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

Implementation of Reversing Control on a Doubly Articulated Vehicle

The problem of reversing vehicles with two trailers could be solved with a semi-autonomous assistance system for automatically steering the vehicle. In the literature found, no controllers have been implemented on a full-size vehicle with two trailers. In this paper, two simple path-tracking controllers are presented for automating the reversing of a “B-double” vehicle, consisting of a tractor and two trailers. One of the controllers is a heuristic “preview point” controller; the other uses a state feedback approach. The controllers steer the wheels on the front axle so as to stabilize the vehicle in reverse and control the path of the rearmost axle to follow a prescribed path. A tuning strategy is outlined where both controllers are tuned using the linear quadratic regulator and have the same closed-loop poles. The two controllers are implemented on a full-size B-double test vehicle. Experimental results are discussed, and the controller performances are evaluated against criteria. With the state feedback controller, the test vehicle was able to track target paths, consisting of a roundabout and a lane change, to within 50 mm.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. The authors would like to acknowledge Denby Transport for their loan of the ‘Extra’ Eco-Link B-trailer for use in vehicle testing. The authors would like to acknowledge the members of the CVDC who supported the work in this paper. At the time of writing, the Consortium consisted of the University of Cambridge with the following partners from the heavy vehicle industry: Anthony Best Dynamics, Camcon, Denby Transport, Firestone Air Springs, GOODYEAR DUNLOP, Haldex, Motor Industry Implementation of Reversing Control on a Doubly-Articulated Vehicle 15 Research Association, SDC Trailers, SIMPACK, Tinsley Bridge, Tridec, Volvo Trucks, and Wincanton

An Investigation of Higher Capacity Urban Freight Vehicles

Studies have shown that increasing the capacity of Heavy Goods Vehicles is one of the most effective ways of reducing fuel consumption per tonne-kilometre of freight moved, with consequent reductions in greenhouse and noxious emissions. Some of the disadvantages of larger vehicles are more pronounced in urban environments, including safety of other road users, and reduced manoeuvrability. This thesis discusses technologies for improving safety of vulnerable road users, and frameworks for assessing the maximum size of urban freight vehicles. An overview of the freight industry is provided in Chapter 1, with a focus on maximising capacity as a method for reducing emissions. Chapter 2 focusses on the safety of vulnerable road users, through development of a camera-based detection system for cyclists, which is essential for a predictive collision avoidance system. The proposed system is accurate to within 10 cm at distances of greater than 1 m from the vehicle, but suffers from loss of accuracy at close range, and in poor lighting conditions. The logistics of urban freight operations are analysed in Chapter 3, including a comparison between two supermarket home delivery operations, and an analysis of refuse collection schedules. A framework is proposed for selecting an optimum vehicle size for a multi-drop operation, given reductions in driving distance and time spent on other procedures. A potential capacity increase of 80% is demonstrated, requiring a 50% reduction in driving distance, and automation of certain procedures. Chapters 4 to 6 propose a novel framework for assessing the optimum size of Heavy Goods Vehicles, according to the limits of their manoeuvrability. This method is based on simulation of vehicles attempting a library of real-world manoeuvres. Simulation models are described in Chapter 4, and path planning algorithms in Chapter 5. The framework is evaluated on three case studies: a 4.25 t grocery delivery vehicle, a 44 t articulated refuse collection vehicle, and a 44 t general urban vehicle with rear axle steering. A range of potential higher capacity vehicles are proposed in Chapter 6 for those applications The impact of rear axle steering on manoeuvrability is also considered in detail in Chapter 6. It is shown that the use of rear axle steering does not always allow the use of a longer vehicle, because a rear axle steered vehicle cannot compromise between cut-in and tailswing in the way a conventional vehicle can. However, the use of rear axle steering allows reduction in both tyre wear and rear axle load limits, which permits greater vehicle fill before rear axle loads are exceeded. These results are compared, in Chapter 7, to an alternative method for modelling manoeuvrability (Performance-Based Standards). Finally, Chapter 8 presents some concluding remarks and recommendations for future work, including investigation of an improved cyclist detection system fusing cameras and ultrasonic sensors, and increased development of the manoeuvrability models to more accurately reflect real driving.This work was supported by the EPSRC, as well as the Cambridge Vehicle Dynamics Consortium, and the Centre for Sustainable Road Freigh

