Download or read book Autonomous Road Vehicles Localization Using Satellites Lane Markings and Vision written by Zui Tao and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimating the pose (position and attitude) in real-time is a key function for road autonomous vehicles. This thesis aims at studying vehicle localization performance using low cost automotive sensors. Three kinds of sensors are considered : dead reckoning (DR) sensors that already exist in modern vehicles, mono-frequency GNSS (Global navigation satellite system) receivers with patch antennas and a frontlooking lane detection camera. Highly accurate maps enhanced with road features are also key components for autonomous vehicle navigation. In this work, a lane marking map with decimeter-level accuracy is considered. The localization problem is studied in a local East-North-Up (ENU) working frame. Indeed, the localization outputs are used in real-time as inputs to a path planner and a motion generator to make a valet vehicle able to drive autonomously at low speed with nobody on-board the car. The use of a lane detection camera makes possible to exploit lane marking information stored in the georeferenced map. A lane marking detection module detects the vehicle's host lane and provides the lateral distance between the detected lane marking and the vehicle. The camera is also able to identify the type of the detected lane markings (e.g., solid or dashed). Since the camera gives relative measurements, the important step is to link the measures with the vehicle's state. A refined camera observation model is proposed. It expresses the camera metric measurements as a function of the vehicle's state vector and the parameters of the detected lane markings. However, the use of a camera alone has some limitations. For example, lane markings can be missing in some parts of the navigation area and the camera sometimes fails to detect the lane markings in particular at cross-roads. GNSS, which is mandatory for cold start initialization, can be used also continuously in the multi-sensor localization system as done often when GNSS compensates for the DR drift. GNSS positioning errors can't be modeled as white noises in particular with low cost mono-frequency receivers working in a standalone way, due to the unknown delays when the satellites signals cross the atmosphere and real-time satellites orbits errors. GNSS can also be affected by strong biases which are mainly due to multipath effect. This thesis studies GNSS biases shaping models that are used in the localization solver by augmenting the state vector. An abrupt bias due to multipath is seen as an outlier that has to be rejected by the filter. Depending on the information flows between the GNSS receiver and the other components of the localization system, data-fusion architectures are commonly referred to as loosely coupled (GNSS fixes and velocities) and tightly coupled (raw pseudoranges and Dopplers for the satellites in view). This thesis investigates both approaches. In particular, a road-invariant approach is proposed to handle a refined modeling of the GNSS error in the loosely coupled approach since the camera can only improve the localization performance in the lateral direction of the road. Finally, this research discusses some map-matching issues for instance when the uncertainty domain of the vehicle state becomes large if the camera is blind. It is challenging in this case to distinguish between different lanes when the camera retrieves lane marking measurements.As many outdoor experiments have been carried out with equipped vehicles, every problem addressed in this thesis is evaluated with real data. The different studied approaches that perform the data fusion of DR, GNSS, camera and lane marking map are compared and several conclusions are drawn on the fusion architecture choice.

Download or read book Automatic Laser Calibration Mapping and Localization for Autonomous Vehicles written by Jesse Sol Levinson and published by Stanford University. This book was released on 2011 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation presents several related algorithms that enable important capabilities for self-driving vehicles. Using a rotating multi-beam laser rangefinder to sense the world, our vehicle scans millions of 3D points every second. Calibrating these sensors plays a crucial role in accurate perception, but manual calibration is unreasonably tedious, and generally inaccurate. As an alternative, we present an unsupervised algorithm for automatically calibrating both the intrinsics and extrinsics of the laser unit from only seconds of driving in an arbitrary and unknown environment. We show that the results are not only vastly easier to obtain than traditional calibration techniques, they are also more accurate. A second key challenge in autonomous navigation is reliable localization in the face of uncertainty. Using our calibrated sensors, we obtain high resolution infrared reflectivity readings of the world. From these, we build large-scale self-consistent probabilistic laser maps of urban scenes, and show that we can reliably localize a vehicle against these maps to within centimeters, even in dynamic environments, by fusing noisy GPS and IMU readings with the laser in realtime. We also present a localization algorithm that was used in the DARPA Urban Challenge, which operated without a prerecorded laser map, and allowed our vehicle to complete the entire six-hour course without a single localization failure. Finally, we present a collection of algorithms for the mapping and detection of traffic lights in realtime. These methods use a combination of computer-vision techniques and probabilistic approaches to incorporating uncertainty in order to allow our vehicle to reliably ascertain the state of traffic-light-controlled intersections.

