Zenseact Scalable Mapping
| Title | Zenseact Scalable Mapping |
|---|---|
| Summary | Scalable mapping through crowd sourcing |
| Keywords | |
| TimeFrame | Fall 2022 |
| References | |
| Prerequisites | |
| Author | |
| Supervisor | TBD |
| Level | Master |
| Status | Open |
This thesis aims to develop a scalable method to crowdsource certain elements of an HD map by collecting sensor data from a fleet of vehicles and fusing the information into a single coherent road model. The focus is to describe the geometry of lane markers, traffic signs, and natural driving profiles on a large scale, or at least from a handful of drives on the ring roads of Göteborg.
The topic is proposed by Zenseact. More details are available here:
https://career.zenseact.com/jobs/2113621-master-thesis-scalable-mapping-through-crowd-sourcing
About Zenseact: We develop the complete software stack for ADAS and AD, from sensing to actuation. Our focus is to build a single cutting-edge software platform in order to serve various levels of autonomy and offer unequaled scalability at the same time. We operate in Sweden and China.
