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Path Planning for Autonomous Vehicle by Umar Zakir Abdul Hamid,Volkan Sezer,Bin Li,Yanjun Huang,Muhammad Aizzat Zakaria Pdf
Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs ).
Autonomous Road Vehicle Path Planning and Tracking Control by Levent Guvenc,Bilin Aksun-Guvenc,Sheng Zhu,Sukru Yaren Gelbal Pdf
Discover the latest research in path planning and robust path tracking control In Autonomous Road Vehicle Path Planning and Tracking Control, a team of distinguished researchers delivers a practical and insightful exploration of how to design robust path tracking control. The authors include easy to understand concepts that are immediately applicable to the work of practicing control engineers and graduate students working in autonomous driving applications. Controller parameters are presented graphically, and regions of guaranteed performance are simple to visualize and understand. The book discusses the limits of performance, as well as hardware-in-the-loop simulation and experimental results that are implementable in real-time. Concepts of collision and avoidance are explained within the same framework and a strong focus on the robustness of the introduced tracking controllers is maintained throughout. In addition to a continuous treatment of complex planning and control in one relevant application, the Autonomous Road Vehicle Path Planning and Tracking Control includes: A thorough introduction to path planning and robust path tracking control for autonomous road vehicles, as well as a literature review with key papers and recent developments in the area Comprehensive explorations of vehicle, path, and path tracking models, model-in-the-loop simulation models, and hardware-in-the-loop models Practical discussions of path generation and path modeling available in current literature In-depth examinations of collision free path planning and collision avoidance Perfect for advanced undergraduate and graduate students with an interest in autonomous vehicles, Autonomous Road Vehicle Path Planning and Tracking Control is also an indispensable reference for practicing engineers working in autonomous driving technologies and the mobility groups and sections of automotive OEMs.
Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver by Muhammad Aizzat Zakaria,Yanjun Huang,Bin Li,Volkan Sezer,Umar Zakir Abdul Hamid Pdf
Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs ).
Autonomous Guided Vehicles by Hamed Fazlollahtabar,Mohammad Saidi-Mehrabad Pdf
This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with AGVs, programming manufacturing systems equipped with AGVs, reliability models, the reliability of AGVs, routing under uncertainty, and risks involved in AGV-based transportation. The clear style and straightforward descriptions of problems and their solutions make the book an excellent resource for graduate students. Moreover, thanks to its practice-oriented approach, the novelty of the findings and the contemporary topic it reports on, the book offers new stimulus for researchers and practitioners in the broad field of production engineering.
Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver by Muhammad Aizzat Zakaria,Yanjun Huang,Bin Li,Volkan Sezer,Umar Zakir Abdul Hamid Pdf
Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs ).
Autonomous Ground Vehicles by Ümit Özgüner,Tankut Acarman,Keith Alan Redmill Pdf
In the near future, we will witness vehicles with the ability to provide drivers with several advanced safety and performance assistance features. Autonomous technology in ground vehicles will afford us capabilities like intersection collision warning, lane change warning, backup parking, parallel parking aids, and bus precision parking. Providing you with a practical understanding of this technology area, this innovative resource focuses on basic autonomous control and feedback for stopping and steering ground vehicles.Covering sensors, estimation, and sensor fusion to percept the vehicle motion and surrounding objects, this unique book explains the key aspects that makes autonomous vehicle behavior possible. Moreover, you find detailed examples of fusion and Kalman filtering. From maps, path planning, and obstacle avoidance scenarios...to cooperative mobility among autonomous vehicles, vehicle-to-vehicle communication, and vehicle-to-infrastructure communication, this forward-looking book presents the most critical topics in the field today.
Belief State Planning for Autonomous Driving: Planning with Interaction, Uncertain Prediction and Uncertain Perception by Hubmann, Constantin Pdf
This work presents a behavior planning algorithm for automated driving in urban environments with an uncertain and dynamic nature. The algorithm allows to consider the prediction uncertainty (e.g. different intentions), perception uncertainty (e.g. occlusions) as well as the uncertain interactive behavior of the other agents explicitly. Simulating the most likely future scenarios allows to find an optimal policy online that enables non-conservative planning under uncertainty.