Download or read book Contributions to Lane Marking Based Localization for Intelligent Vehicles written by Wenjie Lu and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous Vehicles (AV) applications and Advanced Driving Assistance Systems (ADAS) relay in scene understanding processes allowing high level systems to carry out decision marking. For such systems, the localization of a vehicle evolving in a structured dynamic environment constitutes a complex problem of crucial importance. Our research addresses scene structure detection, localization and error modeling. Taking into account the large functional spectrum of vision systems, the accessibility of Open Geographical Information Systems (GIS) and the widely presence of Global Positioning Systems (GPS) onboard vehicles, we study the performance and the reliability of a vehicle localization method combining such information sources. Monocular vision-based lane marking detection provides key information about the scene structure. Using an enhanced multi-kernel framework with hierarchical weights, the proposed parametric method performs, in real time, the detection and tracking of the ego-lane marking. A self-assessment indicator quantifies the confidence of this information source. We conduct our investigations in a localization system which tightly couples GPS, GIS and lane makings in the probabilistic framework of Particle Filter (PF). To this end, it is proposed the use of lane markings not only during the map-matching process but also to model the expected ego-vehicle motion. The reliability of the localization system, in presence of unusual errors from the different information sources, is enhanced by taking into account different confidence indicators. Such a mechanism is later employed to identify error sources. This research concludes with an experimental validation in real driving situations of the proposed methods. They were tested and its performance was quantified using an experimental vehicle and publicly available datasets.

Download or read book China Satellite Navigation Conference CSNC 2020 Proceedings Volume III written by Jiadong Sun and published by Springer Nature. This book was released on 2020-06-06 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt: China Satellite Navigation Conference (CSNC 2020) Proceedings presents selected research papers from CSNC 2020 held during 22nd-25th November in Chengdu, China. These papers discuss the technologies and applications of the Global Navigation Satellite System (GNSS), and the latest progress made in the China BeiDou System (BDS) especially. They are divided into 13 topics to match the corresponding sessions in CSNC2020, which broadly covered key topics in GNSS. Readers can learn about the BDS and keep abreast of the latest advances in GNSS techniques and applications.

Download or read book Autonomous Vehicle Localization Using Sensor Fusion with Lane Marking Detection and High Definition Map written by 賴柏翔 and published by . This book was released on 2020 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Creating Autonomous Vehicle Systems written by Shaoshan Liu and published by Morgan & Claypool Publishers. This book was released on 2017-10-25 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Advances in Dynamics of Vehicles on Roads and Tracks III written by Wei Huang and published by Springer Nature. This book was released on with total page 997 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Autonomous driving algorithms and Its IC Design written by Jianfeng Ren and published by Springer Nature. This book was released on 2023-08-09 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid development of artificial intelligence and the emergence of various new sensors, autonomous driving has grown in popularity in recent years. The implementation of autonomous driving requires new sources of sensory data, such as cameras, radars, and lidars, and the algorithm processing requires a high degree of parallel computing. In this regard, traditional CPUs have insufficient computing power, while DSPs are good at image processing but lack sufficient performance for deep learning. Although GPUs are good at training, they are too “power-hungry,” which can affect vehicle performance. Therefore, this book looks to the future, arguing that custom ASICs are bound to become mainstream. With the goal of ICs design for autonomous driving, this book discusses the theory and engineering practice of designing future-oriented autonomous driving SoC chips. The content is divided into thirteen chapters, the first chapter mainly introduces readers to the current challenges and research directions in autonomous driving. Chapters 2–6 focus on algorithm design for perception and planning control. Chapters 7–10 address the optimization of deep learning models and the design of deep learning chips, while Chapters 11-12 cover automatic driving software architecture design. Chapter 13 discusses the 5G application on autonomous drving. This book is suitable for all undergraduates, graduate students, and engineering technicians who are interested in autonomous driving.

