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 Study of Vehicle Localization Optimization with Visual Odometry Trajectory Tracking written by Dayang Nur Salmi Dharmiza Awang Salleh and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the growing research on Advanced Driver Assistance Systems (ADAS) for Intelligent Transport Systems (ITS), accurate vehicle localization plays an important role in intelligent vehicles. The Global Positioning System (GPS) has been widely used but its accuracy deteriorates and susceptible to positioning error due to factors such as the restricting environments that results in signal weakening. This problem can be addressed by integrating the GPS data with additional information from other sensors. Meanwhile, nowadays, we can find vehicles equipped with sensors for ADAS applications. In this research, fusion of GPS with visual odometry (VO) and digital map is proposed as a solution to localization improvement with low-cost data fusion. From the published works on VO, it is interesting to know how the generated trajectory can further improve vehicle localization. By integrating the VO output with GPS and OpenStreetMap (OSM) data, estimates of vehicle position on the map can be obtained. The lateral positioning error is reduced by utilizing lane distribution information provided by OSM while the longitudinal positioning is optimized with curve matching between VO trajectory trail and segmented roads. To observe the system robustness, the method was validated with KITTI datasets tested with different common GPS noise. Several published VO methods were also used to compare improvement level after data fusion. Validation results show that the positioning accuracy achieved significant improvement especially for the longitudinal error with curve matching technique. The localization performance is on par with Simultaneous Localization and Mapping (SLAM) SLAM techniques despite the drift in VO trajectory input. The research on employability of VO trajectory is extended for a deterministic task in lane-change detection. This is to assist the routing service for lane-level direction in navigation. The lane-change detection was conducted by CUSUM and curve fitting technique that resulted in 100% successful detection for stereo VO. Further study for the detection strategy is however required to obtain the current true lane of the vehicle for lane-level accurate localization. With the results obtained from the proposed low-cost data fusion for localization, we see a bright prospect of utilizing VO trajectory with information from OSM to improve the performance. In addition to obtain VO trajectory, the camera mounted on the vehicle can also be used for other image processing applications to complement the system. This research will continue to develop with future works concluded in the last chapter of this thesis.

Download or read book Proceedings of the Future Technologies Conference FTC 2021 Volume 1 written by Kohei Arai and published by Springer Nature. This book was released on 2021-10-23 with total page 1020 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a wide range of important topics including but not limited to Technology Trends, Computing, Artificial Intelligence, Machine Vision, Communication, Security, e-Learning, and Ambient Intelligence and their applications to the real world. The sixth Future Technologies Conference 2021 was organized virtually and received a total of 531 submissions from academic pioneering researchers, scientists, industrial engineers, and students from all over the world.. After a double-blind peer review process, 191 submissions have been selected to be included in these proceedings. One of the meaningful and valuable dimensions of this conference is the way it brings together a large group of technology geniuses in one venue to not only present breakthrough research in future technologies, but also to promote discussions and debate of relevant issues, challenges, opportunities and research findings. We hope that readers find the book interesting, exciting, and inspiring; it provides the state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research.

Download or read book A Novel Lightweight Lane Departure Warning System Based on Computer Vision for Improving Road Safety written by Yue Chen and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid improvement of the Advanced Driver Assistant System (ADAS), autonomous driving has become one of the most common hot topics in recent years. While driving, many technologies related to autonomous driving choose to use the sensors installed on the vehicle to collect the information of road status and the environment outside. This aims to warn the driver to perceive the potential danger in the fastest time, which has become the focus of autonomous driving in recent years. Although autonomous driving brings plenty of conveniences to people, the safety of it is still facing difficulties. During driving, even the experienced driver can not guarantee focus on the status of the road all the time. Thus, lane departure warning system (LDWS) becomes developed. The purpose of LDWS is to determine whether the vehicle is in the safe driving area. If the vehicle is out of this area, LDWS will detect it and alert the driver by the sensors, such as sound and vibration, in order to make the driver back to the safe driving area. This thesis proposes a novel lightweight LDWS model LEHA, which divides the entire LDWS into three stages: image preprocessing, lane detection, and lane departure recognition. Different from the deep learning methods of LDWS, our LDWS model LEHA can achieve high accuracy and efficiency by relying only on simple hardware. The image preprocessing stage aims to process the original road image to remove the noise which is irrelevant to the detection result. In this stage, we apply a novel algorithm of grayscale preprocessing to convert the road image to a grayscale image, which removes the color of it. Then, we design a binarization method to greatly extract the lane lines from the background. A newly-designed image smoothing is added to this stage to reduce most of the noise, which improves the accuracy of the following lane detection stage. After obtaining the processed image, the lane detection stage is applied to detect and mark the lane lines. We use region of interest (ROI) to remove the irrelevant parts of the road image to reduce the detection time. After that, we introduce the Canny edge detection method, which aims to extract the edges of the lane lines. The last step of LDWS in the lane detection stage is a novel Hough transform method, the purpose of it is to detect the position of the lane and mark it. Finally, the lane departure recognition stage is used to calculate the deviation distance between the vehicle and the centerline of the lane to determine whether the warning needs to turn on. In the last part of this paper, we present the experiment results which show the comparison results of different lane conditions. We do the statistic of the proposed LDWS accuracy in terms of detection and departure. The detection rate of our proposed LDWS is 98.2% and the departure rate of it is 99.1%. The average processing time of our proposed LDWS is 20.01 x 10−3s per image.

