Sökning: "Learning in autonomous vehicles"

Visar resultat 1 - 5 av 47 avhandlingar innehållade orden Learning in autonomous vehicles.

  1. 1. Terrain machine learning

    Författare :Viktor Wiberg; Martin Servin; Tomas Nordfjell; Eddie Wadbro; Todor Stoyanov; Umeå universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; LANTBRUKSVETENSKAPER; AGRICULTURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; multibody dynamics simulation; rough terrain vehicle; autonomous vehicles; robotics control; discrete element method; sim-to-real; reinforcement learning; fysik; Physics;

    Sammanfattning : The use of heavy vehicles in rough terrain is vital in the industry but has negative implications for the climate and ecosystem. In addition, the demand for improved efficiency underscores the need to enhance these vehicles' navigation capabilities. LÄS MER

  2. 2. Decision-Making in Autonomous Driving using Reinforcement Learning

    Författare :Carl-Johan E Hoel; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Monte Carlo tree search; epistemic uncertainty; tactical decision-making; reinforcement learning; neural networks; aleatoric uncertainty; autonomous driving;

    Sammanfattning : The main topic of this thesis is tactical decision-making for autonomous driving. An autonomous vehicle must be able to handle a diverse set of environments and traffic situations, which makes it hard to manually specify a suitable behavior for every possible scenario. LÄS MER

  3. 3. Data-Efficient Learning of Semantic Segmentation

    Författare :David Nilsson; Mathematical Imaging Group; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; semantic segmentation; embodied learning; active learning; semantic video segmentation; computer vision; deep learning;

    Sammanfattning : Semantic segmentation is a fundamental problem in visual perception with a wide range of applications ranging from robotics to autonomous vehicles, and recent approaches based on deep learning have achieved excellent performance. However, to train such systems there is in general a need for very large datasets of annotated images. LÄS MER

  4. 4. Modelling Pedestrians in Autonomous Vehicle Testing

    Författare :Maria Priisalu; Matematik LTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; pedestrian sensing; pedestrian forecasting; pedestrian motion synthesis; generative testing; autonomous vehicle testing; reinforcement learning;

    Sammanfattning : Realistic modelling of pedestrians in Autonomous Vehicles (AV)s and AV testing is crucial to avoid lethal collisions in deployment. The majority of AV trajectory forecasting literature do not utilize the motion cues present in 3D human pose because it is hard to gather large datasets of articulated 3D pedestrian motion. LÄS MER

  5. 5. On Supervisor Synthesis via Active Automata Learning

    Författare :Ashfaq Hussain Farooqui; Chalmers tekniska högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Supervisory control theory; Finite-state machines; Active learning; Model learning; Automata learning; Discrete-event systems;

    Sammanfattning : Our society's reliance on computer-controlled systems is rapidly growing. Such systems are found in various devices, ranging from simple light switches to safety-critical systems like autonomous vehicles. In the context of safety-critical systems, safety and correctness are of utmost importance. LÄS MER