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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]

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]

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]

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]

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]

Featured Application: The model and analysis results established in this paper can be used for dynamic analyses of the autonomous driving control of articulated steering vehicles, as well as for the design of hybrid or pure electric power articulated steering vehicles. Articulated steering vehicles (ASVs), with brilliant maneuverability and efficiency, are being widely applied in mining, construction, agriculture, and forestry. However, their special structures result in them having complex dynamic characteristics, but there are no reliable models for further research. This study established a simulation platform with the dynamic model of ASVs, where the subsystems of the power train, steering systems, tires, and frames were also included. The dynamic model was validated with field test data of typical working cycles, in which the focus was on longitudinal and lateral motions and the characteristics of steering and power train systems. Then, the distribution of hydraulic and drive power was revealed using the simulation platform and test data. For a load–haul–dump (LHD) vehicle with a 6 m3 capacity, the maximum power of the system was about 289 kW; the power of the motor accounted for the majority of the power at the beginning stage of loading, being about 74%, and then the hydraulic power dominated in the later stage of loading. During the transport stage, the power of the motor accounted for about 79% of the total power. Finally, the influence of the dynamic parameters on lateral and longitudinal motions was analyzed based on the validated platform. [ABSTRACT FROM AUTHOR]

This research was mainly focused on the evaluation of path planning approaches as a prerequisite for the automation of bale collection operations. A comparison between a traditional bale collection path planning approach using traditional vehicles such as tractors, and loaders with an optimized path planning approach using a new autonomous articulated concept vehicle with neighborhood reach capabilities (AVN) was carried out. Furthermore, the effects of carrying capacity on reduction in the working distance of the bale collection operation was also studied. It was concluded that the optimized path planning approach using AVN with increased carrying capacity significantly reduced the working distance for the bale collection operation and can thus improve agricultural sustainability, particularly within forage handling. [ABSTRACT FROM AUTHOR]

The tractor and trailer units of the semi-trailer truck are connected through the hitch point. The articulation angle is generated when lateral force is applied to the vehicle and it causes the tractor and trailer units to move in different trajectories. When driving on narrow road or large curvature road, considerable level of driving skill is required to drive within the road boundary. If the driver passes through a narrow road without considering the articulation angle, a collision accident may occur to surrounding obstacles or vehicles. In this study, an autonomous driving system was proposed by considering the articulation angle of a semi-trailer truck in a narrow road. Based on the model predictive control, the future trajectory of the semi-trailer truck is predicted and controlled. Collision detection is conducted by using the Separate Axis Theorem and the result is reflected in model predictive control (MPC) constraints. The proposed algorithm is verified using MATLAB Simulink and TruckSim. [ABSTRACT FROM AUTHOR]

This research suggests an autonomous driving control algorithm for Bus Rapid Transit (BRT, articulated bus). The control algorithm is composed of an integration of MPC (model Predictive Control) and PI control algorithms because vehicles have a lot of delayed systems. Specifically, an MPC algorithm is used as a lateral controller, and a PI control algorithm is used as a longitudinal controller in parallel. To develop the MPC algorithm, path information (path planning) and an inner model is necessary. Thus, the path information is defined as the road center since the BRT is traveling a certain path, and the inner model is defined from the bicycle model of vehicle dynamics. The wheel steering input is controlled based on the predicted lateral movement using the inner model. To develop the PI algorithm, brake pressure and throttle position inputs are controlled based on the longitudinal velocity error. As a result, the integrated control algorithm of MPC and PI is developed in commercial tool Matlab/Simulink with a plant model which is developed in commercial tool TruckSim. In conclusion, the integrated control algorithm is verified in the simulation environment with a standard of ISO-11270 which is to test a Lane Keeping Assist System (LKAS). [ABSTRACT FROM AUTHOR]

