Tractor-trailer Vehicle Research Articles

Model Predictive Control Based Path Planner Design for On-road Autonomous Tractor Trailer Vehicles

Efficient path planning for on-road autonomous tractor trailer vehicles (ATTVs) is a complex task due to the intricate kinematics introduced by the articulated trailer. This technical paper introduces a novel Model Predictive Control (MPC) based lateral path planner designed to address the unique challenges of maneuvering ATTVs, particularly in environments that require navigation through narrow spaces and around multiple obstacles on well-structured roads. The authors have expertly developed a Cartesian kinematic model tailored for ATTVs and have innovatively applied the Frenet frame to better apply constraints in structured road environments. The efficacy of the proposed path planner is confirmed through real-time testing on actual roadways, showcasing its practical application and the advantages it offers over existing methods.

Fixed-Time Consensus for Multiple Tractor-Trailer Vehicles With Dynamics Control: A Distributed Internal Model Approach

Fixed-Time Consensus for Multiple Tractor-Trailer Vehicles With Dynamics Control: A Distributed Internal Model Approach

An Efficient Trajectory-Planning Method With a Reconfigurable Model for Any Tractor-Trailer Vehicle

Trajectory planning for a tractor-trailer vehicle (TTV) is a tough task even in a static environment because of its complicated kinematic constraints. This paper aims to efficiently plan an optimal trajectory with a reconfigurable model for any TTV in the static environment. A reconfigurable modelling method is first proposed to simulate the TTV with arbitrary number of trailers and hitching mode. Then, the planning task is formulated as a nonlinear optimal control problem. However, it is too difficult to be solved, and is time-consuming to find a feasible solution, let alone the optimal one. To this end, a novel guided solving method (GSM) is proposed to solve this problem progressively with great efficiency. GSM is divided into two steps. Step 1 plans rough trajectories for the TTV, taken as an initial guess for the next step. In step 2, the problem is split into a sequence of subproblems, solved by asynchronously expanding the size of both vehicle body and obstacles, speeding up the optimization process. Simulations are carried out in several complex cases, and four competitive algorithms are selected for comparison. The results show that the proposed method outperforms others in the feasibility and efficiency of problem-solving for trajectory planning. Specifically, the proposed method is feasible in all testing cases, and saves up to 81.4%, 83.2% and 55.9% solving time compared with other three methods in the 135° turn scenario, respectively, bringing the great improvement of planning efficiency.

Recent Advancements and Future Trends in Indirect Bridge Health Monitoring

Bridges hold an imperative role in the transportation network and infrastructure. Continuous monitoring of their condition is crucial for the efficient operation of transportation facilities. Conventional bridge monitoring has relied on direct sensor instrumentation on the bridge to obtain the bridge response. Indirect bridge health monitoring (iBHM) leverages the moving traffic over the specific bridge of interest. The benefit of iBHM lies in the fact that bridge instrumentation is no longer required since the moving vehicle is instrumented with sensors. The collected data can be used to identify the dynamic characteristics of the bridge. Additionally, the method can be used to detect damage using the information of the vehicle bridge interaction. This paper systematically reviews the recent research progress in iBHM, and the review is organized based on four main groups, namely single test vehicles, tractor-trailer vehicles, crowdsourced/smartphone monitoring, and contact point (CP) response. The primary classification is further divided according to the nature of the investigation, which includes theoretical and numerical investigations, laboratory tests, and full-scale validations. After a concise and systematic review, the existing challenges and future recommendations are outlined. It is anticipated that this review will provide valuable guidance for researchers and practitioners of bridge engineering to understand better the evolution, development, and future trends of iBHM.

