H.J. Boekema
8 records found
1
Automated Vehicles (AVs) rely on up-to-date map information to inform trajectory prediction and planning modules, but these maps are expensive to obtain and update as they are usually annotated by humans. We propose SAM-Maps, a method for automatically generating road maps from a
...
We present a vehicle system capable of navigating safely and efficiently around Vulnerable Road Users (VRUs), such as pedestrians and cyclists. The system comprises key modules for environment perception, localization and mapping, motion planning, and control, integrated into a p
...
This paper studies road user trajectory prediction in mixed traffic, i.e. where vehicles and Vulnerable Road Users (VRUs, i.e. pedestrians, cyclists and other riders) closely share a common road space. We investigate if typical prediction components (scene graph representation, s
...
This letter presents View-of-Delft Prediction, a new dataset for trajectory prediction, to address the lack of on-board trajectory datasets in urban mixed-traffic environments. View-of-Delft Prediction builds on the recently released urban View-of-Delft (VoD) dataset to make it s
...