environmental protection. Researchers have investigated the factors influencing the ergonomics of the vehicle interior which is very practical to improve safety and driving performance in addition, it can significantly reduce the development costs and the development cycle of new vehicle concepts, but the concept of ergonomics was not clearly articulated from a human perspective. This study aims to interpret the definition of ergonomics in the context of the interior of the vehicles and also in the study the influencing factors of the ergonomics of the index layer of the human-machine interaction interface, in the central console of the vehicle, are identified. The influencing factors are analyzed by creating and visualizing bibliometric networks in VOSViewer. [ABSTRACT FROM AUTHOR]

The Generalised N-Trailer (GNT) vehicle is a tool for field operations that optimises harvesting and transportation tasks, offering a highly scalable payload using only one tractor. Precise knowledge of the position and attitude of each segment in the chained vehicle is crucial for the controller's success during operation. In this study, we propose the use of a Nonlinear Moving Horizon Estimator (NMHE) to estimate the system's state when the GNT vehicle is equipped with incremental encoders on its joints. A first NMHE serves as a virtual calibration procedure, estimating initial joint angle values and the system's state using noisy and biased measurements of the joints and the tractor pose. This calibration is performed while the chained vehicle travels along a straight path, whose length is determined by the number of trailers and their geometrical properties. Subsequently, a second NMHE, with fewer optimisation variables and constraints replace the first to effectively reduce the computational burden. Moreover, it treats the incremental encoder measurements as if they were absolute encoders after the initial joint angles have been estimated by the first NMHE. The proposed method is compared against the Extended Kalman Filter (EKF) and validated through simulated and practical real-time experiments, showcasing its effectiveness in achieving precise control and enhancing operational efficiency. [Display omitted] • The state of chained vehicles with incremental encoders can be estimated by using MHE • The computational burden is reduced by switching from N M H E 1 to N M H E 2 • The state estimated is compatible with the system's model and constraints [ABSTRACT FROM AUTHOR]

The prominent problem of articulated steering structure of engineering vehicle is that there is pressure oscillation in the hydraulic system during steering, which seriously affects the performance of steering system. To solve this problem, the maximum stroke difference of left and right cylinders and the minimum maximum cylinder pressure are the optimization objectives, and the position of cylinder hinge point is the design variable. The multi-objective optimization design of articulated steering system is carried out by using the particle swarm optimization algorithm. After optimization, the maximum pressure of the steering system is reduced by 13.5%, and the oscillation amplitude is reduced by 16%, so the optimization effect is obvious. The dynamic characteristics of the hydraulic steering system under different loads, such as pressure and flow rate, are obtained through field steering tests of wheel loaders. The results show that the load has an important effect on the pressure response of the system, and the causes and influencing factors of pressure and flow fluctuation are determined. The relationship between mileage and hydrogen consumption is obtained, which provides data support for vehicle control strategy. The high-pressure overflow power consumption accounts for 60% of the total work, and the work lost on the steering gear reaches 36 kJ. The test results verify the rationality and correctness of the optimization method of steering mechanism and provide data support for the improvement in steering hydraulic system.

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With the development of science and technology, self-driving technology is gradually being applied to automobile semi-trailer trains. Aiming at the problem that it is challenging to plan the traveling trajectory of an autonomous semi-trailer train, a trajectory planning algorithm based on a constrained iterative linear quadratic regulator is proposed. The constrained iterative linear quadratic regulator solves the problem that the iterative constrained linear quadratic regulator cannot deal with inequality constraints by transforming inequality constraints into interior point penalty functions to deal with all kinds of inequality constraints in the trajectory planning problem. When dealing with the obstacle avoidance problem, the body contour is modeled approximately according to the actual shape of the vehicle, and the obstacle avoidance constraints are transformed into inequality constraints. Considering the unique body structure of a semi-trailer train, the articulation angle constraint function is designed according to different vehicle speeds. Simulation experimental results show that the algorithm can plan safe driving trajectories for semi-trailer trains in complex traffic scenarios. [ABSTRACT FROM AUTHOR]

