Mitigation of Motion Sickness Using Optimal Speed Profiling in Automated Vehicles

It is anticipated that for the automated driving industry to grow, public acceptance is required. The trust and acceptance of automated vehicles are primarily dependent on the travelling experience of people. In automated vehicles, passengers are expected to be engaged in non-driving tasks that are likely to decrease their predictability of the...

Safe Navigation in Dense Traffic Scenarios using Reinforcement Learning as Global Guidance for a Model Predictive Controller

The successful integration of autonomous vehicles (AVs) in human environments is highly dependent on their ability to navigate safely and timely through dense traffic conditions. Such conditions involve a diverse range of human behaviors, ranging from cooperative (willing to yield) to non-cooperative human drivers (unwilling to yield) that need...

Motion Planning for Non-holonomic Autonomous Vehicles in Parking Spaces: An optimal Control Problem Approach

This MSc. thesis explores the design and implementation of a motion planner for non-holonomic autonomous vehicles in parking spaces. The planner must avoid collisions with static obstacles, satisfy performance, comfort and safety constraints for the motion, satisfy the non-holonomic constraints of the vehicle model, consider the dynamics of the...