Mapping In High-Definition Is What Unlocks Autonomous Trucking Secrets

Mapping In High-Definition Is What Unlocks Autonomous Trucking Secrets
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For autonomous-vehicle technology, some trucks are likely going to need to travel by high-definition mapping surveys. These are especially exciting means. I mean, we’re talking about trucks that are autonomous and are capable of bringing technology together for the sake of AV tech. Passenger cars may not have the same need to travel as widely and thoroughly via complex road networks.

But autonomous trucking is the future! For mapping that is.

To put this a little more clearer, look at it like this, HD maps are combining with three layers of info. There’s 3D representation of the road while also showing off stop signs and lane markings, while also going into the extent of crosswalks, curb heights and so forth. Much was seen with precise accuracy. Alternatively, there’s such an interpretive later that can show an Autonomous Vehicle what signs differ from each other, as well as the lights and the markings themselves. Overall, this is known as the semantic layer. Thirdly, a vector outlines the optimal paths of driving, which in turn, gives AV “virtual rails.”

Map makers then prove to show off the additional information which is superimposable from beyond the layers. Additionally, the frequency shows that the maps gets a huge update. From here, HD maps evolve from simplicity to then assist an Autonomous Vehicle to get what the AV sees and anticipates, furthered beyond the horizon. HD maps as they are can turn into a fourth sensor that would completely change the LiDAR and radar abilities commonly found on autonomous vehicles. That’s certainly something new.

The industry of trucking as it shows is one of a specific data deficit. Which can play into parts as lane width, turn angles, signal distances, auxiliary lane presence and cargo restrictions. Motion planning is although a valid concern for autonomous vehicles.

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