Sökning: "Driving model"

Visar resultat 1 - 5 av 1063 uppsatser innehållade orden Driving model.

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. 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

4. 3. CNN-LSTM architecture for predicting hazardous driving situations

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

   Författare :Noomi Lindblad; Stefani Platakidou; [2023-10-05]
   Nyckelord :Data science; Machine learning; LSTM; CNN; Vehicle data; Hazardous driving situation; Deep learning;

   Sammanfattning : This study aims to investigate how a CNN-LSTM model can be used together with recorded vehicle data from trucks and external weather data in order to predict a hazardous driving situation. The dataset consists of three-second-long driving snippets from customer and development trucks registered within Europe. LÄS MER

5. 4. 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

7. 5. Digitalization and Electrification´s Transformational Impact on the Automotive Mobility Industry - A multiple case study on the Swedish automotive mobility industry facing changing business models, challenges, and future opportunities

   Master-uppsats, Göteborgs universitet/Graduate School

   Författare :Max Guron; [2023-07-19]
   Nyckelord :Digitalization; Electrification; Business model; Business model framework; Business model innovation; Technological Change; Industrial Change; Disruptive technology; Automotive Mobility; Automotive Industry; Mobility services; Car-sharing; Automotive manufacturers; Car-sharing providers; ride-hailing providers;

   Sammanfattning : The automotive mobility industry, including car manufactures, car-sharing, and ride-hailing companies, is experiencing technological change through electrification and digitalization. These two trends can potentially disrupt the whole industry through, i.e. LÄS MER