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 Computer Vision for Road Safety written by Mahdi Rezaei and published by . This book was released on 2014 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advances in Visual Computing written by George Bebis and published by Springer Science & Business Media. This book was released on 2008-11-13 with total page 1245 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNCS 5358 and LNCS 5359 constitutes the refereed proceedings of the 4th International Symposium on Visual Computing, ISVC 2008, held in Las Vegas, NV, USA, in December 2008. The 102 revised full papers and 70 poster papers presented together with 56 full and 8 poster papers of 8 special tracks were carefully reviewed and selected from more than 340 submissions. The papers are organized in topical sections on computer graphics, visualization, shape/recognition, video analysis and event recognition, virtual reality, reconstruction, motion, face/gesture, and computer vision applications. The 8 additional special tracks address issues such as object recognition, real-time vision algorithm implementation and application, computational bioimaging and visualization, discrete and computational geometry, soft computing in image processing and computer vision, visualization and simulation on immersive display devices, analysis and visualization of biomedical visual data, as well as image analysis for remote sensing data.

Download or read book Accuracy of Stereo based Object Tracking in a Driver Assistance Context written by Waqar Khan and published by . This book was released on 2013 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stereo vision is currently used in the car industry as a tool for designing driver-assistance systems. However, limitations inherently due to the discrete nature of disparities observed by a stereo-vision system have not yet been modelled and analysed so far; this thesis aims at closing this gap. Stereo-vision results are used in driver-assistance systems for estimating trajectories or just speed. Besides accuracy limitations in stereo matching, the discrete nature of disparities also defines limitations to detected trajectories or speed. This thesis proposes and discusses a novel tool for a safety engineer which permits the safety of these driver assistance systems to be estimated. It is based on a model which considers the true error in measured velocities of objects. Outputs from this tool show that the choice of stereo-system parameters, so as to optimally place the disparity change boundaries, is critical to the effectiveness of such a system. As soon as the possibly colliding object crosses one of these boundaries, the range of possible trajectories for a (possibly colliding) object reduces significantly. This factor also means that larger objects (e.g. trucks) are slightly better tracked by stereo vision than smaller ones (e.g. signs or pedestrians). Completely safe stereo-based systems are also shown to issue many precautionary (and ultimately unnecessary) warnings if the stereo parameters are not chosen carefully.

Download or read book Robotic Vehicles Systems and Technology written by Tian Seng Ng and published by Springer Nature. This book was released on 2021-03-06 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the technological innovations of robotic vehicles. It presents the concepts required for self-driving cars on the road. Besides, readers can gain invaluable knowledge in the construction, programming, and control of the six-legged robot. The book also presents the controllers and aerodynamics of several different types of rotorcrafts. It includes the simulation and flight of the various kinds of rotor-propelled air vehicles under each of their different aerodynamics environment. The book is suitable for academia, educators, students, and researchers who are interested in autonomous vehicles, robotics, and rotor-propelled vehicles.

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 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 A Lane Detection Vision Module for Driver Assistance written by Kristijan Maček and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Predicting Vehicle Trajectory written by Cesar Barrios and published by CRC Press. This book was released on 2017-03-03 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on improving the prediction of a vehicle’s future trajectory, particularly on non-straight paths. Having an accurate prediction of where a vehicle is heading is crucial for the system to reliably determine possible path intersections of more than one vehicle at the same time. The US DOT will be mandating that all vehicle manufacturers begin implementing V2V and V2I systems, so very soon collision avoidance systems will no longer rely on line of sight sensors, but instead will be able to take into account another vehicle’s spatial movements to determine if the future trajectories of the vehicles will intersect at the same time. Furthermore, the book introduces the reader to some improvements when predicting the future trajectory of a vehicle and presents a novel temporary solution on how to speed up the implementation of such V2V collision avoidance systems. Additionally, it evaluates whether smartphones can be used for trajectory predictions, in an attempt to populate a V2V collision avoidance system faster than a vehicle manufacturer can.

Download or read book Communication Technologies for Vehicles written by Francine Krief and published by Springer Nature. This book was released on 2020-12-19 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th International Workshop on Communication Technologies for Vehicles, Nets4Cars/Nets4Trains/Nets4Aircraft 2020, held in Bordeaux, France, in November 2020. The 18 full papers were carefully reviewed and selected from 22 submissions. The selected papers present orig-inal research results in areas related to the physical layer, communication protocols and standards, mobility and traffic models, experimental and field operational testing, and performance analysis.

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 Vision based Driver Assistance System Using Integration Information from Lane Geometry and Traffic Direction written by 黃贊宇 and published by . This book was released on 2007 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development and Demonstration of a Cost effective In vehicle Lane Departure and Advanced Curve Speed Warning System written by Muhammad Faizan and published by . This book was released on 2018 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Lane-Departure Warning System (LDWS) and Advance Curve-Warning System (ACWS) are critical among several Advanced Driver-Assistance Systems (ADAS) functions, having significant potential to reduce crashes. Generally, LDWS use different image processing or optical scanning techniques to detect a lane departure. Such LDWS have some limitations such as harsh weather or irregular lane markings can influence their performance. Other LDWS use a GPS receiver with access to digital maps with lane-level resolution to improve the system's efficiency but make the overall system more complex and expensive. In this report, a lane-departure detection method is proposed, which uses a standard GPS receiver to determine the lateral shift of a vehicle by comparing a vehicle’s trajectory to a reference road direction without the need of any digital maps with lane-level resolution. This method only needs road-level information from a standard digital mapping database. Furthermore, the system estimates the road curvature and provides advisory speed for a given curve simultaneously. The field test results show that the proposed system can detect a true lane departure with an accuracy of almost 100%. Although no true lane departure was left undetected, occasional false lane departures were detected about 10% of the time when the vehicle did not actually depart its lane. Furthermore, system always issues the curve warning with an advisory speed at a safe distance well ahead of time.