For immersive telepresence within a vehicle, the operator needs to be fully aware of the current driving situation. The problem is how to measure if the operator recognized all driving relevant information. Tracking the operators gaze while driving might be a possible solution. ... [mehr]

Speaker: Sungkyu Lee Room: 1967 At the current stage of autonomous driving, failures in complex situations are inevitable. Instead of minimizing the amount of failures, the idea of introspection is to learn when a prediction for a given input cannot be trusted. The learned... [mehr]

In the near future, autonomous cars will continue to make mistakes that require human supervision to correct. To allow enough time for a human to take over, it is necessary to predict that a failure is about to occur. One approach is to try and detect input that is different from... [mehr]

Clouds have great visual impact and emotional influence on people. However, the volumetric nature of cloud make it difficult to reproduce in a computer, especially in video games which require the rendering process to be real-time. This thesis aims to find a method to render... [mehr]

Donkey Car (https://www.donkeycar.com) is an opensource DIY self-driving platform for small scale racing cars equipped with a Raspberry Pi and a wide-angle Raspberry Pi camera. It allows driving your car with your phone or laptop and recording images, steering angles and... [mehr]

Date: 14.01.2020, 13:15 Room: 1967 [mehr]

The goal is to research different approaches for autonomous driving in the CARLA simulator. Publicly available models should be implemented and compared with regards to the errors the models make. [mehr]

At the current stage of autonomous driving, failures in complex situations are inevitable. A learning-based method to predict such failures could prevent dangerous situations or crashes. However, collecting real-life training data of crashes caused by autonomous vehicles is not... [mehr]

Speaker: Furkan Kaynar 10:00, room 1967 [mehr]

Date: 12.12.2019, 12:30 Room: 1967 [mehr]