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  1. 1. Evaluation of Deep Q-Learning Applied to City Environment Autonomous Driving

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

    Författare :Jonas Wedén; [2024]
    Nyckelord :Machine Learning; ML; Reinforcement Learning; RL; Neural Network; Deep Learning; Autonomous Vehicle; Vehicle; CARLA; Convolutional Neural Network; CNN; Precisit; Q-learning; Deep Q-learning; DQN;

    Sammanfattning : This project’s goal was to assess both the challenges of implementing the Deep Q-Learning algorithm to create an autonomous car in the CARLA simulator, and the driving performance of the resulting model. An agent was trained to follow waypoints based on two main approaches. LÄS MER

  3. 2. Självkörande fordon : En fallstudie av positiva och negativa ekonomiska och socialaeffekter av införande av självkörande lastbilar i ett transportföretag.

    Kandidat-uppsats,

    Författare :issa zeid Baker; Abdullah Hassan; [2024]
    Nyckelord :;

    Sammanfattning : The transport industry is facing major challenges as customers strive for high quality services and fast deliveries. Therefore, transport companies started investing in new innovations to be able to satisfy the customer's requirements. LÄS MER

  4. 3. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks

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

    Författare :Xinchen Wang; [2024]
    Nyckelord :Deep Learning; Semantic segmentation; Network optimization; Network pruning; Torch Pruning; YOLOv8; Network Depth; Djup lärning; Semantisk segmentering; Nätverksoptimering; Nätverksbeskärning; Fackelbeskärning; YOLOv8; Nätverksdjup;

    Sammanfattning : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. LÄS MER

  5. 4. On Expressing Automotive Maneuvers with SFC

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

    Författare :Zizhuang Cui; Jiacheng Li; [2023-10-05]
    Nyckelord :space-filling curve; Software engineering; software testing; taxonomy;

    Sammanfattning : Conventional methods for testing autonomous driving software often involve dealing with a large number of dimensions, which can complicate the processing and analysis of test datasets. Therefore, there is a pressing need to develop a more efficient approach that is both time and cost-effective. LÄS MER

  7. 5. 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