Abstract
Early and accurate detection of crossing pedestrians is crucial in automated driving to execute emergency manoeuvres in time. This is a challenging task in urban scenarios however, where people are often occluded (not visible) behind objects, e.g. other parked vehicles. In this paper, an occlusion aware multi-modal sensor fusion system is proposed to address scenarios with crossing pedestrians behind parked vehicles. Our proposed method adjusts the detection rate in different areas based on sensor visibility. We argue that using this occlusion information can help to evaluate the measurements. Our experiments on real world data show that fusing radar and stereo camera for such tasks is beneficial, and that including occlusion into the model helps to detect pedestrians earlier and more accurately.
| Original language | English |
|---|---|
| Title of host publication | Proceedings IEEE Symposium Intelligent Vehicles (IV 2019, Paris) |
| Place of Publication | Piscataway, NJ, USA |
| Publisher | IEEE |
| Pages | 1768-1774 |
| ISBN (Electronic) | 978-1-7281-0560-4 |
| DOIs | |
| Publication status | Published - 2019 |
| Event | IEEE Intelligent Vehicles Symposium 2019 - Paris, France Duration: 9 Jun 2019 → 12 Jun 2019 |
Conference
| Conference | IEEE Intelligent Vehicles Symposium 2019 |
|---|---|
| Abbreviated title | IV 2019 |
| Country/Territory | France |
| City | Paris |
| Period | 9/06/19 → 12/06/19 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.