HD maps deliver a faithful representation of the road with laser-sharp precision, setting a new standard for in-car navigation systems of autonomous vehicles. The HD mapping technology allows a driverless vehicle to localize itself with high precision, mapping its exact location with respect to the surrounding environment. As opposed to traditional maps, HD maps are not intended for general navigation. HD maps for autonomous driving integrate and analyze sets of data from multiple sources, such as vehicle sensors, LiDAR, onboard cameras, satellite imagery, and GPS in real time. The fusion of this car big data reflects the exact position of the car in relation to all landmarks, supplying comprehensive, up-to-the-second information about road gradients and boundaries, traffic signaling, lane placement, anticipated curves, and safety conditions.

 

Although HD map technology has made great progress in promoting auto driving, there are still some defects to be solved. The high surveying and mapping cost and the lack of common standards have certain restrictions on the development of the HD map market. In order to solve these problems, advanced navigation companies such as Tomtom, NVIDIA and Here maps are joining forces with professional IT suppliers such as Intellias. Through cooperation, their goal is to reduce the cost burden and accelerate the market entry of their high-precision mapping solutions, which will help promote the market development of HD maps.

 

Nowadays, there are two mainly types of HD Maps, including Crowdsourcing Model and Centralized Mode. And Crowdsourcing Model is the main type for HD Maps, reaching a sales value of approximately 977.16 million USD in 2021, with 72.62% of global sales value.

 

Global HD Map for Autonomous Driving market size will reach US$ 24,023.79 million by 2028, from US$ 1,345.65 million in 2021, growing at a CAGR of 50.89% during 2022 and 2028.

 

 

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