High Accuracy and Real-time Maps for Autonomous Vehicles

Autonomous and fully driverless vehicles will require high accuracy maps enabling precise positioning within lanes based on reference points on 3D models of the road environment. Additionally, maps will need to be updated continuously with real-time information about traffic, roadworks, and any other relevant information needed for anticipating and planning the path ahead and emulate human driving. These requirements can only be met by crowdsourcing sensor data from  vehicles on the road, transforming both the way maps are generated and the entire ecosystem involved in the creation of maps, with new players like car OEMs, Tier1 players, and software vendors already showing interest. 

This report discusses in detail the characteristics of driverless maps, production processes, the players involved and their solutions, issues and challenges, and new pricing and business models. It also provides in-depth information about crowdsourcing technology, including hybrid approaches and the role of 5G.  

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