An Intrinsically Stable MPC Approach for Anti-Jackknifing Control of Tractor-Trailer Vehicles

Tractor-trailer vehicles are affected by jackknifing, a phenomenon that consists in the divergence of the trailer hitch angle and ultimately causes the vehicle to fold up. For the case of backward motions, in which jackknifing can occur at any speed, we present a control method that drives the vehicle along generic reference Cartesian trajectories while avoiding the divergence of the hitch angle. This is obtained thanks to a feedback control law that combines two actions: a tracking term, computed using input–output linearization, and a corrective term, generated via IS-MPC, an intrinsically stable MPC scheme which is effective for stable inversion of non-minimum phase systems. The successful performance of the proposed anti-jackknifing control is verified through simulations and experiments on a purposely built one-trailer prototype. To show the generality of the approach, we also apply and test the proposed method on a two-trailer vehicle.

Adaptive Line-of-Sight Tracking Control for a Tractor-Trailer Vehicle System With Multiple Constraints

In this paper, for the line-of-sight (LOS) tracking problem of a tractor-trailer vehicle system, we propose a novel adaptive constrained tracking control algorithm for the trailer to track a desired trajectory, while satisfying multiple <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">performance</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">feasibility</i> constraint requirements during the operation. To deal with these constraint requirements, both a universal barrier function approach and a novel state transformation scheme are incorporated to deal with constraints of different nature. An adaptive control structure is introduced to deal with system parameter uncertainties and external disturbances. We show that for the LOS distance and angle tracking errors, exponential convergence into small neighbourhoods of equilibrium can be guaranteed, with the convergence rate depending on the control input and adaptive gains. In the end, a simulation example and an experimental study further demonstrate the efficacy of the proposed algorithm.

Optimization-Based Maneuver Planning for a Tractor-Trailer Vehicle in a Curvy Tunnel: A Weak Reliance on Sampling and Search

This study is focused on the maneuver planning problem for a tractor-trailer vehicle in a curvy and tiny tunnel. Due to the curse of dimensionality, the prevalent sampling-and- search-based planners used to handle a rigid-body vehicle well become less efficient when the trailer number grows or when the tunnel narrows. This fact also has impacts on an optimization-based planner if it counts on a sampling-and-search-based initial guess to warm-start. We propose an optimization-based maneuver planner that weakly relies on the sampling and search, hoping to get rid of the curse of dimensionality and thus find optima rapidly. The proposed planner comprises three stages: stage 1 identifies the homotopy class via A* search in a 2D grid map; stage 2 recovers the kinematic feasibility with softened intermediate problems iteratively solved; stage 3 finds an optimum that strictly satisfies the nominal collision-avoidance constraints. Optimization-based planners are commonly known to run slowly, but this work shows that they have obvious advantages over the prevalent sampling-and-search-based planners when the solution space dimension is high and/or the constraints are harsh.

Real-Time Trajectory Planning for On-road Autonomous Tractor-Trailer Vehicles

Real-Time Trajectory Planning for On-road Autonomous Tractor-Trailer Vehicles

Robust Tube-Based Model Predictive Control for Lane Change Maneuver of Tractor-Trailer Vehicles Based on a Polynomial Trajectory

This paper reports an effective quintic polynomial-based trajectory planning approach and a robust tube-based model predictive control (RTMPC) method for an underactuated tractor-trailer vehicle system during lane change maneuver. To begin with, a time-based quintic polynomial function is introduced for implementation of trajectory planning, which takes vehicle system safety, comfort, and traffic efficiency into account. After that, an RTMPC scheme, consisting of a nominal system-oriented model predictive controller and an ancillary feedback control law, is proposed to construct posture controller, such that favorable transient performances can be achieved for the trajectory tracking process. Lastly, the simulation results confirm that the proposed lane change trajectory planning and tracking control methods can effectively perform the lane change behaviors for tractor-trailer vehicles.

