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BANGALORE, INDIA, September 12, 2018 /24-7PressRelease/ --
The GPS-based maps (Machine to human), used at present are not accurate enough for self-driving cars as they require centimeter level accuracy. The maps for the self-driving cars must be very detailed (Machin to machine), containing all the critical characteristics of the road, including the slope, curvature, lane markings and pavements. Moreover, it is necessary to build the mapping system for autonomous cars that will become part of the autonomous car software, to ensure almost real-time incorporation of contextual awareness of the situation of traffic around the vehicle.
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A continuous exchange of data between vehicles and the cloud can overload data networks and data storage, creating additional challenges for software vendors. As of now, Map providers are making efforts to reduce the amount of data exchanged between a vehicle and the cloud by augmenting the amount of information handled inside the vehicle. A proposed solution is a so-called "self-repair map" that would use on-board artificial intelligence algorithms and in-depth learning to navigate without going too far into the cloud. The built-in artificial vision algorithms may recognize milestones and road signs captured by cameras.
A major challenge for self-driving car map market is to keep them updated continuously so that they provide the latest information to the cars. Unlike conventional digital maps, self-driving car maps require almost constant updates. The slightest variation on the road, a construction zone that opens during the night or a bit of debris could stop a self-driving car. For full autonomous cars to be deployed, it needs to have a high-definition map of the area, like a map annotated with the permanently fixed objects in that area.
There is no common standard obvious for these HD maps. Everyone is trying to develop its own internal HD mapping. In other words, everyone is reinventing the wheel and wasting a lot of resources. This could probably be one of the reasons that could stop cars from becoming a commodity. Because mapping companies do not share cartographic data and use different standards, they need to create new maps for each city they want to be in. As of now, every autonomous car map looks different because it depends on the sensor system of the vehicle that creates it.
There are ~90 million passenger cars sold every year. Given the growth in research of autonomous cars, even if a handful of those become autonomous, it would create a multi- billion dollar opportunity for HD maps as every autonomous car needs one.
There are ~30 companies trying to create HD maps for autonomous cars. The market comprises about 8-10 established players and more than 20 start-ups. Here (now jointly owned by Audi, BMW, and Daimler)is in a very good position to establish market leadership. The autonomous car concept has disrupted the automotive industry and we are seeing unusual developments.
The lucrative business potential of autonomous car maps as brought together many unconventional partnerships. Some of the examples include
• Bosch partnering with Tomtom
• Here acquisition by Audi,Daimler and BMW
• One map alliance created by Here
• TomTom partnering with Elektrobit
11. Point one navigation
19. Civil maps
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