Download or read book Augmenting Vehicle Localization with Visual Context written by Robert Andrew Rae and published by . This book was released on 2009 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vehicle self-localization, the ability of a vehicle to determine its own location, is vital for many aspects of Intelligent Transportation Systems (ITS) and telematics where it is often a building block in a more complex system. Navigation systems are perhaps the most obvious example, requiring knowledge of the vehicle's location on a map to calculate a route to a desired destination. Other pervasive examples are the monitoring of vehicle fleets for tracking shipments or dispatching emergency vehicles, and in public transit systems to inform riders of time-of-arrival thereby assisting trip planning. These system often depend on Global Positioning System (GPS) technology to provide vehicle localization information; however, GPS is challenged in urban environments where satellite visibility and multipath conditions are common. Vehicle localization is made more robust to these issues through augmentation of GPS-based localization with complementary sensors, thereby improving the performance and reliability of systems that depend on localization information. This thesis investigates the augmentation of vehicle localization systems with visual context. Positioning the vehicle with respect to objects in its surrounding environment in addition to using GPS constraints the possible vehicle locations, to provide improved localization accuracy compared to a system relying solely on GPS. A modular system architecture based on Bayesian filtering is proposed in this thesis that enables existing localization systems to be augmented by visual context while maintaining their existing capabilities.

Download or read book Handbook of Position Location written by Reza Zekavat and published by John Wiley & Sons. This book was released on 2019-01-28 with total page 1521 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review of position location technology — from fundamental theory to advanced practical applications Positioning systems and location technologies have become significant components of modern life, used in a multitude of areas such as law enforcement and security, road safety and navigation, personnel and object tracking, and many more. Position location systems have greatly reduced societal vulnerabilities and enhanced the quality of life for billions of people around the globe — yet limited resources are available to researchers and students in this important field. The Handbook of Position Location: Theory, Practice, and Advances fills this gap, providing a comprehensive overview of both fundamental and cutting-edge techniques and introducing practical methods of advanced localization and positioning. Now in its second edition, this handbook offers broad and in-depth coverage of essential topics including Time of Arrival (TOA) and Direction of Arrival (DOA) based positioning, Received Signal Strength (RSS) based positioning, network localization, and others. Topics such as GPS, autonomous vehicle applications, and visible light localization are examined, while major revisions to chapters such as body area network positioning and digital signal processing for GNSS receivers reflect current and emerging advances in the field. This new edition: Presents new and revised chapters on topics including localization error evaluation, Kalman filtering, positioning in inhomogeneous media, and Global Positioning (GPS) in harsh environments Offers MATLAB examples to demonstrate fundamental algorithms for positioning and provides online access to all MATLAB code Allows practicing engineers and graduate students to keep pace with contemporary research and new technologies Contains numerous application-based examples including the application of localization to drone navigation, capsule endoscopy localization, and satellite navigation and localization Reviews unique applications of position location systems, including GNSS and RFID-based localization systems The Handbook of Position Location: Theory, Practice, and Advances is valuable resource for practicing engineers and researchers seeking to keep pace with current developments in the field, graduate students in need of clear and accurate course material, and university instructors teaching the fundamentals of wireless localization.

Download or read book Autonomous Vehicle Technology written by James M. Anderson and published by Rand Corporation. This book was released on 2014-01-10 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.

Download or read book Advanced Driver Intention Inference written by Yang Xing and published by Elsevier. This book was released on 2020-03-15 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Driver Intention Inference: Theory and Design describes one of the most important function for future ADAS, namely, the driver intention inference. The book contains the state-of-art knowledge on the construction of driver intention inference system, providing a better understanding on how the human driver intention mechanism will contribute to a more naturalistic on-board decision system for automated vehicles. Features examples of using machine learning/deep learning to build industry products Depicts future trends for driver behavior detection and driver intention inference Discuss traffic context perception techniques that predict driver intentions such as Lidar and GPS

