Search Results (23)

This paper addresses the impact of complex mining environments and the nonlinear dynamics of hinged mining trucks on reverse path tracking control for autonomous mining trucks. We propose a neural-network-based sliding mode control (NN-SMC)-based control strategy for reverse motion to improve tracking accuracy and robustness. First, a tractor–trailer dynamic model is built, and the force characteristics at the coupling joint are analyzed to derive the reverse interaction forces, which simplifies trailer modeling and avoids the influence of uncertain tractor parameters. Next, a control scheme matching the simplified model is developed, where an optimized sliding surface is designed and a neural network adaptively tunes control parameters to reduce chattering and improve adaptability to challenging conditions. Finally, hardware-in-the-loop tests validate the simulation results. Both simulation and experiments show that, compared with conventional SMC, the proposed method reduces lateral displacement error by 13.98% and heading error by 18.96%, demonstrating the effectiveness of the control approach. Full article

To address the high sensing cost, uneven material distribution, and safety–efficiency trade-off in close-range wheel loader–dump truck collaborative unloading, this study proposes a perception–task–control framework for autonomous unloading. A complementary front–rear vision configuration is used to perceive the dump-truck bed under varying relative viewpoints, and the estimated bed pose is further transformed into executable unloading targets. To improve load distribution, a partition-aware task-generation strategy is developed, by which the unloading objective is extended from a single target point to sequential zone-level targets. An event-triggered two-stage reinforcement learning controller is then designed to organize the unloading process. The first stage guides the loader toward a perception-enabled region, while the second stage performs vision-guided precision alignment and coordinated lifting according to the current zone-level target. A closed-loop co-simulation environment is constructed using MATLAB/Simscape R2025b and Unreal Engine, and field-test data are used for simulation–field response comparison. The simulation results under representative operating conditions show that the proposed framework can complete sequential zone-level unloading without collision under the tested conditions. The quantitative results support the effectiveness of the method in terms of target completion, completion time, terminal positioning accuracy, lifting completion, and collision avoidance. The field-test comparison further indicates that the developed simulation model can reproduce the main trajectory, articulation-angle, and lifting-cylinder displacement responses of the wheel loader during unloading. These results demonstrate the feasibility of integrating low-cost visual perception, partition-aware task generation, and two-stage learning-based control for autonomous wheel-loader unloading. Full article

This research addresses the coupling issue between speed tracking and vertical posture in articulated unmanned mining trucks within unstructured environments. An extension theory-based coordinated control strategy is proposed, incorporating both articulation joint safety and vehicle stability. The control framework employs extension theory to classify operational modes based on articulation angle and velocity deviation. For longitudinal motion, active disturbance rejection control (ADRC) is adopted to mitigate the influence of varying payload mass and road slope on speed tracking performance. For vertical dynamics, a soft actor–critic (SAC) algorithm regulates active suspension to improve ride comfort. Both simulations and hardware-in-the-loop testing results demonstrate the superiority of the proposed strategy: coordinated control maintains speed tracking error below 4%, reduces body acceleration by 16.1%, 11.9%, and 17.5%, and improves articulation angle oscillations by 12.6%, 14.6%, and 15.1% across scenarios, confirming the strategy’s enhanced performance over conventional single-loop control approaches. Full article