Creating Autonomous Vehicle Systems by Shaoshan Liu,Liyun Li,Jie Tang,Shuang Wu,Jean-Luc Gaudiot Pdf
This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.
Autonomous Robot Vehicles by Ingemar J. Cox,Gordon T. Wilfong Pdf
Autonomous robot vehicles are vehicles capable of intelligent motion and action without requiring either a guide or teleoperator control. The recent surge of interest in this subject will grow even grow further as their potential applications increase. Autonomous vehicles are currently being studied for use as reconnaissance/exploratory vehicles for planetary exploration, undersea, land and air environments, remote repair and maintenance, material handling systems for offices and factories, and even intelligent wheelchairs for the disabled. This reference is the first to deal directly with the unique and fundamental problems and recent progress associated with autonomous vehicles. The editors have assembled and combined significant material from a multitude of sources, and, in effect, now conviniently provide a coherent organization to a previously scattered and ill-defined field.
Path Planning for Vehicles Operating in Uncertain 2D Environments by Viacheslav Pshikhopov Pdf
Path Planning for Vehicles Operating in Uncertain 2D-environments presents a survey that includes several path planning methods developed using fuzzy logic, grapho-analytical search, neural networks, and neural-like structures, procedures of genetic search, and unstable motion modes. Presents a survey of accounting limitations imposed by vehicle dynamics Proposes modified and new original methods, including neural networking, grapho-analytical, and nature-inspired Gives tools for a novice researcher to select a method that would suit their needs or help to synthesize new hybrid methods
Trajectory Planning of an Autonomous Vehicle in Multi-Vehicle Traffic Scenarios by Mahdi Morsali Pdf
Tremendous industrial and academic progress and investments have been made in au-tonomous driving, but still many aspects are unknown and require further investigation,development and testing. A key part of an autonomous driving system is an efficient plan-ning algorithm with potential to reduce accidents, or even unpleasant and stressful drivingexperience. A higher degree of automated planning also makes it possible to have a betterenergy management strategy with improved performance through analysis of surroundingenvironment of autonomous vehicles and taking action in a timely manner. This thesis deals with planning of autonomous vehicles in different urban scenarios, road,and vehicle conditions. The main concerns in designing the planning algorithms, are realtime capability, safety and comfort. The planning algorithms developed in this thesis aretested in simulation traffic situations with multiple moving vehicles as obstacles. The re-search conducted in this thesis falls mainly into two parts, the first part investigates decou-pled trajectory planning algorithms with a focus on speed planning, and the second sectionexplores different coupled planning algorithms in spatiotemporal environments where pathand speed are calculated simultaneously. Additionally, a behavioral analysis is carried outto evaluate different tactical maneuvers the autonomous vehicle can have considering theinitial states of the ego and surrounding vehicles. Particularly relevant for heavy duty vehicles, the issues addressed in designing a safe speedplanner in the first part are road conditions such as banking, friction, road curvature andvehicle characteristics. The vehicle constraints on acceleration, jerk, steering, steer ratelimitations and other safety limitations such as rollover are further considerations in speedplanning algorithms. For real time purposes, a minimum working roll model is identified us-ing roll angle and lateral acceleration data collected in a heavy duty truck. In the decoupledplanners, collision avoiding is treated using a search and optimization based planner. In an autonomous vehicle, the structure of the road network is known to the vehicle throughmapping applications. Therefore, this key property can be used in planning algorithms toincrease efficiency. The second part of the thesis, is focused on handling moving obstaclesin a spatiotemporal environment and collision-free planning in complex urban structures.Spatiotemporal planning holds the benefits of exhaustive search and has advantages com-pared to decoupled planning, but the search space in spatiotemporal planning is complex.Support vector machine is used to simplify the search problem to make it more efficient.A SVM classifies the surrounding obstacles into two categories and efficiently calculate anobstacle free region for the ego vehicle. The formulation achieved by solving SVM, con-tains information