Vision-based trailer pose estimation for articulated vehicles

Articulated Heavy Goods Vehicles (HGVs) are more efficient than conventional rigid lorries, but exhibit reduced low-speed manoeuvrability and high-speed stability. Technologies such as autonomous reversing and path-following trailer steering can mitigate this, but practical limitations of the available sensing technologies restrict their commercialisation potential. This dissertation describes the development of practical vision-based articulation angle and trailer off-tracking sensing for HGVs. Chapter 1 provides a background and literature review, covering important vehicle technologies, existing commercial and experimental sensors for articulation angle and off-tracking measurement, and relevant vision-based technologies. This is followed by an introduction to pertinent computer vision theory and terminology in Chapter 2. Chapter 3 describes the development and simulation-based assessment of an articulation angle sensing concept. It utilises a rear-facing camera mounted behind the truck or tractor, and one of two proposed image processing methods: template-matching and Parallel Tracking and Mapping (PTAM). The PTAM-based method was shown to be the more accurate and versatile method in full-scale vehicle tests. RMS measurement errors of 0.4-1.6$^\circ$ were observed in tests on a tractor semi-trailer (Chapter 4), and 0.8-2.4$^\circ$ in tests on a Nordic combination with two articulation points (Chapter 5). The system requires no truck-trailer communication links or artificial markers, and is compatible with multiple trailer shapes, but was found to have increasing errors at higher articulation angles. Chapter 6 describes the development and simulation-based assessment of a trailer off-tracking sensing concept, which utilises a trailer-mounted stereo camera pair and visual odometry. The concept was evaluated in full-scale tests on a tractor semi-trailer combination in which camera location and stereo baseline were varied, presented in Chapter 7. RMS measurement errors of 0.11-0.13 m were obtained in some tests, but a sensitivity to camera alignment was discovered in others which negatively affected results. A very stiff stereo camera mount with a sub-0.5 m baseline is suggested for future experiments. A summary of the main conclusions, a review of the objectives, and recommendations for future work are given in Chapter 8. Recommendations include further refinement of both sensors, an investigation into lighting sensitivity, and alternative applications of the sensors.This work was supported by a "CSIR South Africa Cambridge Scholarship", funded jointly by the Cambridge Commonwealth, European & International Trust and the Council for Scientific & Industrial Research (CSIR South Africa)

Simulasi Kontrol Penjejak Lintasan pada Traktor Roda Dua untuk Lintasan Multi Segmen

AbstrakSebagian besar mata pencaharian penduduk Indonesia adalah petani. Pada umumnya petani di Indonesia masih menggunakan traktor roda dua atau traktor tangan untuk mengolah lahan pertanian. Hadirnya mesin otonom khususnya traktor roda dua menjadi solusi dalam meningkatkan produktivitas pertanian. Traktor otonom roda dua memerlukan keakuratan menyetir dalam mengolah lahan pertanian agar dapat mengikuti lintasan.Tujuan penelitian adalah untuk mensimulasikan pengontrolan penjejak lintasan pada traktor roda dua dengan sinyal kontrol kecepatan (v) dan kecepatan sudut(ω). Parameter kontrol dicari dengan melakukan tuning terhadap parameter gain kontrol kecepatan (Kv), gain kontrol kecepatan sudut (Kω)dan jarak titik pusat ke referensi (b). Penelitian ini juga mengajukan metode untuk membuat lintasan traktor multisegmen secara otomatis berdasarkan masukan data panjang dan lebar lahan pertanian serta jarak atau interval setiap alur. Hasil tuningmemberikan nilai IAE (integral absolute error) minimal 9,7971 dengan nilai parameterb = 0,1, Kv = 10 dan Kω = 10.Penerapan nilai parameter pada simulasi multi segmen menunjukkan hasiltrayectori tracking yang cukup baik yaitu tercapainya errorkeseluruhan yang cukup kecil.

