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 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 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 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 An Integrated Solution Based Irregular Driving Detection written by Rui Sun and published by Springer. This book was released on 2016-09-07 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis introduces a new integrated algorithm for the detection of lane-level irregular driving. To date, there has been very little improvement in the ability to detect lane level irregular driving styles, mainly due to a lack of high performance positioning techniques and suitable driving pattern recognition algorithms. The algorithm combines data from the Global Positioning System (GPS), Inertial Measurement Unit (IMU) and lane information using advanced filtering methods. The vehicle state within a lane is estimated using a Particle Filter (PF) and an Extended Kalman Filter (EKF). The state information is then used within a novel Fuzzy Inference System (FIS) based algorithm to detect different types of irregular driving. Simulation and field trial results are used to demonstrate the accuracy and reliability of the proposed irregular driving detection method.

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 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 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

Download or read book Vehicle Positioning System Using Vision based Road Marker Matching on Structured Roads written by 曹皓鈞 and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computer Vision and Recognition Systems written by Chiranji Lal Chowdhary and published by CRC Press. This book was released on 2022-03-10 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This cutting-edge volume focuses on how artificial intelligence can be used to give computers the ability to imitate human sight. With contributions from researchers in diverse countries, including Thailand, Spain, Japan, Turkey, Australia, and India, the book explains the essential modules that are necessary for comprehending artificial intelligence experiences to provide machines with the power of vision. The volume also presents innovative research developments, applications, and current trends in the field. The chapters cover such topics as visual quality improvement, Parkinson’s disease diagnosis, hypertensive retinopathy detection through retinal fundus, big image data processing, N-grams for image classification, medical brain images, chatbot applications, credit score improvisation, vision-based vehicle lane detection, damaged vehicle parts recognition, partial image encryption of medical images, and image synthesis. The chapter authors show different approaches to computer vision, image processing, and frameworks for machine learning to build automated and stable applications. Deep learning is included for making immersive application-based systems, pattern recognition, and biometric systems. The book also considers efficiency and comparison at various levels of using algorithms for real-time applications, processes, and analysis.

Download or read book GPS and Lane Detection for Accurate Trajectories in Vision based Driver Assistance System written by Di Terry Sun and published by . This book was released on 2011 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis discusses the Global Positioning System (GPS), the digital maps and map matching algorithms, the image based lane detection algorithm and the ways of integrating these three techniques together to solve the lane detection problem. GPS has been developed and utilized for more than thirty years. Several industries have been established based on the GPS, and it also helps existing industries to upgrade their services towards more cost effective, fast, and reliable solutions. Digital maps are built to translate the GPS raw data to a human readable format. They contain both the location information and its reference to the earth. The basic digital maps that are used for car navigation contain the road names and their reference to the earth. Since the GPS raw data contains errors, some of the GPS raw locations fall out of the road on digital maps. The map matching algorithms are used to help map the GPS raw data to the occupied road. By correctly locating the occupied route, the device could also provide drivers with some useful information, such as the road geometry in front of the vehicle, reaching traffic lights, etc. Driver assistance systems (DAS) are a new research area considered to be the next revolution of the industry. The lane detection application is a kind of advanced DAS to solve the lane keeping problem. The image based lane detection application use the camera as the sole information source. Several algorithms have been developed to help understand the local environment. Since large volumes of calculations are involved in these algorithms, other information sources can be imported to reduce the computation expense. This thesis presents a solution to utilize and combine the information that comes from two sensors - the GPS and the camera, to provide a light weight solution for the lane detection applications. This thesis introduces some background knowledge of the GPS together with the digital maps and the map matching algorithm. The image based pattern detection techniques are also discussed. The detailed approaches and experiments will be presented at the end.

Download or read book Image Analysis and Recognition written by Mohamed Kamel and published by Springer. This book was released on 2015-07-03 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 12th International Conference on Image Analysis and Recognition, ICIAR 2015, held in Niagara Falls, ON, Canada, in July 2015. The 55 revised full papers and 5 short papers presented were carefully reviewed and selected from 80 submissions. The papers are organized in the following topical sections: image quality assessment; image enhancement; image segmentation, registration and analysis; image coding, compression and encryption; dimensionality reduction and classification; biometrics; face description, detection and recognition; human activity recognition; robotics and 3D vision; medical image analysis; and applications.

