Submitted by JÚLIO HEBER SILVA (julioheber@yahoo.com.br) on 2016-11-10T13:48:13Z No. of bitstreams: 2 Dissertação - Rômulo Muriel Mesquita de Oliveira - 2015.pdf: 7641184 bytes, checksum: b650ba6efa2c0aba74125271f293ebcc (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Jaqueline Silva (jtas29@gmail.com) on 2016-11-10T17:42:47Z (GMT) No. of bitstreams: 2 Dissertação - Rômulo Muriel Mesquita de Oliveira - 2015.pdf: 7641184 bytes, checksum: b650ba6efa2c0aba74125271f293ebcc (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2016-11-10T17:42:47Z (GMT). No. of bitstreams: 2 Dissertação - Rômulo Muriel Mesquita de Oliveira - 2015.pdf: 7641184 bytes, checksum: b650ba6efa2c0aba74125271f293ebcc (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2015-02-20 / The increasing number of accidents on roads and highways around the world is causing concern in many government agencies. Because of that, actions have been proposed to eradicate this reality, which claims the lives of millions annually. Within the different types of traffic accidents occurring, one specific has gained space in the media, which involves the door of a vehicle, improperly opened, causing collision with a cyclist, motorcyclist or other vehicle. The law states to be responsible for the accident the one who opened the door without taking proper precautions, however, due to physical and emotional factors that disturb each day more the society, lives in traffic can?t be under the responsibility of a person. Many assistive technologies that helps in decision making or even contributing to road safety, have been submitted to the automotive market, which once included in vehicles would save the lives of thousands. Aware of this, this paper proposes a technology that, through low cost ultrasonic sensor detects possibility of collision on the side of the vehicle and sends alerts to the driver so he or she does not open the door during the moment of risk. For development of this security system was necessary to define which ultrasonic sensor to use, to prepare the case for the hardware accommodation, to build the computer program, to analyze the positioning of the system in the vehicle and to execute experimental tests to validate the ADS (Avoiding Doored System), name given to the collision avoidance system / A elevação do número de acidentes em estradas e rodovias ao redor do mundo vem causando preocupação em muitos órgãos governamentais. Em função disso, ações vêm sendo propostas para erradicação dessa realidade, que tira a vida de milhões anualmente. Dentro os vários tipos de acidentes que ocorrem no trânsito, um muito específico vem ganhando espaço na mídia, aquele envolvendo a porta de um veículo, aberta indevidamente, causando colisão com um ciclista, motociclista ou mesmo outro veículo. A legislação determina ser responsável pelo acidente àquele que abriu a porta sem tomar as devidas precauções, no entanto, devido a fatores físicos e emocionais, que perturbam cada dia mais a sociedade, deixar vidas no trânsito sob responsabilidade de terceiros não é uma escolha prudente. Inúmeras tecnologias assistivas, que auxiliam na tomada de decisão ou mesmo que contribuem para segurança no trânsito, vêm sendo apresentadas ao mercado automobilístico, as quais, uma vez inclusa nos veículos, pouparia a vida de milhares. Nesse contexto, este trabalho apresenta uma proposta de tecnologia que, por meio de sensor ultrassônico de baixo custo, detecta possibilidade de colisão na lateral do veículo devido à abertura da porta e emite alerta ao condutor, de forma que este não abra a porta durante o instante de risco. Para tanto, foi necessário desenvolver um sistema de mapeamento do campo de atuação do sensor, de modo que fosse possível determinar o mais adequado para o desenvolvimento do sistema. Além disso, foi projetado e construído um “case” para acomodação dos periféricos do sistema, desenvolvido o software de controle do sistema e posteriormente foi analisado o posicionamento do sistema no veículo e aplicação de testes experimentais para avaliação funcional do ADS (Avoiding Doored System), assim nomeado o sistema que evita colisões por abertura da porta.

