Lane Change Intention Recognition Models Using Hidden Markov Models and Relevance Vector Machines

The development of intelligent vehicle and autonomous driving asked a higher requirement of ADAS on its functionality. Currently, ADAS systems are able to detect and segment urban and highway driving scenes. They cannot, in general, extract ’meaning’ from this segmentation yet. Learning the intention of other road users will help ADAS understand...

Vehicle motion prediction for autonomous driving: A deep learning model based on vehicle interaction and road geometry using a semantic map

To be able to understand the dynamic driving environment, an autonomous vehicle needs to predict the mo- tion of other traffic participants in the driving scene. Motion prediction can be done based on experience and recently observed series of past events, and entails reasoning about probable outcomes with these past ob- servations. Aspects that...

Deep End-to-end Network for 3D Object Detection in the Context of Autonomous Driving

Nowadays, autonomous driving is a trending topic in the automotive field. One of the most crucial challenges of autonomous driving research is environment perception. Currently, many techniques achieve satisfactory performance in 2D object detection using camera images. Nevertheless, such 2D object detection might be not sufficient for autonomous...

Grey Matter Age Prediction as a Biomarker for Risk of Dementia: A Population-based Study

The gap between predicted brain age and chronological age could serve as biomarker for early-stage neurodegeneration and as potentially as a risk indicator for dementia. We assess the utility of this age gap as a risk biomarker for incident dementia in a general elderly population. The brain age is estimated from longitudinal brain magnetic...

Development of vehicle-cyclist interaction model for scenario generation/validation

The number of road accidents is increasing all over the world. When Vulnerable Road Users (VRU) are involved in an accident, they are prone to more serious injuries. Half of the fatalities around the world involve VRUs. One way of mitigating the severity and the number of VRU accidents is the introduction of Advanced Driver Assistance Systems ...

Deep segmentation of the drivable path of a self-driving vehicle using external data: Influence of domain shift factors and depth information

Robot Care Systems (RCS) is involved in the development of the WEpod, an autonomous shuttle which can transfer up to six people. Based on a predefined map of the environment, the shuttle is able to navigate through mixed traffic its perception sensors such as camera, radar and lidar sensors. This study is acquired in collaboration with RCS and...

Framework Design and Image Registration for Sonar-Based Underwater SLAM

The startup company Fleet Cleaner has developed a mobile robot, specialized in the hull cleaning of large cargo vessels. Navigation and localization of this robot is currently performed manually. This is a difficult process that is greatly complicated during operation. This is mainly due to the availability of relative positioning sensors only,...

Robust Tracking Approach for Dealing with Classification Uncertainty

Every year about 1.25 million people die as a result of road traffic accidents. Besides the traffic on the road increases every day, including the environmental impact due to the corresponding traffic emissions. Autonomous driving could be a unique opportunity to increase these traffic safety, traffic flow efficiency and to reduce emissions in...

Segmenting and Detecting Carotid Plaque Components in MRI

Cardiovascular diseases and stroke are currently the leading causes of death worldwide. Atherosclerotic plaque is a mostly asymptotic vascular disease, but rupture of an atherosclerotic plaque in the carotid artery could lead to stroke. Automated segmentation of plaque components could help improve risk assessment by producing fast and reliable...

Vehicle Trajectory Prediction Using Road Structure

An autonomous vehicle should be able to operate amidst numerous other human-driven vehicles, each driving on its own trajectory. To safely navigate in such a dynamic environment, the autonomous vehicle should be able to predict trajectories of the vehicles operating in its vicinity and use these to plan its own path. Most related work uses a...