Mining articulated vehicles (MAVs) are widely used as primary transportation equipment in both underground and open-pit mines. These include various machines such as Load–Haul–Dump machines and mining trucks. Path tracking control for MAVs has been an important research topic. Most current research focuses on path tracking control during forward driving. However, there are relatively limited studies on reverse path tracking control. Reversing plays a crucial role in the operation of MAVs. Nevertheless, existing methods typically use the center of the front axle as the control point; therefore, the positioning system is usually installed at the front axle. In practice, however, this means the positioning system is actually located at the rear axle during reverse operations. While it is theoretically possible to infer the position and orientation of the front axle from the rear axle, a strong nonlinear relationship exists between the motion states of the front and rear axles, which introduces significant errors in the system. As a result, these existing methods are not suitable for reverse driving conditions. To address this issue, this paper proposes a nonlinear model predictive control (NMPC) method for path tracking during mining-articulated vehicle (MAV) reverse operations. This method innovatively reconstructs the reverse-motion model by selecting the center of the rear axle as the control point, effectively addressing the instability issues encountered in traditional control methods during reverse maneuvers without requiring additional positioning devices. A comparative analysis with other control strategies, such as NMPC for forward driving, reverse NMPC using the front axle model, and reverse linear model predictive control (LMPC), reveals that the proposed NMPC method achieves excellent control accuracy. Displacement and heading error amplitudes do not exceed 0.101 m and 0.0372 rad, respectively. The maximum solution time per control period is 0.007 s. In addition, as the complexity of the reverse path increases, it continues to perform excellently. Simulation results show that as the curvature of the U-shaped curve increases, the proposed NMPC method consistently maintains high accuracy under various operational conditions. Full article

The transport industry in the European Union plays a key role in the economy. However, due to persistent political, social, and technological changes, examining optimization strategies in transportation has become a crucial task to minimize expenditure, promote sustainable solutions, and address environmental degradation concerns. This study analyzes the effectiveness of a new truck trailer design, adapted from existing European models, which improves load capacity through an extended trailer length. The increased length (and, by extension, volume) is expected to reduce the number of vehicles for freight transportation, thereby improving road congestion and reducing environmental impacts, which include GHG emissions and overall carbon footprint. To achieve this objective, a comprehensive analysis of current European regulations on articulated vehicles and road trains was carried out, alongside a review of related case studies implemented or under development across the European Union member states. Additionally, a pilot study was conducted using the proposed 18 m semi-trailer across 14 real-life freight routes involving loads from several suppliers and manufacturers. This study therefore demonstrates the economic benefits and reduction in pollutant emissions related to the extended design and evaluates its impact on road infrastructure conditions, given the total length of 20.55 m. Full article

Unmanned underground articulated dump trucks (UADTs) are an important direction for the coal mining industry to vigorously promote automation and intelligence. Among these, tracking and controlling the motion trajectory is the key weak link. This paper presents a kinematic analysis of the stationary turning process of UADTs. Then, a posture state model for articulated trucks is established. The objective is to optimize the control method and further improve trajectory tracking accuracy. Based on the advantages and disadvantages of the feedback linearization control (FLC) method, a sliding mode control method based on the Ackermann formula (ASMC) and integral type switch gain (ISMC) are proposed. Finally, hardware-in-the-loop simulation verifies the superiority and tracking quality of the controller. The results show that the ASMC controller can control the lateral position deviation, course angle deviation, and curvature deviation around 10 cm, 0.04 rad, and 0.08 m⁻¹ in the hardware-in-the-loop simulation environment. The ISMC controller can control the lateral position deviation, course angle deviation, and curvature deviation near 8 cm, 0.01 rad, and 0.02 m⁻¹, and can also effectively control the jitter problem. Each deviation is stabilized within 10 s. This provides a reference for the development of trajectory tracking strategies for articulated vehicles. Full article

This paper tackles the complex problem of trajectory planning for trucks with multiple trailers, with a specific focus on autonomous parking assistance applications. These systems aim to autonomously guide vehicles from a starting position to a target location while effectively navigating real-world obstacles. We propose a novel six-phase approach that combines global and local optimization techniques, enabling the efficient and accurate generation of reference trajectories. Our method is validated in a case study involving a truck with two trailers, illustrating its capability to handle intricate parking scenarios requiring precise obstacle avoidance and high maneuverability. Results demonstrate that the proposed strategy significantly improves trajectory planning efficiency and robustness in challenging environments. Full article

