Global Self-Driving Car Maps Market 2018-2023

Introduction

The maps for the driverless cars must be very detailed (HD), containing all the critical characteristics of the road, including the slope and the curvature, the types of marking of the lane and the objects that are on the edge of the road.

Moreover, it is necessary to build the mapping system for autonomous cars that will become part of the driverless car software, to ensure that the vehicle can be placed inside it and allow the rich and almost real-time incorporation of contextual awareness of the situation of traffic around the vehicle. It is obvious that GPS-based maps are not accurate enough for new generation cars that do not have drivers. When dealing with a regular map, the position of the machine can be identified by about one meter.

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Market Dynamics

A self-driving car collects more than one terabyte of data a day. With that highly detailed information coming from the numerous car sensors; it is not cheap to send it via a network like the Internet. The cumbersome data storage is just one of the technical problems that many of the brightest engineering minds are facing. Many companies have not discovered how to actually store their data, which is why autonomous vehicles are geo-fenced. Physically they cannot adapt to the data in the trunk of the car, so they are limited to certain areas.

The major challenge for self-driving car maps is to keep them updated continuously so that they provide the latest information to the cars. Unlike conventional digital maps, self-guided 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 car without a driver. For full autonomous cars to be deployed, it needs to have a high-definition map of the area, like a map annotated with what are the permanently fixed objects in that area.

Market Size

The companies at present develop maps by driving cars fitted with LIDAR rotating units mounted on the top of their cars that shoot lasers, making pictures of the street and nature. Engineers, in a time-consuming process, review images and label objects that are found, such as stop signs, buildings, traffic lights, and non-entry signs. The laser equipment needed to perform this scan is expensive; it can cost a lot to equip with only one car to do this job.

Most of the mapping company’s use lidar technology to create their maps for self-driving cars, but when we see the cost of the LIDAR system which is >$10,000 per unit as of now, a very expensive amount for mapping companies to equip the lidar systems on their cars and map the cities around them. Therefore, we believe there is a strong possibility of a subscription model that could be brought in by mapping companies to reign in the high initial mapping cost. Depending on the market volume of autonomous cars, the market value for autonomous car maps could reach multi billion dollars by 2023.Most of the companies have entered into agreements to pool their resources to map the world.


Competitive Landscape

Dozens of companies are creating highly detailed, multi-layered road and highway maps, and there's still a lot of work to do. The established companies like HERE and TomTom have been present in this market for quite some time now. There are also many well-funded start-ups active in this market like Mapillary, Carmera, Deepmap and Civil maps. Going forward, as autonomous cars move closer to production, we believe the list will grow.

Companies Profiled

1. TomTom
2. Here
3. Sanborn
4. Baidu
5. Mobileye
6. Waymo
7. NavInfo
8. Navmii
9. AutoNavi(Alibaba)
10. TELENAV
11. Nvidia
12. Micello
13. Civil maps
14. Deepmap
15. lvl5
16. Carmera
17. Mapbox
18. Mapper
19. Mapillary
20. Point one navigation

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