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 International Conference on Advanced Intelligent Systems for Sustainable Development AI2SD 2023 written by Mostafa Ezziyyani and published by Springer Nature. This book was released on with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: Zusammenfassung: This book is a comprehensive compilation of groundbreaking insights stemming from the esteemed International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD'2023), hosted at Cadi Ayyad University Morocco. Focused on the crucial themes of energy, environment, agriculture, and industry, this book captures the essence of transformative discussions and cutting-edge research that unfolded during the conference. Within these pages, readers are invited to explore the intricate world of intelligent systems, where innovation converges to tackle the key challenges of sustainability. The book immerses its audience in a wealth of knowledge that deeply represents the latest advancements shaping the future landscape. Diverse topics are intricately woven into the fabric of this discourse, covering AI-driven solutions designed for energy optimization, environmental sustainability, precision agriculture, and intelligent industry applications. Each contribution serves as a testament to the collaborative efforts of researchers, practitioners, and experts who gathered to drive innovation at the intersection of intelligent systems and sustainable development. Crafted as an invaluable resource, 'Advancements in Intelligent Systems: AI2SD'2023 Proceedings' caters to a diverse readership eager to delve into the forefront of trends and developments emerging from the crossroads of advanced intelligent systems in energy, environment, agriculture, and industry. Whether you're a researcher, practitioner, or enthusiast, unlock the transformative potential inherent in these innovative domains

Download or read book Computer Vision ECCV 2018 Workshops written by Laura Leal-Taixé and published by Springer. This book was released on 2019-01-22 with total page 777 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set comprising the LNCS volumes 11129-11134 constitutes the refereed proceedings of the workshops that took place in conjunction with the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.43 workshops from 74 workshops proposals were selected for inclusion in the proceedings. The workshop topics present a good orchestration of new trends and traditional issues, built bridges into neighboring fields, and discuss fundamental technologies and novel applications.

Download or read book Pattern Recognition and Computer Vision written by Zhouchen Lin and published by Springer Nature. This book was released on 2019-10-31 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 11857, 11858, and 11859 constitutes the refereed proceedings of the Second Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019, held in Xi’an, China, in November 2019. The 165 revised full papers presented were carefully reviewed and selected from 412 submissions. The papers have been organized in the following topical sections: Part I: Object Detection, Tracking and Recognition, Part II: Image/Video Processing and Analysis, Part III: Data Analysis and Optimization.

Download or read book A Lane Detection Tracking and Recognition System for Smart Vehicles written by Guangqian Lu and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As important components of intelligent transportation system, lane detection and tracking (LDT) and lane departure warning (LDW) systems have attracted great interest from the computer vision community over the past few years. Conversely, lane markings recognition (LMR) systems received surprisingly little attention. This thesis proposed a real-time lane assisting framework for intelligent vehicles, which consists of a comprehensive module and simplified module. To the best of our knowledge, this is the first parallel architecture that considers not only lane detection and tracking, but also lane marking recognition and departure warning. A lightweight version of the Hough transform, PPHT is used for both modules to detect lines. After detection stage, for the comprehensive module, a novel refinement scheme consisting of angle threshold and segment linking (ATSL) and trapezoidal refinement method (TRM) takes shape and texture information into account, which significantly improves the LDT performance. Also based on TRM, colour and edge informations are used to recognize lane marking colors (white and yellow) and shapes (solid and dashed). In the simplified module, refined MSER blobs dramatically simplifies the preprocessing and refinement stage, and enables the simplified module performs well on lane detection and tracking. Several experiments are conducted in highway and urban roads in Ottawa. The detection rate of the LDT system in comprehensive module average 95.9% and exceed 89.3% in poor conditions, while the recognition rate depends on the quality of lane paint and achieves an average accuracy of 93.1%. The simplified module has an average detection rate of 92.7% and exceeds 84.9% in poor conditions. Except the conventional experimental methods, a novel point cluster evaluation and pdf analysis method have been proposed to evaluate the performance of LDT systems, in terms of the stability, accuracy and similarity to Gaussian distribution.