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. Full article

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. Full article

The present study analyses the production rates of stop-unrelease amongst advanced French learners of English before and after training. Although stop-unrelease may be regarded as a minor issue in English pronunciation teaching, it has received some attention in recent years. Earlier studies showed that amongst “phonetically naive English listeners”, the lack of release of /p/, /t/ and /k/ leads to lower identification scores. The present study analyses the speech of 31 French university students majoring in English to measure the efficiency of an awareness approach on the production of stop-unrelease. The experiment comprised three phases with a test and a control group. During Phase 1, both groups were asked to read pairs of words and sentences containing medial and final voiceless stops. We chose combinations of two identical stops (homorganic) or stops with different places of articulation (heterorganic), as well as stops in utterance-final position. Namely, wait for me at that table over there, that pan, or I like that truck. In Phase 2, one group watched an explanatory video to increase awareness on stop-unrelease in English before reading Phase 1 words and sentences a second time. The remaining group was the control group and did not receive any training. Among the participants, 17 read a French text containing pairs of stops in similar positions to those in the English one, which served as an L1 baseline. In total, six students continued until Phase 3 (reading the same stimuli a month later; three in the control group and three in the test group). The results showed that sentence-final stops were overwhelmingly released (above 90%) in both English and French in Phase 1. Training had a significant impact on sentence-final stop-unrelease (p < 0.001), which rose from 9.65% to 72.2%. Progress was also visible in other contexts as in heterorganic pairs of stops. Based on these results, we strongly recommend the combined use of spectrograms and gestures to raise awareness in a classroom or for online learning so as to reach multiple learner profiles and further increase efficiency in pronunciation learning. Full article

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. Full article

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. Full article

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. Full article

This paper proposes an integrated path tracking controller for articulated vehicles. A nonlinear model-predictive control (NMPC)-based reference state tracker is designed as an upper-level controller to solve the vehicle’s longitudinal velocity and steering rate. A terminal cost is introduced into the NMPC to improve the controller’s stability. A lower-level controller is developed to translate upper-level solutions into vehicle actuators’ signals, including steering and driving controllers. The steering controller translates the steering rate into the linear velocity of the cylinder to calculate the required fluid volume and ultimately into the rotation speed of the steering motor. The neural network method is applied in the driving controller to ensure accuracy under different loadings. In order to investigate the effects of the path tracking controller, an articulated dump truck is adapted for the field tests by adding the steering-by-wire system and driving-by-wire system, respectively. Experimental verifications of the lower-level controller are performed. The results show that the controller can accurately satisfy the demand. Finally, the tracking performance of the integrated path tracking controller is analyzed experimentally under different reference velocities. The results indicate that tracking accuracy can be guaranteed. Full article

With the continuous development of road transport of goods, the issue of safety risks related to the movement of trucks and road trains remains an essential element of the overall road safety system. One of the persistent problems is the braking of such kits, especially in emergencies on the road. The work aims to show how typical changes in operating conditions can affect the basic indicators illustrating the safety of braking (effectiveness indicators, stability symptoms). A simulation method was applied for the analysis, which used a relatively simple (quasi-static) model of the tractor-semitrailer set’s rectilinear motion and models of the braking system and the longitudinal forces in the tyre-road surface contact. Calculations were made for the selected truck-trailer set in nominal condition and for several deviations from the nominal state, such as loading the trailer (load value, location of the semi-trailer’s centre of gravity), reduced surface adhesion, and selected faults of the semitrailer braking system. The results were compared for several qualitative and quantitative criteria for the evaluation of braking safety. Attention was drawn to the problem of the forces in the coupling (which determine the possibility of jack-knifing phenomena), the order of axle locking, and the braking distance. The presented results show that the change of operating conditions as above compared to the nominal condition visibly deteriorates the effectiveness of the braking process. The greatest threat, both related to the braking efficiency and the increase in the force in the coupling, is associated with the lack of braking of the semitrailer axle or a significant reduction in its load. The weight and location of the load’s centre of gravity considerably impact braking safety. In addition to the negative impact on the braking distance or increase in the horizontal force in the coupling, it changes the order of locking the axle. ABS reduces the risk associated with braking safety but does not eliminate it. At the same time, it has been shown that using relatively simple calculation tools makes it possible to indicate the risks related to the braking safety of such articulated vehicles. Full article