The aim of this diploma thesis is the research of building polygons for the testing of autonomous vehicles, from the point of view of road technology and also designing aspects. In the thesis are mentioned 9 most important world test polygons and their description of design parameters. There are described particular stages of automation from foreign organizations which are concerned with research and development in the automotive industry. In addition, there are described basic advanced driver assistance systems and connectivity between vehicles and infrastructure. Conclusion also contains the assessment of existing aerodrome test areas for autonomous vehicles.

This master‘s thesis describes the design and implementation of the system for detection and recognition of speed limit road signs. It focuses on the recognition of the red circular speed limit sign from the image data using the computer vision methods. Several methods were programmed and tested as a part of this thesis. In the final solution, the segmentation based on YCbCr color model is used. Detection of the circular sign and final classification is performed by template matching method. Algorithm for the tracking of the detected signs between frames of the video is used for better performance in real-time recognition. Application is developed using MATLAB and Simulink. The result is a simple driver assistance system prototype, which can be implemented in any computer with camera. The correct function of the algorithm was confirmed during a testing in a traffic.

abstract: Object detection is an interesting computer vision area that is concerned with the detection of object instances belonging to specific classes of interest as well as the localization of these instances in images and/or videos. Object detection serves as a vital module in many computer vision based applications. This work focuses on the development of object detection methods that exhibit increased robustness to varying illuminations and image quality. In this work, two methods for robust object detection are presented. In the context of varying illumination, this work focuses on robust generic obstacle detection and collision warning in Advanced Driver Assistance Systems (ADAS) under varying illumination conditions. The highlight of the first method is the ability to detect all obstacles without prior knowledge and detect partially occluded obstacles including the obstacles that have not completely appeared in the frame (truncated obstacles). It is first shown that the angular distortion in the Inverse Perspective Mapping (IPM) domain belonging to obstacle edges varies as a function of their corresponding 2D location in the camera plane. This information is used to generate object proposals. A novel proposal assessment method based on fusing statistical properties from both the IPM image and the camera image to perform robust outlier elimination and false positive reduction is also proposed. In the context of image quality, this work focuses on robust multiple-class object detection using deep neural networks for images with varying quality. The use of Generative Adversarial Networks (GANs) is proposed in a novel generative framework to generate features that provide robustness for object detection on reduced quality images. The proposed GAN-based Detection of Objects (GAN-DO) framework is not restricted to any particular architecture and can be generalized to several deep neural network (DNN) based architectures. The resulting deep neural network maintains the exact architecture as the selected baseline model without adding to the model parameter complexity or inference speed. Performance results provided using GAN-DO on object detection datasets establish an improved robustness to varying image quality and a higher object detection and classification accuracy compared to the existing approaches. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2020

