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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.
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