about the initial point, destination, stationary and moving obstacles.These features, combined with smoothness property of the Gaussian kernel used in SVMformulation is proven to be able to solve complex planning missions in a safe way. Here, three algorithms are developed by taking advantages of SVM formulation, a greedysearch algorithm, an A* lattice based planner and a geometrical based planner. One general property used in all three algorithms is reduced search space through using SVM. In A*lattice based planner, significant improvement in calculation time, is achieved by using theinformation from SVM formulation to calculate a heuristic for planning. Using this heuristic,the planning algorithm treats a simple driving scenario and a complex urban structureequal, as the structure of the road network is included in SVM solution. Inspired byobserving significant improvements in calculation time using SVM heuristic and combiningthe collision information from SVM surfaces and smoothness property, a geometrical planneris proposed that leads to further improvements in calculation time. Realistic driving scenarios such as roundabouts, intersections and takeover maneuvers areused, to test the performance of the proposed algorithms in simulation. Different roadconditions with large banking, low friction and high curvature, and vehicles prone to safetyissues, specially rollover, are evaluated to calculate the speed profile limits. The trajectoriesachieved by the proposed algorithms are compared to profiles calculated by optimal controlsolutions.
Frontiers in Guided Wave Optics and Optoelectronics by Bishnu Pal Pdf
As the editor, I feel extremely happy to present to the readers such a rich collection of chapters authored/co-authored by a large number of experts from around the world covering the broad field of guided wave optics and optoelectronics. Most of the chapters are state-of-the-art on respective topics or areas that are emerging. Several authors narrated technological challenges in a lucid manner, which was possible because of individual expertise of the authors in their own subject specialties. I have no doubt that this book will be useful to graduate students, teachers, researchers, and practicing engineers and technologists and that they would love to have it on their book shelves for ready reference at any time.
Sensing and Control for Autonomous Vehicles by Thor I. Fossen,Kristin Y. Pettersen,Henk Nijmeijer Pdf
This edited volume includes thoroughly collected on sensing and control for autonomous vehicles. Guidance, navigation and motion control systems for autonomous vehicles are increasingly important in land-based, marine and aerial operations. Autonomous underwater vehicles may be used for pipeline inspection, light intervention work, underwater survey and collection of oceanographic/biological data. Autonomous unmanned aerial systems can be used in a large number of applications such as inspection, monitoring, data collection, surveillance, etc. At present, vehicles operate with limited autonomy and a minimum of intelligence. There is a growing interest for cooperative and coordinated multi-vehicle systems, real-time re-planning, robust autonomous navigation systems and robust autonomous control of vehicles. Unmanned vehicles with high levels of autonomy may be used for safe and efficient collection of environmental data, for assimilation of climate and environmental models and to complement global satellite systems. The target audience primarily comprises research experts in the field of control theory, but the book may also be beneficial for graduate students.
Motion Planning for Autonomous Vehicles in Partially Observable Environments by Taş, Ömer Şahin Pdf
This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling.
Autonomy and Unmanned Vehicles by Somaiyeh MahmoudZadeh,David M.W. Powers,Reza Bairam Zadeh Pdf
This book addresses higher–lower level decision autonomy for autonomous vehicles, and discusses the addition of a novel architecture to cover both levels. The proposed framework’s performance and stability are subsequently investigated by employing different meta-heuristic algorithms. The performance of the proposed architecture is shown to be largely independent of the algorithms employed; the use of diverse algorithms (subjected to the real-time performance of the algorithm) does not negatively affect the system’s real-time performance. By analyzing the simulation results, the book demonstrates that the proposed model provides perfect mission timing and task management, while also guaranteeing secure deployment. Although mainly intended as a research work, the book’s review chapters and the new approaches developed here are also suitable for use in courses for advanced undergraduate or graduate students.
