Searched for: contributor:"Gavrila, Dariu (graduation committee)"
(1 - 11 of 11)
document
Ammerlaan, Jelle (author)
Self-driving vehicles have shown rapid development in recent years and continue to move towards full autonomy. For high or full automation, self-driving vehicles will have to be able to address and solve a broad range of situations, one of which is interaction with traffic agents. For correct and save maneuvering through these situations,...
master thesis 2020
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Glastra, Thom (author)
The bottleneck of the maximum road volume in urban areas is the maximum capacity of the traffic flow on the intersection, which is coordinated with Traffic Light Controllers (TLCs). A promising method to decrease the number of stops are Green Light Optimal Speed Advice (GLOSA) systems. These systems will give a speed advice to arriving vehicles...
master thesis 2020
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van Schouwenburg, Sietse (author)
Simultaneous Localization And Mapping (SLAM) algorithms provide accurate localization for autonomous vehicles and provide essential information for the path planning module. However, SLAM algorithms as- sume a static environment in order to estimate a location. This assumption influences the pose estimation in dynamic urban environments. The...
master thesis 2019
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Ai, Zhiwei (author)
Deep learning methods have been demonstrated to be promising in semantic segmentation of point clouds. Existing works focus on extracting informative local features based on individual points and their local neighborhood. They lack consideration of the general structures and latent contextual relations of underlying shapes among points. To this...
master thesis 2019
document
YANG, MINGHAO (author)
One-Shot Neural Architecture Search (NAS) is a promising method to significantly reduce search time without any separate training. It can be treated as a Network Compression problem on the architecture parameters from an overparameterized network. However, there are two issues associated with most one-shot NAS methods. First, dependencies...
master thesis 2019
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Bos, Evert (author)
With an in vehicle camera many different things can be done that are essential for ADAS or autonomous driving mode in a vehicle. First, it can be used for detection of general objects, for example cars, cyclists or pedestrians. Secondly, the camera can be used for traffic light recognition, which is localization of traffic light position and...
master thesis 2019
document
Katsaounis, Georgios (author)
Recent advances in sensor technology have lead to increased resolution of novel sensors, while tracking applications where distance between sensors and objects of interest is very small have gained research interest recently. In these cases, it is possible that multiple sensor detections are generated by each object of interest. Extended Object...
master thesis 2019
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Kossen, Rebecca (author)
Autonomous driving is a development that has gained a lot of attention lately, because it can lead to major improvements in the mobility sector. One example of a research project that aims to develop vehicles that are capable of reaching the highest level of autonomy in driving, is the WEpods project. The goal of this research is in line with...
master thesis 2019
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Wout, Daan (author)
A prevalent approach for learning a control policy in the model-free domain is by engaging Reinforcement Learning (RL). A well known disadvantage of RL is the necessity for extensive amounts of data for a suitable control policy. For systems that concern physical application, acquiring this vast amount of data might take an extraordinary amount...
master thesis 2019
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Wang, Ziqi (author)
This work explores the possibility of incorporating depth information into a deep neural network to improve accuracy of RGB instance segmentation. The baseline of this work is semantic instance segmentation with discriminative loss function.The baseline work proposes a novel discriminative loss function with which the semantic net-work can learn...
master thesis 2018
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Wymenga, Jan (author)
This work presents a multi-sensor approach for weather condition estimation in automated vehicles. Using combined data from weather sensors (barometer, hygrometer, etc) and an in-vehicle camera, a machine learning and computer vision framework is employed to estimate the current weather condition in realtime and in-vehicle. The use of different...
master thesis 2018
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