An indirect method for bridge mode shapes identification based on wavelet analysis

Mode shapes have been playing a vital role in the research and application of bridge structural health monitoring. This paper presents a novel indirect method identifying bridge mode shapes using dynamic responses of a tractor–trailer vehicle model, which consists of one tractor and three instrumented trailers. In an effort to eliminate the road roughness effect, accelerations of adjacent trailers are firstly subtracted. Wavelet analysis is then employed to identify bridge mode shapes from the subtracted accelerations in an iterative manner. Furthermore, wavelet denoising algorithm is adopted to improve the identification accuracy in the presence of measurement noise. Systematic numerical simulations, in which a tractor–trailer model passes over an expressway bridge, are conducted in order to investigate the performance of the proposed method. Sensitivity analysis including vehicle speed, class of road roughness, and noise level are studied in this numerical investigation. Results demonstrate that the proposed method is able to identify bridge modal frequencies and mode shapes with satisfactory resolution, accuracy, and robustness.

Observer‐based neural adaptive control of a platoon of autonomous tractor–trailer vehicles with uncertain dynamics

This study addresses the platoon formation control problem of multiple off-axle hitching tractor–trailers with limited communication ranges, under model uncertainties and external disturbances, without any collision and without velocity and acceleration measurements for the first time. Towards this end, a new second-order Euler–Lagrange formulation of tractor–trailers is introduced under the prescribed performance design procedure that preserves all structural properties of the tractor–trailer dynamics. Then, a prescribed performance non-linear transformation, a saturated filtered tracking error, radial basis function neural networks, an adaptive robust controller, and a high-gain observer are creatively employed to design a novel platoon output-feedback controller, which forces the vehicles to construct a desired convoy while guaranteeing the robust performance against unmodelled dynamics and external forces and ensuring inter-vehicular communication maintenance, collision avoidance between each successive pair in the convoy of vehicles, and some preassigned desired response specifications of platoon formation errors including overshoot/undershoot, convergence speed, and ultimate tracking accuracy. By utilising a Lyapunov-based stability analysis, a semi-global uniform ultimate boundedness of formation errors is ensured with prescribed performance. Finally, simulation results illustrate the efficacy of the proposed control system.

Simulated Braking Performance Comparison of an Electric Drum Brake and a Hydraulic Drum Brake Systems

The most important safety equipment for the operation of a vehicle is the brake equipment. This research attempts to develop an all-electric braking system that can be used in an electric vehicle. Since the drum brake requires lower actuation input than the disk brake in order to deliver the same amount of braking force. It seems logical to be used in the electric vehicle as far as minimizing energy usage is concerned. The proposed electric drum brake system conceptually is not new as it has been used as a trailer brake for a tractor-trailer vehicle. Adopting the trailer brake for a passenger vehicle requires proper downsizing and different braking control scheme. This paper presents the modelling and simulation results of the proposed electric drum brake. The main interest is its braking performance which can be investigated by the brake force profile or the brake force characteristic. The results are compared with the braking performance of the conventional hydraulic drum brake system which is using validated data from the literature. The simulation results show that the braking force of the electric drum brake system is two times higher than that is of the hydraulic drum brake system subjected to the same actuation force. The results from this paper will be valuable for the development of the controller in the future.

Model predictive-based tractor-trailer stabilisation using differential braking with experimental verification

Different types of instability modes in tractor-trailer vehicles, including jackknifing and snaking, necessitate designing a fast and effective control strategy. In this paper, a model predictive controller (MPC) is developed to prevent these instability modes in a car-trailer vehicle as a specific form of tractor-trailer vehicles equipped with differential braking. The effectiveness of the control action when the differential braking is applied only to the tractor and only to the trailer is also studied comparatively. The developed MPC controller utilises an affine tyre force model, and the control actions are limited based on the capacity of the tyres. The aim of the controller is to ensure that the tractor and the trailer follow the desired yaw rate and the desired hitch angle, respectively. The controller performance is evaluated through experimental tests and simulations. Experimental tests are conducted on an all-wheel-drive electric Chevrolet Equinox and a student-built research trailer, both equipped with an independent braking module on each wheel. In the simulations, the controller is implemented in MATLAB/Simulink, and an experimentally validated CarSim model of the tested tractor-trailer vehicle is employed. The results show that the designed MPC controller effectively prevents both instability modes; however, differential braking has much more capacity when it is applied to the tractor.

