Download or read book Vision Based Control of a Full Size Car by Lane Detection written by N. Chase Kunz and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous driving is an area of increasing investment for researchers and auto manufacturers. Integration has already begun for self-driving cars in urban environments. An essential aspect of navigation in these areas is the ability to sense and follow lane markers. This thesis focuses on the development of a vision-based control platform using lane detection to control a full-sized electric vehicle with only a monocular camera. An open-source, integrated solution is presented for automation of a stock vehicle. Aspects of reverse engineering, system identification, and low-level control of the vehicle are discussed. This work also details methods for lane detection and the design of a non-linear vision-based control strategy.

Download or read book Vision based Vehicle Guidance written by Ichiro Masaki and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 355 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 Vision Based Lane Detection for Intelligent Vehicles written by Umar Ozgunalp and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Vision based Road Lane Detection for Autonomous Vehicles written by AbdulHakam Am Assidiq and published by . This book was released on 2008 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development of a Vision based Lane Detection System Considering Configuration Aspects written by Kansuh Huh and published by . This book was released on 2005 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vision-based lane-sensing systems require accurate and robust sensing performance in lane detection. Besides, there exists trade-off between the computational burden and processor cost, which should be considered for implementing the systems in passenger cars. In this paper, a stereo vision-based lane detection system considering sensor configuration aspects such as field of view (FOV), span pixels, resolution, etc is developed. An inverse perspective mapping method is formulated based on the relative correspondence between the left and right cameras so that the 3D road geometry can be reconstructed in a robust manner. The selection rule of the sensor configuration and specifications is investigated for a standard highway. Based on the selected sensor configurations, it is shown that sensing region range on the camera image coordinate can be determined for the best lane-sensing performance. The proposed system is implemented on a passenger car and its real-time sensing performance is verified experimentally.

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 Advanced Motion Control and Sensing for Intelligent Vehicles written by Li Li and published by Springer Science & Business Media. This book was released on 2007-11-24 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the latest information in intelligent vehicle control and intelligent transportation. Detailed discussions of vehicle dynamics and ground-vehicle interactions are provided for the modeling, simulation and control of vehicles. It includes an extensive review of past and current research achievements in the intelligent vehicle motion control and sensory field, and the book provides a careful assessment of future developments.

Download or read book Vision Based Tactical Driving written by Todd Jochem and published by . This book was released on 1996 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Much progress has been made toward solving the autonomous lane keeping problem using vision based methods. Systems have been demonstrated which can drive robot vehicles at high speeds for long distances. The current challenge for vision based on-road navigation researchers is to create systems that maintain the performance of the existing lane keeping systems, while adding the ability to execute tactical level driving tasks like lane transition and intersection detection and navigation. There are many ways to add tactical functionality to a driving system. Solutions range from developing task specific software modules to grafting additional functionality onto a basic lane keeping system. Solutions like these are problematic because they either make reuse of acquired knowledge difficult or impossible, or preclude the use of alternative lane keeping systems. A more desirable solution is to develop a robust, lane keeper independent control scheme that provides the functionality to execute tactical actions. Based on this hypothesis, techniques that are used to execute tactical level driving tasks should: be based on a single framework that is applicable to a variety of tactical level actions, be extensible to other vision based lane keeping systems, and require little or no modification of the lane keeping system with which it is being used. This thesis examines a framework, called Virtual Active Vision, which provides this functionality through intelligent control of the visual information presented to the lane keeping system. Novel solutions based on this framework for two classes of tactical driving tasks, lane transition and intersection detection and transversal, are presented in detail. Specifically, algorithms which allow the ALVINN lane keeping system to robustly execute lane transition maneuvers like lane changing, entrance and exit ramp detection and transversal, and obstacle avoidance are presented. Additionally, with the aid of active camera control, the ALVINN system enhanced with Virtual Active Vision tools can successfully detect and navigate basic road intersections."

Download or read book Vision based Control and Coordination of Unmanned Vehicles written by Omid Shakernia and published by . This book was released on 2003 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Novel Vision based Lane Detection and Tracking Algorithm Using B snake written by Yue Wang and published by . This book was released on 1999 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Information Technology and Intelligent Transportation Systems written by Valentina Emilia Balas and published by Springer. This book was released on 2016-11-08 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume includes the proceedings of the 2015 International Conference on Information Technology and Intelligent Transportation Systems (ITITS 2015) which was held in Xi’an on December 12-13, 2015. The conference provided a platform for all professionals and researchers from industry and academia to present and discuss recent advances in the field of Information Technology and Intelligent Transportation Systems. The presented information technologies are connected to intelligent transportation systems including wireless communication, computational technologies, floating car data/floating cellular data, sensing technologies, and video vehicle detection. The articles focusing on intelligent transport systems vary in the technologies applied, from basic management systems to more application systems including topics such as emergency vehicle notification systems, automatic road enforcement, collision avoidance systems and some cooperative systems. The conference hosted 12 invited speakers and over 200 participants. Each paper was under double peer reviewed by at least 3 reviewers. This proceedings are sponsored by Shaanxi Computer Society and co-sponsored by Chang’an University, Xi’an University of Technology, Northwestern Poly-technical University, CAS, Shaanxi Sirui Industries Co., LTD.

