Intelligent Steering Control for Heavy Articulated Vehicles
Creators: name: Rahman, Shammi
Publisher: name: University of Lincoln
Year: 2024
Subjects: H620 - Electrical engineering
H331 - Road vehicle engineering

description: Heavy Goods Vehicles (HGVs) such as tractor-semitrailers are essential to freight transportation. Though advantageous, they suffer from maneuverability issues and lateral instabilities, limiting their usage. Considering this, many researchers have sought to investigate improvement in their performance, utilising the actuators already fitted on the vehicle or proposing new ones. Steering-based control has attracted significant attention in this regard, especially due to the increased interest in autonomous driving. In many cases, using steering control is advantageous as it does not require designing or fitting new actuators. It is common to control the steering at the front axle of the vehicle for improved path guidance for autonomous driving. However, steering additional axles on HGVs, such as the axles on a semitrailer, provides the potential for improved lateral stability and enables them to access narrower roads. Against this background, the aim of this thesis is to investigate methods to improve the lateral performance of HGVs by utilising automated steering control. A newly formulated method called Artificial Flow Guidance (AFG) was used for this. AFG is a path planning system that uses velocity vectors to guide the path of the vehicle. These vectors are generated based on the path geometry and the fluid flow analogy. In nature, fluids have useful properties such as always flowing to an available outlet which makes them useful for path planning/following. Also the flow vector distribution allows for motion coordination at different points of an articulated vehicle. AFG has previously been used to provide automated steering control on light vehicles. It was shown to provide stable performance, with low computational costs. However, heavy vehicles are seen to suffer from large deviations from a desired path during transient maneuvers, e.g. when encountering changes in path curvature. To counteract this effect, AFG was modified by including a boundary layer around the desired path, which is found to be capable of providing centimeter-level precision even at higher speeds. The new formulation, called Boundary Layer AFG (BL-AFG) is a particular contribution of this thesis. In this work, attention has focused on four categories of steering control. An active steering controller was designed to steer multiple axles on the vehicle for improved path following and stability. The controller was seen to be robust to changes in trailer mass and road friction. The method was found to be applicable to different vehicle configurations and able to steer a subset of the axles without having to redesign the controller. Two automated steering controllers were then designed for a tractor-semitrailer, one which ensures that the front of the vehicle follows the reference path and, an adaptive controller which reduces the overall offtracking of the vehicle at low speeds while ensuring high-speed stability. Only the front axle on the vehicle was allowed to steer. Lessons learned from AFG, especially the variable preview distance, were applied to another simple steering control method, namely Pure Pursuit (PP). PP is popularly used when controlling light vehicles, with maneuvers limited to moderate speeds. With the improvement proposed, the PP controller is seen to provide stable path guidance for tractor-semitrailers within the simulated range of 10-80 km/h.