Empowering the Autonomous World through AI

Artificial intelligence technologies are fundamentally changing the way we work, communicate and live. While the development of digital assistants, smart buildings, location-aware wearables, and autonomous cars and drones all apply these technologies in different ways, they have one common element: location intelligence. As a global leader in this field, our developers, data scientists, and researchers are finding new and exciting ways to create location intelligence for the smart cities, vehicles and devices that will shape our future.


This work focuses on detecting 3D road features for automatically building the HD Map. These features include the (yellow) lane and (blue) road boundaries shown in the video, among others. By applying deep convolutional networks to our HERE True LiDAR, we capture 3D geometry and surface reflectivity to produce centimeter accurate 3D features.

    Deep Learning Road Features from LiDAR
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    Detecting building signs from street-level imagery
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We’re proud to work with some of brightest minds in AI

Principal Research Engineer, HAD

Steve O’Hara

As part of our Highly Automated Driving (HAD) division’s Sensing and Perception Team, Steve utilizes deep neural networks in embedded and constrained devices to ensure our HD Live Map is always up to date.

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Head of Highly Automated Driving

Sanjay Sood

By integrating GPS location data with cutting-edge machine learning and natural language processing, Sanjay is pushing the boundaries of location intelligence to make autonomous driving a reality.

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Teaching a vehicle to see in real-time

Teaching a car’s navigation system to recognize signs and objects is no easy task. Using the latest advances in machine learning, we train our models to identify each object with high fidelity under a wide variety of environmental conditions.

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Maps that continuously adapt

An autonomous vehicle is only as good as the data behind it. As an autonomous vehicle drives down the road, it orients itself by continuously cross-referencing data from our HD Live Map with the signs, poles, and lane markers it detects with its sensors. But what happens when it detects an object that’s not on our map? That’s where our location intelligence comes in.

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