Download or read book Hands On Vision and Behavior for Self Driving Cars written by Luca Venturi and published by Packt Publishing Ltd. This book was released on 2020-10-23 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to learning visual perception for self-driving cars for computer vision and autonomous system engineers Key FeaturesExplore the building blocks of the visual perception system in self-driving carsIdentify objects and lanes to define the boundary of driving surfaces using open-source tools like OpenCV and PythonImprove the object detection and classification capabilities of systems with the help of neural networksBook Description The visual perception capabilities of a self-driving car are powered by computer vision. The work relating to self-driving cars can be broadly classified into three components - robotics, computer vision, and machine learning. This book provides existing computer vision engineers and developers with the unique opportunity to be associated with this booming field. You will learn about computer vision, deep learning, and depth perception applied to driverless cars. The book provides a structured and thorough introduction, as making a real self-driving car is a huge cross-functional effort. As you progress, you will cover relevant cases with working code, before going on to understand how to use OpenCV, TensorFlow and Keras to analyze video streaming from car cameras. Later, you will learn how to interpret and make the most of lidars (light detection and ranging) to identify obstacles and localize your position. You’ll even be able to tackle core challenges in self-driving cars such as finding lanes, detecting pedestrian and crossing lights, performing semantic segmentation, and writing a PID controller. By the end of this book, you’ll be equipped with the skills you need to write code for a self-driving car running in a driverless car simulator, and be able to tackle various challenges faced by autonomous car engineers. What you will learnUnderstand how to perform camera calibrationBecome well-versed with how lane detection works in self-driving cars using OpenCVExplore behavioral cloning by self-driving in a video-game simulatorGet to grips with using lidarsDiscover how to configure the controls for autonomous vehiclesUse object detection and semantic segmentation to locate lanes, cars, and pedestriansWrite a PID controller to control a self-driving car running in a simulatorWho this book is for This book is for software engineers who are interested in learning about technologies that drive the autonomous car revolution. Although basic knowledge of computer vision and Python programming is required, prior knowledge of advanced deep learning and how to use sensors (lidar) is not needed.

Download or read book Handbook of Intelligent Vehicles written by Azim Eskandarian and published by Springer. This book was released on 2012-02-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Intelligent Vehicles provides a complete coverage of the fundamentals, new technologies, and sub-areas essential to the development of intelligent vehicles; it also includes advances made to date, challenges, and future trends. Significant strides in the field have been made to date; however, so far there has been no single book or volume which captures these advances in a comprehensive format, addressing all essential components and subspecialties of intelligent vehicles, as this book does. Since the intended users are engineering practitioners, as well as researchers and graduate students, the book chapters do not only cover fundamentals, methods, and algorithms but also include how software/hardware are implemented, and demonstrate the advances along with their present challenges. Research at both component and systems levels are required to advance the functionality of intelligent vehicles. This volume covers both of these aspects in addition to the fundamentals listed above.

Download or read book Intelligent Vehicle Technologies written by Ljubo Vlacic and published by Butterworth-Heinemann. This book was released on 2001 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: An exploration of the growing field of intelligent technologies, from intelligent control systems to intelligent sensors. Systems such as in-car navigation devices and cruise control are already being introduced into modern vehicles, but manufacturers are now racing to develop systems such as smart cruise control, on-vehicle driver information systems, collision avoidance systems, vision enhancement and roadworthiness diagnostics systems. There are practical examples and illustrations throughout the book.

Download or read book Automated Car Driver Assisted written by Nor Sakinah Abdul Shukor and published by . This book was released on 2012 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Improved Vision based Lane Line Detection in Adverse Weather Conditions Utilizing Vehicle to infrastructure V2I Communication written by and published by . This book was released on 2019 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lane line detection is a very critical element for both Advanced Driver Assistance Systems (ADAS) and Autonomous Driving features. Although, there has been significant amount of research dedicated to the detecton and localization of lane lines in the past decade, there is still a gap in the robustness of the implemented systems. A major challenge to the existing lane line detection algorithms stems from coping with bad weather conditions (e.g. rain, snow, fog, haze, etc.). Snow offers an especially challenging environment, where lane marks and road boundaries are completely covered by snow. In these scenarios, on-board sensors such as cameras, LiDAR, and radars are of very limited benefit. In this research, the focus is on solving the problem of improving robustness of lane line detection in adverse weather conditions, especially snow. A framework is proposed that relies on utilizing Vehicle-to-Infrastructure (V2I) communication to access reference images stored in the cloud. These reference images were captured at approximately the same geographical location when visibility was clear and weather conditions were good. The reference images are used to detect and localize lane lines. The proposed framework then uses image registration techniques to align both the sensed image (adverse weather) and the reference image. Once the two images are aligned, the lane line information from the reference image is then superimposed on the local map built by the ADAS or Autonomous driving system. A real-world experiment is designed to evaluate the error in localizing the lane lines using the proposed framework in comparison to ground truth data. The measurements and evaluations are based on data gathered from a test vehicle. The vehicle is equipped with a monocular camera, forward looking radar, LiDAR, and GPS/IMU. The initial results show good potential for improving upon current state-of-the are approaches used in today's automotive industry. The novelty of this work is a result of proposing a vision-based ADAS method that uses prior knowledge about the environment instead of being solely reactive to vehicle sensor inputs.

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.