Many trucks are used for a class of activities involving a sequence of basic load-haul-dump operations. The repetitiveness of this operation has been an enabler for autonomous vehicle technology in efforts to increase safety and efficiency. In this paper, we present a framework for the automation of the load-haul-dump operation in a mine setting using an articulated dump truck. A simulation environment for the testing of autonomous driving algorithms is developed and a custom mining environment is generated to adapt to our simulation settings. We also present an operational decomposition of the sequence of tasks and develop a finite state machine for high-level decision making based on this decomposition. A path tracking module that considers both bodies of the articulated truck is also developed. The resulting architecture was implemented to achieve autonomy for a load-haul-dump operation in the simulated environment within a fixed path. Experiments show that the proposed FSM-path tracking system can automate the load-haul-dump operation; and that the simulation environment can support the testing and development of autonomous driving algorithms for configurations such as an articulated truck. [ABSTRACT FROM AUTHOR]

Due to the declining birthrate and aging population, the shortage of labor in the construction industry has become a serious problem, and increasing attention has been paid to automation of construction equipment. We focus on the automatic operation of articulated six-wheel dump trucks at construction sites. For the automatic operation of the dump trucks, it is important to estimate the position and the articulated angle of the dump trucks with high accuracy. In this study, we propose a method for estimating the state of a dump truck by using four global navigation satellite systems (GNSSs) installed on an articulated dump truck and a graph optimization method that utilizes the redundancy of multiple GNSSs. By adding real-time kinematic (RTK)-GNSS constraints and geometric constraints between the four antennas, the proposed method can robustly estimate the position and articulation angle even in environments where GNSS satellites are partially blocked. As a result of evaluating the accuracy of the proposed method through field tests, it was confirmed that the articulated angle could be estimated with an accuracy of 0.1 ∘ in an open-sky environment and 0.7 ∘ in a mountainous area simulating an elevation angle of 45 ∘ where GNSS satellites are blocked. [ABSTRACT FROM AUTHOR]

In recent years, control design for unmanned systems, especially a tractor–trailer system, has gained popularity among researchers. The emergence of such interest is caused by the potential reduction in cost and shortage of number of workers and labors. Two industries will benefit from the advancements of these types of systems: agriculture and cargo. By using the unmanned tractor–trailer system, harvesting and cultivating plants will become a safe and easy task. It will also cause a reduction in cost which in turn reduces the price on the end consumers. On the other hand, by using the unmanned tractor–trailer system in the cargo industry, shipping cost and time for the item delivery will be reduced. The work presented in this paper focuses on the development of a path tracking and a cascaded controller to control a tractor–trailer in reverse motion. The path tracking controller utilizes the Frenet–Serret frame to control the kinematics of the tractor–trailer system on a desired path, while the cascade controller's main objective is to stabilize the system and to perform commands issued by the path tracker. The controlled parameters in this proposed design are the lateral distance to a path, trailer's heading angel, articulated angel, and articulated angle's rate. The main goal of such controller is to follow a path while the tractor–trailer system is moving in reverse and controlling the stability of the articulated vehicle to prevent the occurrence of a jackknife incident (uncontrolled state). The proposed controller has been tested in a different scenario where a successful implementation has been shown. [ABSTRACT FROM AUTHOR]

Automatic guidance systems and autonomous vehicles require tested methods of path generation to ensure successful maneuvers (such as automatic trajectory correction and headland turn management). In this study, an evolution of Zakin’s kinematic modeling, as applied in the automobile industry, is proposed for an agricultural poly-articulated vehicle (representing a tractor or other type of towing vehicle with one or more towed implements attached with an articulated hitch). Geometry, vehicle ground speed, and angular steering velocity are considered in the generation of maneuvering paths. Based on the specifics of real field conditions (slope, plant residue, resistance due to soil compaction, etc.), the initial model was improved by introducing correction coefficients. An experimental setup is proposed using a tractor with two towed implements and a testing method involving point-to-point path comparison. The modeling method has potential for integrating more complex procedures (such as path generation, geolocation, and following) into the design of a maneuvering management system for agricultural machines, which can contribute to the efficiency of field operations. [ABSTRACT FROM AUTHOR]

