A path planning and path-following control framework for a general 2-trailer with a car-like tractor

Maneuvering a general 2-trailer with a car-like tractor in backward motion is a task that requires significant skill to master and is unarguably one of the most complicated tasks a truck driver has to perform. This paper presents a path planning and path-following control solution that can be used to automatically plan and execute difficult parking and obstacle avoidance maneuvers by combining backward and forward motion. A lattice-based path planning framework is developed in order to generate kinematically feasible and collision-free paths and a path-following controller is designed to stabilize the lateral and angular path-following error states during path execution. To estimate the vehicle state needed for control, a nonlinear observer is developed which only utilizes information from sensors that are mounted on the car-like tractor, making the system independent of additional trailer sensors. The proposed path planning and path-following control framework is implemented on a full-scale test vehicle and results from simulations and real-world experiments are presented.Comment: Preprin

DEVELOPMENT OF TEST ENVIRONMENTS FOR REVERSE ASSIST FUNCTIONS AS APPLIED TO AN A-DOUBLE VEHICLE COMBINATION

High-capacity transport vehicles reduce costs and improve efficiency. Long vehicle combinations such as an A-double combination vehicle (Tractor + semitrailer + dolly + semitrailer) improve transportation efficiency but they are extremely difficult to manoeuvre in tight spaces and in the reverse direction. This document summarizes developing environments to test reverse assist functions as applied to the A-double combination vehicle. These environments create a rapid prototyping platform consisting of a virtual and a scaled environment to test and validate controller concepts. The behaviour of the plant model in the virtual environment, the scaled vehicle model and the plant model in VTM (Volvo Truck Model) are studied and compared. A proportional controller is developed to test the environments and evaluate the process of concept development using the rapid prototype platform. The controller performance is evaluated and a possibility of incorporating integral controller is discussed

Theory and practice of reversing control on multiply-articulated vehicles

A path-tracking controller is presented for automating the reversing of multiply-articulated vehicles. This uses a state feedback approach and steers the wheels of the front axle to ensure that the rearmost vehicle unit tracks a specified path. Linear closed-loop analysis is performed and shows that the controller is stable for vehicles with up to six trailers. The controller is implemented on three full-size experimental heavy vehicles: a ‘tractor–semitrailer’, a ‘B-double’ vehicle and a ‘B-triple’ vehicle, which have one trailer, two trailers and three trailers respectively. Experimental results are presented and the controller performance is evaluated. All test vehicles were able to track the paths to within 400 mm of the desired path. This research was funded by the Engineering and Physical Sciences Research Council (EPSRC) and Volvo Trucks through an Industrial CASE award. The authors would like to acknowledge Leo Laine and Carl-Johan Hoel from Volvo Trucks for their collaboration and contributions to the research.This is the author accepted manuscript. The final version is available from Sage via http://dx.doi.org/10.1177/095440701559691

K-BMPC: Derivative-based Koopman Bilinear Model Predictive Control For Tractor-trailer Trajectory Tracking With Unknown Parameters

Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in dynamics are unknown. To address this constraint, we propose a derivative-based lifting function construction method, show that the corresponding infinite dimensional Koopman bilinear model over the lifting function is equivalent to the original control-affine system. Further, we analyze the propagation and bounds of state prediction errors caused by the the truncation in derivative order. The identified finite dimensional Koopman bilinear model would serve as predictive model in next step. Koopman Bilinear Model Predictive control (K-BMPC) is proposed to solve the trajectory tracking problem. We linearize the bilinear model around the estimation of the lifted state and control input. Then the bilinear Model Predictive Control problem is approximated by a quadratic programming problem. Further, the estimation is updated at each iteration until the convergence is reached. Moreover, we implement our algorithm on a tractor-trailer dynamic system, taking into account the longitudinal and side slip effects. The open-loop simulation shows the proposed Koopman bilinear model captures the dynamics with unknown parameters and has good prediction performance. Closed loop tracking results show the proposed K-BMPC exhibits elevated tracking precision along with commendable computational efficiency. The experimental results demonstrate the feasibility of the proposed method

The Effect of Sideslip on Jackknife Limits During Low Speed Trailer Operation

Jackknifing refers to the serious situation where a vehicle-trailer system enters a jackknife state and the vehicle and trailer eventually collide if trailer operation is not corrected. This paper considers low speed trailer maneuvering typical of trailer backing where jackknife state limits can vary due to sideslip caused by physical interaction between the vehicle, trailer, and environment. Analysis of a kinematic model considering sideslip at the vehicle and trailer wheels indicates that vehicle-trailer systems should be divided into three categories based on the ratio of hitch length and trailer tongue length, each with distinct behaviors. The Long Trailer category may have no jackknifing state while the other two categories always have states leading to jackknifing. It is found that jackknife limits, which are the boundaries between the jackknifing state and the recoverable regions, can be divided into safe and unsafe limits, the latter of which must be avoided. Simulations and physical experiments support these results and provide insight about the implications of vehicle and trailer states with slip that lead to jackknifing. Simulations also demonstrate the benefit of considering these new slip-based jackknife limits in trailer backing control

Path-tracking of a tractor-trailer vehicle along rectilinear and circular paths: A Lyapunov-based approach

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