Navigation systems are one of the most commonly found electronic gadgets in modern vehicles nowadays. Alongside navigation units this technology is made readily available to individuals in everyday devices such as a mobile phone. Digital maps which come preloaded on these devices accommodate within them an extensive dataset of spatial information from around the globe which aids the driver in achieving a well guided driving experience. Apart from being essential for navigation this sensor information backs up other vehicular applications in making intelligent decisions. The quality of this information delivered is in direct relation to the underlying dataset used to produce these maps. Since we live in a highly dynamic environment with constantly changing geography, an effort is necessary to keep these maps updated with the most up to date information as frequently as possible. The digital map of interest in this study is OpenStreetMap, the underlying data of which is a combination of donated as well as crowdsourced information from the last 10 years. This extensive dataset helps in building of a detailed digital map of the world using well defined cartographic techniques. The information within OpenStreetMap is currently enhanced by a large group of volunteers who willing use donated satellite imagery, uploaded GPS tracks, field surveys etc. to correct and collect necessary data for a region of interest. Though this method helps in improving and increasing the quality and quantity of the OpenStreetMap dataset, it is very time consuming and requires a great deal of human effort. Through this thesis an effort is made to automatically enrich this dataset by preprocessing crowdsourced sensor data collected from the navigation system and driver assistance systems (Traffic Sign Recognition system and a Lane Detection System) of a driving vehicle. The kind of data that is algorithmically derived includes the calculation of the curvature of the underlying road, correction of speed limit values for individual road segments being driven and the identification of change in the geometry of existing roads due to closure of old ones or addition of new ones in the Nuremberg region of Bavaria, Germany. Except for a small percentage of speed limit information on roads segments, other information is currently not available in the OpenStreetMap database for use in safety and comfort related applications. The navigation system has the ability to deliver geographical data in form of GPS coordinates at a certain frequency. This set of GPS coordinates can grouped together to form a GPS track visualizing the actual path traversed by a driving vehicle. A large number of such GPS tracks repeatedly collected from different vehicles driving in a region of interest gives all GPS points which lie on a particular road. These points, after outlier elimination methods are used as a dataset to scientifically determine the underlying curvature of the road with the aid of curve fitting techniques. Additional information received from the lane detection system helps identify curves on a road for which the curvature must be calculated. The fusion of information from these sources helps to achieve curvature results with high accuracy. Traffic sign recognition system helps detect traffic signs while driving, the fusion of this data with geographical information from the navigation system at the instance of detection helps determine road segments for which the recognized speed limit values are valid. This thesis successfully demonstrates a method to automatically enrich OpenStreetMap data by crowdsourcing raw sensor data from multiple vehicles equipped with driver assistance systems. All OpenStreetMap attributes were 100% updated into the database and the results have proven the effectiveness our system architecture. The positive results obtained in combination with minimal errors promise a better future for assisted driving.

The demand for Advanced Driver Assistance System (ADAS) applications is increasing day by day and their development requires efficient prototyping and real time testing. ADTF (Automotive Data and Time Triggered Framework) is a software tool from Elektrobit which is used for Development, Validation and Visualization of Vision based applications, mainly for ADAS and Autonomous driving. With the help of ADTF tool, Image or Video data can be recorded and visualized and also the testing of data can be processed both on-line and off-line. The development of ADAS applications needs image and video processing and the algorithm has to be highly efficient and must satisfy Real-time requirements. The main objective of this research would be to integrate OpenCV library with ADTF cross platform. OpenCV libraries provide efficient image processing algorithms which can be used with ADTF for quick benchmarking and testing. An ADTF filter framework has been developed where the OpenCV algorithms can be directly used and the testing of the framework is carried out with .DAT and image files with a modular approach. CMake is also explained in this thesis to build the system with ease of use. The ADTF filters are developed in Microsoft Visual Studio 2010 in C++ and OpenMP API are used for Parallel programming approach.

Durch die Entwicklung und Einführung moderner Fahrerassistenzsysteme soll der Komfort und die Sicherheit des Autofahrens erhöht werden. Das Fahrerassistenzsystem Speed Control verbindet die Ergebnisse der Forschungsarbeiten der letzten Jahre aus dem Bereich des Straßenentwurfs und der Fahrzeugtechnik. Dieses System warnt den Kraftfahrer vor sicherheitskritischen Stellen in der Linienführung von Außerortsstraßen. Es empfiehlt dem Fahrer eine sicher und komfortabel fahrbare Geschwindigkeit für den vorausliegenden Streckenabschnitt. Dafür wurden in Abhängigkeit des Fahrertyps Modelle zur Prognose und Beschreibung des Geschwindigkeits- und Beschleunigungsverhaltens entwickelt. Die Umgebungsbedingungen (Tag, nass) werden dabei mit beachtet. / By developing and implementing modern driver assistance systems the comfort and safety of driving shall be improved. The driver assistance system Speed Control combines the last year’s research work results in the fields of road design and automotive engineering. This system alerts the driver to safety critic spots in the alignment of roads. It recommends a safe and comfortable driving speed for the road segment ahead. Therefore driver type depending models to predict and describe the speed and acceleration behaviour were developed. Withal environmental conditions (day, wet) are regarded.