With the development of global urbanization and the construction of regional urbanization, residents around urban cities are increasingly making demands on urban public transportation system. A new kind of modern public transportation vehicle named Multi-Articulated Guided Vehicle based on Virtual Track (MAAV-VT) with the advantages of beautiful, smart energy conservation and environmental protection is proposed in this paper, which aims at optimizing the public transportation system between and within urban areas. Therefore, concentrating on the general design and control strategy, the main contents of this paper are as follows. At first, the design concepts and key technologies of MAAV-VT are introduced. It is the fusion of urban rail transit operation mode and advanced automotive technologies, which have the characteristics of 100% low-floor, medium to high velocity, medium to big capacity, and low construction cost. Then, as the core subsystem, to guarantee the properties of self-guiding and trajectory tracking of the new vehicle, this paper is focused on the control system based on the dynamics and kinematics model of the whole multi-articulated vehicle. The multi-trace-points cooperative trajectory tracking control strategy on the basis of the circulation of feasible path generation method is proposed and the lateral controller is designed for trajectory tracking. The process of feasible path generation is conducted once the tracking error exceeded. A simulation platform is built considering the mechanical properties of each vehicle element and the characteristic of articulated mechanism. Finally, the function of control system is validated. The tracking error of each vehicle elements would be reduced to make sure the whole multi-articulated vehicle moves along the preset virtual track. [ABSTRACT FROM AUTHOR]

This article develops a four-level test system for accurately evaluating pavement compaction performance of autonomous articulated vehicles. In the evaluation layer, various performance indicators are evaluated, including the stability, rapidity and accuracy of trajectory tracking, and the ratio of required compaction to actual compaction once and twice and compaction repeatability index when pavement compaction. The guidance and control layer can be described in terms of theory and application. At the theoretical level, the line of sight guidance algorithm and incremental proportional integral control algorithm are introduced to eliminate system control lag. Among them, the best line of sight guidance and incremental proportional integral control parameters are selected by the Elitist strategies genetic algorithm, and the initial parameters are set according to human driving experience initial control parameters. At the application level, the BECKHOFF controller, a kind of programmable logic controller, acts as the main guidance and control unit in the four-level control system, fixed speed is given to the autonomous articulated vehicle by setting the engine speed and transmission gear, and steering wheel angle is adjusted in real time by the BECKHOFF controller. In the sensor level, a simplified sensor configuration is used to reduce overall cost. The comparative simulation results of no controller, the incremental proportional integral controller, line of sight guidance-incremental proportional integral controller with human driving experience initial control parameters, line of sight guidance-incremental proportional integral controller with random initial control parameters, and elitist strategies genetic algorithm-line of sight guidance-incremental proportional integral controller with human driving experience initial control parameters manifest evidently that the proposed elitist strategies genetic algorithm-line of sight guidance-incremental proportional integral controller with human driving experience initial control parameters has almost no steady-state error, no overshoot, and short settling time. Field results show that ratio of required compaction to actual compaction once achieves 100%, ratio of required compaction to actual compaction twice achieves 94.6%, and compaction repeatability index achieves 35%. [ABSTRACT FROM AUTHOR]

The special steering characteristics and task complexity of autonomous articulated vehicle (AAV) make it often require multiple forward and backward movements during autonomous driving. In this paper, we present a simple yet effective method, named head correction with fixed wheel position (HC-FWP), for the demand of multiple forward and backward movements. The goal-directed rapid-exploring random tree (GDRRT) algorithm is first used to search for a feasible path in the obstacle map, and then, the farthest node search (FNS) algorithm is applied to obtain a series of key nodes, on which HC-FWP is used to correct AAV heading angles. Simulation experiments with Dynapac CC6200 articulated road roller parameters show that the proposed improved goal-directed rapid-exploring random tree (IGDRRT), consisting of GDRRT, FNS, and HC-FWP, can search a feasible path on maps that require the AAV to move back and forth. [ABSTRACT FROM AUTHOR]