In emergency scenarios, lane changing can provide a considerable advantage over braking by aiding in the prevention of rear-end collisions. However, executing lane changes on horizontal curves might lead to rollover collisions. This study proposes a systematic methodology for quantifying the rollover safety margin during lane-changing maneuvers by encompassing the complex characteristics of vehicle-road interactions. Specifically, an enhanced six-degree-of-freedom vehicle dynamics model was developed for a tractor-semitrailer and integrates road superelevation. Using this model, the rollover safety margin reduction rate (fS) was calculated. The fS represents the ratio of the difference between the lateral load transfer ratio margins under both reference state and emergency lane change conditions to the lateral load transfer ratio margin in the reference state. The reference state corresponds to vehicles maintaining 80 km·h-1 on a 270 m radius curve, while the emergency condition is defined as lane change durations of less than 4 seconds. The results reveal that emergency lane change maneuvers and roadway alignment significantly affect rollover safety margin. Shorter lane change duration, higher speed, and smaller radius worsen the rollover safety margin; these effects are further amplified when the lane change direction is opposite to the curve's bending direction. When the tractor-semitrailer performs a lane change at 60 km·h-1 within a 4-second duration on a 600 m radius curve, the fS exceeds 100%, indicating an imminent rollover. Consequently, this study contributes valuable evidence to the development of more reliable and secure lane-change strategies. [ABSTRACT FROM AUTHOR]

Since large articulated vehicles have uncertainties in trailer articulation angle as well as dynamic complexity, it is not easy to accurately establish a reliable motion plan. In this paper, two geometric path plans constructed based on the empirical rules of driving experts are presented so that articulated vehicles can automatically perform perpendicular parking on a reverse path. By analyzing the empirical parking methods of professional drivers, these path plans were constructed by appropriately combining several standardized simple basic motions to facilitate implementation in real vehicles. In addition, the path plans included appropriate complementary motions to effectively respond to uncertainties arising from articulation angles, etc. The complementary motions developed in this study are based on the results of qualitative analysis on the behavior of articulated vehicles. The usefulness of the proposed articulated vehicle parking method has been proven through hundreds of experimental tests using a scaled model automated vehicle. [ABSTRACT FROM AUTHOR]

Effective emission control technologies and eco-friendly propulsion systems have been developed to decrease exhaust particle emissions. However, more work must be conducted on non-exhaust traffic-related sources such as tyre wear. The advent of automated vehicles (AVs) enables researchers and automotive manufacturers to consider ways to further decrease tyre wear, as vehicles will be controlled by the system rather than by the driver. In this direction, this work presents the formulation of an optimal control problem for the trajectory optimisation of automated articulated vehicles for tyre wear minimisation. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one to minimise tyre wear in fixed time cases. Specific boundaries and constraints are applied to the problem to ensure the vehicle’s stability and the feasibility of the solution. According to the results, a small increase in the journey time leads to a significant decrease in the mass loss due to tyre wear. The employment of articulated vehicles with low powertrain capabilities leads to greater tyre wear, while excessive increases in powertrain capabilities are not required. The conclusions pave the way for AV researchers and manufacturers to consider tyre wear in their control modules and come closer to the zero-emission goal.

In this paper, an articulated virtual rail train running on an urban road with N-unit is introduced, and a new tracking control system is designed to realize the tracking control of the articulated virtual rail train. First, a dynamic model for the articulated virtual rail train with N-unit is derived with 11N degrees of freedom. Second, based on the dynamic model, a steering control system is designed, which includes the following sub-controllers: a unit 1 front-axle steering controller and a unit 1∼N rear-axle steering controller for approaching the virtual target path, a unit 2∼N front-axle steering controller for coordinating the movement of adjacent units, and a four-wheel-steering (4WS) controller for each unit. Finally, a numerical simulation model of the train with five units is built in MATLAB, and a cross-validation model is built in ADAMS software. The simulation and verification results show that the tracking errors are within 50 mm, and the lateral articulation forces are less than 2 kN, which indicates that the designed control system has a good tracking performance. [ABSTRACT FROM AUTHOR]

Lateral stability is vital to vehicle handling stability and traffic safety. It is also a crucial factor for the path-tracking ability of the vehicle in the intelligent transportation system (ITS). Most of the research focuses on vehicles with an Ackerman steering system. The ASV (articulated steering vehicle) has a lower steering radius. Thus, it is widely used in some special vehicles, such as mining and construction vehicles. The ASV has weaker lateral stability than the vehicle with an Ackerman steering system. To improve the stability of an ASV, the nonlinear lateral dynamic model is established and validated by field test. With the lateral dynamic model, the steering characteristic of the ASV is analyzed. Based on the stability criteria analysis, the vehicle sideslip angle and angular velocity phase portrait are chosen as the stability indicator. An integrated AASS (active articulated steering system) DYC (direct yaw control) controller based on the adaptive MPC (model predictive control) method is designed according to the track on the phase plane. The double lane-change and 0.7 Hz sine with dwell maneuver are initiated based on the integrated vehicle dynamic model. The results suggest that the provided controller has a better stability performance than the current antiwindup PID control algorithm. It lays a good foundation for the vehicle safety and path tracking of ASV in the ITS. [ABSTRACT FROM AUTHOR]