This thesis work aims at performing a survey of those technologies generally called DriverAssistance Systems (DAS). This thesis work focuses on gathering information in terms ofaccident statistics, sensors and functions and analyzing this information and shall thruaccessible information match functions with accidents, functions with sensors etc.This analysis, based on accidents in United States and Sweden during the period 1998 – 2002and two truck accident studies, shows that of all accidents with fatalities or sever injuriesinvolving a heavy truck almost half are the result of a frontal impact. About one fourth of theaccidents are caused by side impact, whereas single vehicle and rear impact collisions causesaround 14 % each. Of these, about one fourth is collision with unprotected (motorcycles,mopeds, bicycles, and pedestrians) whereas around 60 % are collision with other vehicles.More than 90 % of all accidents are partly the result of driver error and about 75 % aredirectly the result of driver error. Hence there exist a great opportunity to reduce the numberof accidents by introducing DAS.In this work, an analysis of DAS shows that six of the systems discussed today have thepotential to prevent 40 – 50 % of these accidents, whereas 20 – 40 % are estimated to actuallyhaving the chance to be prevented.One of these DAS, automatic emergency brake (AEB), has been analyzed in more detail.Decision models for an emergency brake capable to mitigate rear-end accidents has beendesigned and evaluated. The results show that this model has high capabilities to mitigatecollisions.

The main goal of this work is to gain knowledge of how and to what extent state-of-the-artsimulation tools can be used in a conceptual development phase for vehicle dynamics control atVolvo Car Corporation (VCC).The first part of the thesis deals with an evaluation of vehicle dynamics simulation tools and theiruses. The three simulation tools selected for the study, namely Mechanical Simulation CarSim 8.2.1,IPG CarMaker 4.0.5, and VI-Grade CarRealTime V14, are briefly described and discussed. In order toevaluate and compare these tools with respect to application for vehicle dynamics control, a criterialist is developed covering aspects such as tool requirements and intended usage. Based on thecriteria list and certain identified drawbacks, a ranking of the tools is made possible. Furthermore,the process of developing vehicle models for the different tools is discussed in detail, along with theprocedure of validating the vehicle models.In the second part, the concept of Collision Avoidance Driver Assistance (CADA) function isintroduced and possible approaches for developing CADA functions are discussed in brief. It isimportant to note that the CADA functions in this work are based on cornering the vehicle i.e.maneuvering around the threat, rather than solely reducing vehicle speed. A number ofimplementations of the functions are developed in Simulink. A frequency analysis of a simplifiedlinear vehicle model is performed to investigate the influence of steering, differential braking, andtheir combination on the resultant lateral displacement of the vehicle during an evasive maneuver.The developed CADA functions are then simulated using the vehicle simulation tools. Two specificmetrics - Lateral Displacement gain and DeltaX - are formulated to evaluate the effectiveness of theCADA functions. Based on these metrics, the assistance obtained due to the functions for a specificevasive maneuver is compared.From the evaluation process of the three tools, two were considered suitable for the purpose ofsimulating collision avoidance functions. The evaluation of the CADA functions demonstrates thatcombined assistive steering with differential braking provides considerable assistance in order toavoid collisions. The simulation results also present interesting trends which provide a usefuldirection regarding the conditions for intervention by such collision avoidance functions during anevasive maneuver. The use of simulation tools makes it possible to observe these trends and utilizethem in the development process of the functions.

Dieser Beitrag untersucht Potenziale des Einsatzes von MBE-Ansätzen bei der Validierung von Fahrerassistenzsystemen. Ziel ist die Untersuchung der Machbarkeit des Aufbaus einer Validierungsumgebung zur Automatisierung von Tests im Rahmen der kontinuierlichen Validierung von Fahrerassistenzsystemen. [... aus der Einleitung]