This paper presents a model predictive control (MPC)-based algorithm for rollover prevention of an autonomous electric road sweeper (AERS). For AERS, the basic function of autonomous driving is a path- and velocity-tracking control needed to make a vehicle follow given path and velocity profiles. On the other, the AERS adopts an articulated frame steering (AFS) mechanism which can make cornering behavior agile. Moreover, the tread of the AERS is narrow, and the height of the mass center is high. As a result, it is prone to roll over. For this reason, it is necessary to design a controller for path and velocity tracking and rollover prevention in order to improve maneuverability and roll safety of the AERS. A kinematic model was adopted as a vehicle one for the AERS. With the vehicle model, reference states of position and velocity were determined that are needed to make the AERS track the reference path and prevent rollover. With the vehicle model and reference states, an MPC-based motion controller was designed to optimize articulation angle and velocity commands. The load-transfer ratio (LTR) was used to measure a rollover propensity. To evaluate the proposed algorithm, a simulation was conducted for the U-turn scenario. Simulation results show that the proposed algorithm improves path tracking and prevents the rollover of the AERS. [ABSTRACT FROM AUTHOR]

The problem of asymptotic stabilization for straight and circular forward/backward motions of a tractor-trailer system is addressed using Lyapunov techniques. Smooth, bounded, nonlinear control laws achieving asymptotic stability along the desired path are designed, and explicit bounds on the region of attraction are provided. The problem of asymptotic controllability with bounded control is also addressed. [ABSTRACT FROM AUTHOR]

This paper presents a method to prevent the rollover of autonomous electric road sweepers (AERS). AERS have an articulated frame steering (AFS) mechanism. Moreover, the heights of the center of gravity of the front and rear bodies are high. As such, they are prone to rolling over at low speeds and at small articulation angles. A bicycle model with a nonlinear tire model was used as a vehicle model for AERS. Using that vehicle model, path tracking and speed controllers were designed in order to follow a predefined path and speed profile, respectively. To check the rollover propensity of AERS, load transfer ratio (LTR) based the rollover analysis was completed. Based on the results of the analysis, a rollover prevention scheme was proposed. To validate the proposed scheme, a simulation was conducted using a U-shaped path under constant speed conditions. From the simulation, it was shown that the proposed scheme is effective in preventing AERS from rolling over. [ABSTRACT FROM AUTHOR]

• Effect of changing the control guidance point in articulated vehicles. • Unsafe maneuver reduction for autonomous articulated vehicles. • Scalable guidance point selection strategy for articulated vehicles. • Parameter scheduling for control guidance point variation. In this work we study the effect of changing the vehicle guidance point position over the collision risk and motion control performance of an N-trailer vehicle. Based on a Monte Carlo method, we are able to find the correlation among motion control performance, trajectory curvature variation and guidance point position, to strategically select the latter to enhance the motion control performance. The performance metrics consider controller effort and manoeuvrability space penalties associated with off-track errors and unsafe manoeuvres of the entire vehicles' chain. To validate scalability of the guidance point selection strategy, several N-trailer vehicles were tested in simulation to track a trajectory with abrupt curvature changes, similar to the trajectories executed by machinery in agricultural operations. The performance results are compared to ones obtained using traditional strategy to show the reduction of dangerous manoeuvres as internal turning from 24.5% up to 42.6% as well as a reduction of the resultant off-track errors from 17.3% up to 26.84% in the cases from 4 to 10 trailers respectively. [ABSTRACT FROM AUTHOR]

• Collision-free navigation for autonomous articulated vehicles. • Algoritmization with a tight combination of planning and control stages. • Route planning for non-completely automated agricultural operations. • Optimal selection of the guidance point location used for motion control. Articulated vehicles composed of a tractor and several passive trailers are commonly used for transportation purposes in agricultural applications. The increment of the number of trailers increases the payload capacity, but on the other hand, it also implies serious motion constraints, especially in turning scenarios where there is a greater risk of collisions with the crops. In this context, to reduce dangerous maneuvers during the headland turning scenarios, this paper presents a headland turning algorithmization for the N-trailers, characterized by unifying the motion planning stage with the motion control stage, in contrast to most of the available solutions which treat these stages independently. The proposed algorithmization delivers an admissible headland reference path and the location of the vehicle guidance point for the path-following task, to reduce both possible collisions with the crop and the inter-segment collisions. The proposed approach was validated by solving several illustrative problems which address various field/crop dimensions and vehicles with different number of trailers. The results showed that the proposed system can find and execute a safe maneuver in a broad range of known situations from the agricultural domain. [ABSTRACT FROM AUTHOR]