To overcome the limitations of laparoscopic surgery, robotic systems have been commonly used in the era of minimally invasive surgery despite their high cost. However, the articulation of instruments can be achieved without a robotic system at lower cost using articulating laparoscopic instruments (ALIs). Between May 2021 and May 2022, perioperative outcomes following laparoscopic gastrectomy using ALIs versus robotic gastrectomy were compared. A total of 88 patients underwent laparoscopic gastrectomy using ALIs, while 96 underwent robotic gastrectomy. Baseline characteristics were similar between the groups except for a higher proportion of patients with a medical history in the ALI group (p = 0.013). Clinicopathologic and perioperative outcomes were not significantly different between the groups. However, the operation time was significantly shorter in the ALI group (p = 0.026). No deaths occurred in either group. In conclusion, laparoscopic gastrectomy using ALIs was associated with comparable perioperative surgical outcomes and a shorter operation time compared to robotic gastrectomy in this prospective cohort study. [ABSTRACT FROM AUTHOR]

Minimum lap-time planning (MLTP) is a well-established problem in the race car industry to provide guidelines for drivers and optimize the vehicle's setup. In this paper, we tackle the 3D nature of the problem in its full extension, making no simplifying assumptions on the mechanics of the system. We propose a multibody vehicle model, described by rigorous dynamical equations. To effectively handle the resulting complexity, we devised an efficient direct dynamics computational method based on Featherstone's articulated-body algorithm (ABA). To solve the MLTP, we employed a direct-collocation technique, discretizing the problem so that all information of the 3D track is pre-processed and directly embedded into the discrete problem. This discretization approach turns out to be perfectly compatible with our vehicle model, leading to a solution in accessible computational time frames. The high level of detail of the model makes the proposed approach most useful for in-depth vehicle dynamics analyses on complex tracks. To substantiate the analysis, we provide a comparison with the results obtained by a double-track model on the Nürburgring Nordschleife circuit. Consistently with the average trend defined by the double track, the proposed model features a more dynamically rich behavior, realistically capturing the higher-order effects elicited by the sharp corners and the highly variable slope of the track. [ABSTRACT FROM AUTHOR]

Vibroseis trucks are in danger of rollover during the steering process, which severely threatens the safety of the drivers and the equipment. Therefore, it is important to examine approaches to increase the anti-rollover ability of vibroseis trucks. According to the structural characteristics and working field of the vibroseis truck, an analysis of the influence of different factors on its rollover stability was carried out. Then, a rollover warning index and an anti-rollover warning system were established, which can achieve four levels of judgment of different driving states. A simulation analysis of the anti-rollover warning system was conducted with MATLAB/Simulink software. The results showed that this warning system could accurately determine the driving state on a flat road and a sloping road and produce four types of sound–light alarm according to different rollover states. At the same time, the vibroseis truck showed poor roll stability in the slope steering process which is more prone to rollover accidents. This study establishes a foundation for further research on the design of warning systems not only for vibroseis trucks but also for other articulated trucks. [ABSTRACT FROM AUTHOR]

Physical and virtual K&C analyses are performed to achieve the vehicle dynamics targets by finding the optimum variables such as the position of hardpoints or stiffnesses of bushings. However, finding appropriate design variables that meet all the aims is challenging. This paper evaluates a hardpoint optimization approach to attain suspension K&C characteristic objectives with the design of experiments, neural networks, and genetic algorithm, based on a reference compact-sized prototype vehicle. The MBD model correlation is provided to optimize the hardpoints to improve the vehicle's steering kinematics concerning Ackerman error and camber angle variation that are out of target in baseline suspension. The results showed that NN based optimization strategy to define the hardpoints has significantly improved targeted characteristics compared to conventional response surface methods in the limited design space. [ABSTRACT FROM AUTHOR]

This paper focuses on the trajectory planning and trajectory tracking control of articulated tracked vehicles (ATVs). It utilizes the path planning method based on the Hybrid A-star and the minimum snap smoothing method to obtain the feasible kinematic trajectory. To overcome the highly non-linearity of ATVs, we proposed a linear-parameter-varying (LPV) kinematic tracking-error model. Then, the kinematic controller was formulated as the adaptive model predictive controller (AMPC). The simulation of the path planning algorithm showed that the proposed planning strategy could provide a feasible trajectory for the ATVs passing through the obstacles. Moreover, we compared the AMPC controller with the developed controller in four scenarios. The comparison showed that the AMPC controller achieved satisfactory tracking errors regarding the lateral position and orientation angle errors. The maximum lateral distance error by the AMPC controller has been reduced by 72.4% compared to the standard-MPC controller. The maximum orientation angle error has been reduced by 55.53%. The simulation results confirmed that the proposed trajectory planning and tracking control system could effectively perform the automated driving behaviors for ATVs. [ABSTRACT FROM AUTHOR]