Optimization-Based On-Road Path Planning for Articulated Vehicles

Maneuvering an articulated vehicle on narrow road stretches is often a challenging task for a human driver. Unless the vehicle is accurately steered, parts of the vehicle's bodies may exceed its assigned drive lane, resulting in an increased risk of collision with surrounding traffic. In this work, an optimization-based path-planning algorithm is proposed targeting on-road driving scenarios for articulated vehicles composed of a tractor and a trailer. To this end, we model the tractor-trailer vehicle in a road-aligned coordinate frame suited for on-road planning. Based on driving heuristics, a set of different optimization objectives is proposed, with the overall goal of designing a path planner that computes paths which minimize the off-track of the vehicle bodies swept area, while remaining on the road and avoiding collision with obstacles. The proposed optimization-based path-planning algorithm, together with the different optimization objectives, is evaluated and analyzed in simulations on a set of complicated and practically relevant on-road planning scenarios using the most challenging tractor-trailer dimensions.

Trajectory planning and robust tracking control for a class of active articulated tractor-trailer vehicle with on-axle structure

Traditional articulated vehicles exhibit poor steering performance since there exist no direct rotating moment for the underactuated trailers, which cause such vehicles nearly cannot work well in the narrow space. To overcome this shortcoming associated with the traditional articulated vehicles, an active articulated structure is proposed, in which a steering motor is introduced at the articulated joint of tractor and trailer, in addition to utilizing mecanum wheels as trailer wheels. On the basis of this structure, a coordinated control method is designed to ensure the vehicle kinematics constraints and dynamic maneuverability. The coordination control consists of two level controllers. On the level of kinematics, model predictive control (MPC) is adopted as posture controller, which can solve the non-holonomic problem of the whole active articulated tractor-trailer vehicle system; On the dynamic level, a sliding mode control (SMC) is introduced to design a dynamic controller to track the desired velocities generated online, which can increase the robustness of the system. The simulation results show that the proposed active articulated tractor-trailer vehicle system has better maneuverability compared with the traditional one, and the proposed control strategy can ensure the required control effect.

Tractor-Trailer Vehicle Trajectory Planning in Narrow Environments With a Progressively Constrained Optimal Control Approach

Trajectory planning for a tractor-trailer vehicle is challenging due to the non-convex collision avoidance constraints and the unstable kinematics. This article aims to plan precise and optimal trajectory for a car-like tractor that tows standard or general N-trailers in an environment with static obstacles. This trajectory planning scheme can be formulated as a unified optimal control problem, but numerically solving that problem is difficult. Two efforts are made to address the difficulty. First, an extended hybrid A* search algorithm is proposed to provide an initial guess for the numerical optimization. Second, the numerical optimization process is eased through adopting a progressively constrained optimization strategy, which is about sequentially handling the kinematics, collision avoidance constraints, and boundary conditions. Particularly in dealing with the collision avoidance constraints, an adaptively homotopic warm-starting algorithm is proposed, which defines a sequence of subproblems with the obstacle areas adaptively increase towards their nominal scales. Through solving these subproblems in a sequence, the whole collision avoidance difficulties are dispersed and gradually tackled. Comparative simulations are conducted to validate the efficacy of the proposed trajectory planner.