Download or read book Integrated Vehicle Localization System Using Vision based Lane Detection and Road Marker Recognition written by 林景昱 and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Global Positioning Systems Inertial Navigation and Integration written by Mohinder S. Grewal and published by John Wiley & Sons. This book was released on 2007-03-05 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: An updated guide to GNSS and INS, and solutions to real-world GPS/INS problems with Kalman filtering Written by recognized authorities in the field, this second edition of a landmark work provides engineers, computer scientists, and others with a working familiarity with the theory and contemporary applications of Global Navigation Satellite Systems (GNSS), Inertial Navigational Systems (INS), and Kalman filters. Throughout, the focus is on solving real-world problems, with an emphasis on the effective use of state-of-the-art integration techniques for those systems, especially the application of Kalman filtering. To that end, the authors explore the various subtleties, common failures, and inherent limitations of the theory as it applies to real-world situations, and provide numerous detailed application examples and practice problems, including GNSS-aided INS, modeling of gyros and accelerometers, and SBAS and GBAS. Drawing upon their many years of experience with GNSS, INS, and the Kalman filter, the authors present numerous design and implementation techniques not found in other professional references. This Second Edition has been updated to include: GNSS signal integrity with SBAS Mitigation of multipath, including results Ionospheric delay estimation with Kalman filters New MATLAB programs for satellite position determination using almanac and ephemeris data and ionospheric delay calculations from single and dual frequency data New algorithms for GEO with L1 /L5 frequencies and clock steering Implementation of mechanization equations in numerically stable algorithms To enhance comprehension of the subjects covered, the authors have included software in MATLAB, demonstrating the working of the GNSS, INS, and filter algorithms. In addition to showing the Kalman filter in action, the software also demonstrates various practical aspects of finite word length arithmetic and the need for alternative algorithms to preserve result accuracy.

Download or read book Vision based Vehicle Guidance written by Ichiro Masaki and published by Springer. This book was released on 1992-03-25 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a growing social interest in developing vision-based vehicle guidance systems for improving traffic safety and efficiency and the environment. Ex amples of vision-based vehicle guidance systems include collision warning systems, steering control systems for tracking painted lane marks, and speed control systems for preventing rear-end collisions. Like other guidance systems for aircraft and trains, these systems are ex pected to increase traffic safety significantly. For example, safety improve ments of aircraft landing processes after the introduction of automatic guidance systems have been reported to be 100 times better than prior to installment. Although the safety of human lives is beyond price, the cost for automatic guidance could be compensated by decreased insurance costs. It is becoming more important to increase traffic safety by decreasing the human driver's load in our society, especially with an increasing population of senior people who continue to drive. The second potential social benefit is the improvement of traffic efficiency by decreasing the spacing between vehicles without sacrificing safety. It is reported, for example, that four times the efficiency is expected if the spacing between cars is controlled automatically at 90 cm with a speed of 100 kmjh compared to today's typical manual driving. Although there are a lot of tech nical, psychological, and social issues to be solved before realizing the high density jhigh-speed traffic systems described here, highly efficient highways are becoming more important because of increasing traffic congestion.

Download or read book Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition SoCPaR 2021 written by Ajith Abraham and published by Springer Nature. This book was released on 2022-02-21 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the recent research on soft computing, pattern recognition, nature-inspired computing and their various practical applications. It presents 53 selected papers from the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021) and 11 papers from the 13th World Congress on Nature and Biologically Inspired Computing (NaBIC 2021), which was held online, from December 15 to 17, 2021. A premier conference in the field of soft computing, artificial intelligence and machine learning applications, SoCPaR-NaBIC 2021 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from over 20 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of computer science and engineering.

Download or read book Robots Drones UAVs and UGVs for Operation and Maintenance written by Diego Galar and published by CRC Press. This book was released on 2020-05-07 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial assets (such as railway lines, roads, pipelines) are usually huge, span long distances, and can be divided into clusters or segments that provide different levels of functionality subject to different loads, degradations and environmental conditions, and their efficient management is necessary. The aim of the book is to give comprehensive understanding about the use of autonomous vehicles (context of robotics) for the utilization of inspection and maintenance activities in industrial asset management in different accessibility and hazard levels. The usability of deploying inspection vehicles in an autonomous manner is explained with the emphasis on integrating the total process. Key Features Aims for solutions for maintenance and inspection problems provided by robotics, drones, unmanned air vehicles and unmanned ground vehicles Discusses integration of autonomous vehicles for inspection and maintenance of industrial assets Covers the industrial approach to inspection needs and presents what is needed from the infrastructure end Presents the requirements for robot designers to design an autonomous inspection and maintenance system Includes practical case studies from industries