Sökning: "CARLA Driving Simulator"
Visar resultat 1 - 5 av 15 uppsatser innehållade orden CARLA Driving Simulator.
1. Evaluation of Deep Q-Learning Applied to City Environment Autonomous Driving
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och systemSammanfattning : 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
2. Using Simulation-Based Testing to Evaluate the Safety Impact of Network Disturbances for Remote Driving
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The transportation industry has been transforming because of rapid digitalization and autonomy. Because of this the demand for more connected and autonomous vehicles is increasing for both private individuals and businesses. Reducing human interaction emphasizes the need for higher road safety. LÄS MER
3. Reachability Analysis for Occlusion Reasoning in Realistic Autonomous Driving Scenarios
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In this Bachelor Thesis, we tackle a crucial issue in autonomous driving technology - the detection and reasoning of occluded areas and potential occluded vehicles in realistic scenarios. Autonomous driving has gained significant momentum in recent years, but ensuring safety remains a major concern. LÄS MER
4. Robust Safe Control for Automated Driving Systems With Perception Uncertainties
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Autonomous Driving Systems (ADS), a subcategory of Cyber-Physical Systems (CPS) are becoming increasingly popular with ubiquitous deployment. They provide advanced operational functions for perception and control, but this also raises the question of their safety capability. LÄS MER
5. Risk-Sensitive Decision-Making for Autonomous-Driving
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : A natural aspect of the real world is that one can face uncertain situations on a daily basis. Depending on one's experience, we humans behave and respond differently to uncertainty. However, when designing intelligent agents, one needs to pay attention to the uncertainty inlearning tasks to design risk-sensitive algorithms. LÄS MER