Nexar Automotive | Vision-Based Car Services & Data

Nexar’s dash cams unique image data can be used for a range of connected vehicle services and driver apps

Crowd-sourced vision for real time mapping and driver applications

Dynamic location based services, using crowd-sourced vision for a digital twin of the road

Nexar is about the future of connected car vision. It collects vision data in a scalable and economical manner, so that a swarm of vehicles can share vision data from the world, mapping transient and static road elements, to ensure a safe future of driving, for driver assist and autonomous vehicle applications.

A new set of eyes on the road

Car cameras are about to become ubiquitous. When they become connected and share vision data, they can go beyond any single purpose sensor and create a shared vision and map of the road, detecting change and seeing transient elements. When vision from a “swarm of cameras” is collected, applications can access a common visual memory of the road

Nexar Automotive gets this camera data out of the car and delivers new driver applications, based on the most recent understanding of the road.

Nexar’s CityStream uses trillions of images received from the Nexar dash cam network

Our Coverage

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How It Works

Nexar Automotive allows users to get camera data out of the car

Detecting Change on the Road

Leverage Nexar’s largest independent vision data network and AI detections, and get transient data (work zones) and change detections of road inventory. These constantly updated detections are localized, anonymized and aggregated in a scalable and economical way for the use of auto manufacturers, AV companies, mapping companies and more.

The Future of Connected Car Services

Automotive manufacturers can also offer a variety of camera-based apps, allowing drivers to store dash cam videos, send video messages from the road, or review footage of break-ins and hit-and-runs while their car is parked.

Mapping & Change Detection

Use AI on top of fresh imagery to identify road signs, work zones and blockages, traffic lights and more. “See” the ground truth and detect changes or road hazards to scalably see and respond to changes that are happening in the real world.

Nexar streets enables access to fresh imagery by location and address

Autonomous Vehicles

AV training needs are evolving. They move from a few miles of high-fidelity data, collected by specialized vehicles with high-end sensors, to a vast data set collected by vehicles using a crowd-sourced vision network. This visual safety data, such as corner cases, collisions and near-collision, is then used for benchmarking and training AVs.

Nexar’s CityStream provides road inventory service for monitoring traffic signs & signals

Driver Behavioral Maps

Driver behavioral maps are based on crowd-sourced driving insights for different road segments, driver types, weather and other road conditions. Local agents that have driven in an area know more than agents that have not, autonomous or human. Driver behavioral data captures the information about actual human driving, and overlays it on a map, for autonomous and assisted driving. This data is overlaid on the base map as a high definition map layer showing human behavior on the maps that AVs use for driving. AVs can use it to know when to switch lanes before a turn, how to decelerate when cornering, where virtual stop lines are and more.

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Nexar’s CityStream automatically detects barricade elements in work zones using AI

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Compute and Connectivity Optimization

It is challenging to take vision data out of the car and apply compute to create a digital twin of the road. Vision data is heavy and comes at the cost of bandwidth, due to compute and connectivity challenges when extracting this data from cars. Nexar’s new IETF lisp-Nexagon (Nexar-Hexagon) standard - created in collaboration with the AECC - uses the network edge as an aggregation buffer between cars and the cloud.

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