3: Mapping & Ridesharing

Ride sharing services have spread across the globe and is changing the way people commute short distances mostly within urban areas. Services like Uber, Lyft among others have based their business models on drivers. Recent developments in self driving technology can be disruptive with the involvement of these ride sharing services. Uber recently announced the opening of research facility at Carnegie Mellon, home to "The boss" which won the DARPA urban challenge in 2007.

Uber also drives around 2+ million miles(uber is private company,so a guesstimate) which means simply creating a hardware that can easily be retrofitted onto cars will make the mapping of the world's roads a relatively easier task. This theory is also reinforced by the fact that Microsoft just sold its data acquisition task of maps to uber, while also investing in Uber. Thus mapping using crowd-sourcing can be a very powerful way to collect data for processing as shown by Tesla.

Uber now has arguably one of the top research groups in self driving cars, and massive funding to leverage that potential to market. With this infrastructure to collect data, uber and other ride sharing firms have an enormous advantage to collect data quickly.

TomTom another mapping service provider announced their capabilities in mapping for autonomous cars. A 3D border to border representation of a road by tomtom is shown below.

Carlos Ghosn recently about autonomous cars how auto industry will strive to avoid becoming a commodity much like OS driven smartphone industry took the established hardware makers by storm. Thus Renault-Nissan, Daimler and others are working at collecting data and becoming less reliant on established players like google to provide service to self driving cars mainly mapping data.