Sökning: "autonomous driving"

Visar resultat 11 - 15 av 447 uppsatser innehållade orden autonomous driving.

  1. 11. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network

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

    Författare :Jiayi Feng; [2023]
    Nyckelord :DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Embedded Systems; DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Inbyggda system;

    Sammanfattning : Customized Deep Neural Network (DNN) accelerators have been increasingly popular in various applications, from autonomous driving and natural language processing to healthcare and finance, etc. However, deploying them directly on embedded system peripherals within real-time operating systems (RTOS) is not easy due to the paradox of the complexity of DNNs and the simplicity of embedded system devices. LÄS MER

  3. 12. Lateral Control of Heavy Vehicles

    Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Författare :Aravind Jawahar; Lokesh Palla; [2023]
    Nyckelord :Path Tracking; Collision Avoidance; Pure Pursuit; Stanley; Linear Quadratic Regulator; Sliding Mode Control; Model Predictive Control; Path Tracking; Collision Avoiding; Pure Pursuit; Stanley; Linear Quadratic Regulator; Sliding Mode Control; Model Predictive Control;

    Sammanfattning : The automotive industry has been involved in making vehicles autonomous to different levels in the past decade rapidly. Particularly in the commercial vehicle market, there is a significant necessity to make trucks have a certain level of automation to help reduce dependence on human efforts to drive. LÄS MER

  4. 13. Dynamic Object Removal for Point Cloud Map Creation in Autonomous Driving : Enhancing Map Accuracy via Two-Stage Offline Model

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

    Författare :Weikai Zhou; [2023]
    Nyckelord :Autonomous driving; Dynamic object removal; Map creation; 3D point cloud; Autonom körning; Dynamiska objekt borttagning; Skapande av kartor; 3D-punktmoln;

    Sammanfattning : Autonomous driving is an emerging area that has been receiving an increasing amount of interest from different companies and researchers. 3D point cloud map is a significant foundation of autonomous driving as it provides essential information for localization and environment perception. LÄS MER

  5. 14. Vem eller vad kan hållas straffrättsligt ansvarig för ett självkörande fordon? : En analys av gällande rätt och föreslagen lagstiftning i Sverige

    Uppsats för yrkesexamina på avancerad nivå, Stockholms universitet/Juridiska institutionen

    Författare :Petri Dahlström; [2023]
    Nyckelord :Self-driving; autonomous; automated; automatic; AV; vehicles; cars; artificial intelligence; AI; machine learning; electronic person; criminal liability; Självkörande; autonoma; automatiserade; artificiell intelligens; AI; maskininlärning; elektronisk person; fordon; bilar; straffrättsligt ansvar; ansvarsbedömning;

    Sammanfattning : The last decade has seen a rapid advancement in the fields of artificial intelligence (AI) and automation, with terms such as machine learning, deep learning and algorithms finding their way into everyday conversations. The usage of AI is evergrowing and present in many areas of life such as health care, financial services, and social media interactions. LÄS MER

  7. 15. A requirements engineering approach in the development of an AI-based classification system for road markings in autonomous driving : a case study

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknik

    Författare :Srija Sunkara; [2023]
    Nyckelord :Requirements Engineering; Machine Learning; Goal-Oriented Requirements Engineering; Autonomous Driving; Point Cloud Classification;

    Sammanfattning : Background: Requirements engineering (RE) is the process of identifying, defining, documenting, and validating requirements. However, RE approaches are usually not applied to AI-based systems due to their ambiguity and is still a growing subject. LÄS MER