Sökning: "Advanced Driving Assistance System ADAS"

Visar resultat 1 - 5 av 26 uppsatser innehållade orden Advanced Driving Assistance System ADAS.

  1. 1. Challenges in Specifying Safety-Critical Systems with AI-Components

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Iswarya Malleswaran; Shruthi Dinakaran; [2023-09-26]
    Nyckelord :Software engineering; Requirement engineering; Specification; Safety; Computer Science; Engineering; Machine learning; Deep learning; Runtime monitor; Data Selection; Data Collection;

    Sammanfattning : Safety is an important feature in automotive industry. Safety critical system such as Advanced Driver Assistance System (ADAS) and Autonomous Driving (AD) follows certain processes and procedures in order to perform the desired function safely. LÄS MER

  3. 2. Assessing the Efficiency of COLMAP, DROID-SLAM, and NeRF-SLAM in 3D Road Scene Reconstruction

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Marcus Ascard; Farjam Movahedi; [2023]
    Nyckelord :3D reconstruction; Visual SLAM; Pose evaluation; Point cloud evaluation; Road scenes; Technology and Engineering;

    Sammanfattning : 3D reconstruction is a field in computer vision which has evolved rapidly as a result of the recent advancements in deep learning. As 3D reconstruction pipelines now can run in real-time, this has opened up new possibilities for teams developing Advanced Driver Assistance Systems (ADAS), which rely on the camera system of the vehicle to enhance the safety and driving experience. LÄS MER

  4. 3. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Ziyou Li; [2023]
    Nyckelord :Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

    Sammanfattning : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. LÄS MER

  5. 4. Truck drivers’ attitudes and interactions with advanced driver assistance systems : Applying the joint cognitive system perspective and the contextual control model in naturalistic driving contexts

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Tobias Ryrberg; [2023]
    Nyckelord :ADAS; attitudes; trust; interaction; automation; JCS; COCOM;

    Sammanfattning : One of the most common causes of death is road accidents and in 95% of these accidents the human factor is involved. Therefore, Advanced-Driver-Assistance-Systems (ADAS) have been developed to support the drivers. LÄS MER

  7. 5. Jointly Ego Motion and Road Geometry Estimation for Advanced Driver Assistance Systems

    Master-uppsats, Linköpings universitet/Reglerteknik

    Författare :Jawaria Asghar; [2021]
    Nyckelord :autonomous car; ego-vehicle; road geometry; estimation; Advanced Driver Assistance Systems; sensor fusion; Unscented Kalman Filter.;

    Sammanfattning : For several years, there has been a remarkable increase in efforts to develop an autonomous car. Autonomous car systems combine various techniques of recognizing the environment with the help of the sensors and could drastically bring down the number of accidents on road by removing human conduct errors related to driver inattention and poor driving choices. LÄS MER