An analysis of fatal log truck crashes in the United States from 2011 through 2015

ABSTRACTAnalyses of data obtained from the United States (US) federally maintained Fatality Analysis Reporting System (FARS) crash database indicated that fatal log truck crashes increased across the US. The reported occurrences of log trucks involved in a fatal crash increased by 41% between 2011 and 2015. Analyses of 383 crashes involving log trucks were performed nationally and regionally. Most log truck crashes (84%) involved tractor-trailer configurations. We also compared fatal crashes using only tractor-trailer vehicle configurations for log trucks versus other tractor-trailer cargo body types. Logging tractor-trailers represent 326 (3.4%) of the 9597 tractor-trailers involved in a fatal crash over the same period. Both logging tractor-trailer and other tractor-trailer crashes increased during the 5-year period. Other large truck crashes increased 19% while log truck tractor-trailer crashes increased by more than 33%. Log trucks were the oldest vehicles involved in fatal crashes, with an average age of 13.0 years, which was significantly higher (p < 0.0001) than the overall average for all trucks of 7.6 years. During a fatal crash, log trucks experienced a rollover 21% of the time, which is significantly higher (p < 0.0001) than the overall average of 12% rollovers for other large trucks. Results suggest that programs focused on log truck driver training may want to emphasize the increased risk of rollovers, defensive driving and awareness of other vehicles, as well as awareness of maintenance needs associated with older vehicles.

Derivation of a multi-body model of an articulated vehicle

In this research, a five degree-of-freedom vehicle dynamics bicycle model is developed for a double tractor-trailer vehicle. Lagrange's equations are used to develop the equations of motion. Due to their complexity, the equations are symbolically derived using Maple. The equations are linearised and placed in state-space form; and, are numerically simulated using Matlab. Validation with TruckSim demonstrates the model's performance. At low forward speeds, the model closely represents the motions of the non-linear reference. As speed is increased, the model over-predicts the response, but the trends are similar. The differences are more pronounced with a heavy load condition. The model can be used to perform parametric stability studies and full numerical simulations, whereby state trajectories can be investigated at low lateral acceleration levels.

An ESO-based integrated trajectory tracking control for tractor–trailer vehicles with various constraints and physical limitations

ABSTRACTThis paper develops an effective integrated control strategy for the trajectory tracking control of a tractor–trailer vehicle which suffers from inaccessible system states and uncertain disturbance for practical implementation. In addition, diverse problems, such as nonholonomic constraints, underactuated dynamics, physical limitations, etc, can be resolved favourably all together. Aiming to the vehicle trajectory tracking, a constrained model predictive control (MPC) is introduced as a trajectory tracking module, by which the underactuated dynamics, various constraints and physical limitations, can be tackled at the same time. For the desired velocity tracking, a robust global terminal sliding mode control (GTSMC) is employed to guarantee the finite-time convergence of the velocity tracking process, which will improve the transient performance to a great extent. Particularly, in the absence of velocity information, an extended state observer (ESO) is developed to estimate the vehicle velocity in addition to simultaneously obtaining the uncertain disturbance information, which offers prerequisite for the previous control approaches. The simulation results confirm that the presented control strategy can synthesise varied control techniques effectively and deal with diverse problems for the trajectory tracking of tractor–trailer vehicles successfully.

Forward tracking of complex trajectories with non-Standard N-Trailers of non-minimum-phase kinematics avoiding a jackknife effect

ABSTRACTIt is a common conviction that forward motion control of tractor-trailer vehicles is a substantially simpler problem relative to reversing with trailers. This opinion may be misleading when considering the N-trailer vehicles moving forward with positive hitching offsets when a guidance point is located on a trailer. Due to the non-minimum-phase nature of vehicle kinematics, closing a feedback from a trailer posture can lead to the jackknife effect in this case. So far, there has been no solution to this problem for the N-trailers admitting trajectories of a varying curvature. To fill this gap, we propose a scalable and modular control strategy applicable to the N-trailer vehicles equipped solely with off-axle interconnections. The concept relies on a transformation of the control problem posed for the non-minimum-phase kinematics into a corresponding problem formulated for a virtual vehicle of minimum-phase kinematics, which can be solved by using the recently proposed cascade-like controller.