Trends in vehicle motion control for automated driving on public roads

In this paper, we describe how vehicle systems and the vehicle motion control are affected by automated driving on public roads. We describe the redundancy needed for a road vehicle to meet certain safety goals. The concept of system safety as well as system solutions to fault tolerant actuation of steering and braking and the associated fault tolerant power supply is described. Notably restriction of the operational domain in case of reduced capability of the driving automation system is discussed. Further we consider path tracking, state estimation of vehicle motion control required for automated driving as well as an example of a minimum risk manoeuver and redundant steering by means of differential braking. The steering by differential braking could offer heterogeneous or dissimilar redundancy that complements the redundancy of described fault tolerant steering systems for driving automation equipped vehicles. Finally, the important topic of verification of driving automation systems is addressed

Dynamic Analysis and Obstacle Avoidance of Autonomous Tractor Semi-Trailers

This thesis fills the research gap of the tractor semi-trailer left turn problem at a city intersection. Although obstacle avoidance is a classic topic in the field of autonomous driving, however, most research is focused on passenger cars or single body vehicles. For an autonomous driving tractor semi-trailer, obstacle avoidance is an essential function. This thesis develops an obstacle avoidance algorithm for tractor semi-trailers

Transportation Mission-Based Optimization of Heavy Combination Road Vehicles and Distributed Propulsion, Including Predictive Energy and Motion Control

This thesis proposes methodologies to improve heavy vehicle design by reducing the total cost of ownership and by increasing energy efficiency and safety.Environmental issues, consumers expectations and the growing demand for freight transport have created a competitive environment in providing better transportation solutions. In this thesis, it is proposed that freight vehicles can be designed in a more cost- and energy-efficient manner if they are customized for narrow ranges of operational domains and transportation use-cases. For this purpose, optimization-based methods were applied to minimize the total cost of ownership and to deliver customized vehicles with tailored propulsion components that best fit the given transportation missions and operational environment. Optimization-based design of the vehicle components was found to be effective due to the simultaneous consideration of the optimization of the transportation mission infrastructure, including charging stations, loading-unloading, routing and fleet composition and size, especially in case of electrified propulsion. Implementing integrated vehicle hardware-transportation optimization could reduce the total cost of ownership by up to 35% in the case of battery electric heavy vehicles. Furthermore, in this thesis, the impacts of two future technological advancements, i.e., heavy vehicle electrification and automation, on road freight transport were discussed. It was shown that automation helps the adoption of battery electric heavy vehicles in freight transport. Moreover, the optimizations and simulations produced a large quantity of data that can help users to select the best vehicle in terms of the size, propulsion system, and driving system for a given transportation assignment. The results of the optimizations revealed that battery electric and hybrid heavy combination vehicles exhibit the lowest total cost of ownership in certain transportation scenarios. In these vehicles, propulsion can be distributed over different axles of different units, thus the front units may be pushed by the rear units. Therefore, online optimal energy management strategies were proposed in this thesis to optimally control the vehicle motion and propulsion in terms of the minimum energy usage and lateral stability. These involved detailed multitrailer vehicle modeling and the design and solution of nonlinear optimal control problems

An Empirical Analysis of Factors Affecting Autonomous Truck Adoption

Autonomous vehicles have the potential to revolutionize the transportation industry. The segment of truck transportation is no exception. Autonomous vehicles have the potential to improve trucking safety, to increase shipping velocity, and to decrease costs. Additionally, autonomous trucks could be an important tool to help alleviate the ongoing driver shortage that the trucking industry is contending with. Autonomous truck adoption is not guaranteed. Transportation equipment decisions are market-based, and autonomous trucks must present a compelling business case to transportation professionals. As such, it is imperative to understand the decision-making factors that drive transportation solution adoption, and how autonomous trucks could take advantage of those factors to be a competitive force in the transportation marketplace. It is also important to understand the potential effects that autonomous trucks could have on industry as well, so that companies can develop contingency plans to deal with these effects. This study uses Grounded Theory to analyze semi-structured interviews with twelve professionals from the transportation industry. A conceptual model detailing major factors that affect transportation decisions and propositions about autonomous trucks\u27 effects on industry are presented, along with a discussion. The dissertation concludes with an identification of avenues of future research to further the information uncovered in this study, and to address its limitations