Mobileye

Computer vision and AI powering driver assistance and autonomous driving systems.

4.2 (5)

Évalué par Daniel Nikulshyn·Mis à jour mai 2026

Edge AI Autonomous Driving B2B Enterprise Computer Vision Automotive AI HD Mapping ADAS

Aperçu

Mobileye develops advanced driver-assistance systems (ADAS) and self-driving technologies built around camera-based computer vision, EyeQ system-on-chip processors, and AI-driven decision making. Its technology is deployed by major automakers worldwide to enable features like lane keeping, collision avoidance, adaptive cruise control, and progressively higher levels of vehicle autonomy. The company also offers solutions for fleet safety, high-definition mapping through its REM crowdsourcing approach, and full self-driving platforms such as Mobileye Drive and Chauffeur. By combining perception, mapping, and policy software, Mobileye aims to make roads safer while moving the industry toward scalable autonomous mobility.

Fonctionnalités clés

EyeQ SoC for on-vehicle AI processing
Camera-based perception and object detection
Road Experience Management (REM) HD mapping
Responsibility-Sensitive Safety (RSS) driving policy
ADAS solutions for OEMs and fleets
Mobileye Drive autonomous driving platform

Cas d’usage

OEM ADAS Integration

Automakers integrate Mobileye's EyeQ SoC and camera-based perception to deliver driver-assistance features like lane keeping, collision avoidance, and adaptive cruise control.

Fleet Safety Deployment

Commercial fleet operators deploy Mobileye's ADAS solutions to reduce accidents, monitor driver behavior, and improve overall road safety across their vehicle fleets.

HD Mapping at Scale

Mapping and mobility providers leverage Mobileye's REM crowdsourced approach to build and maintain high-definition maps using real-world driving data from equipped vehicles.

Autonomous Vehicle Platforms

Mobility operators and automakers use Mobileye Drive and Chauffeur platforms to develop robotaxis and self-driving vehicles with integrated perception, mapping, and RSS-based driving policy.

Pour & contre

Pour

Proven technology adopted by many global automakers
Strong expertise in vision-based perception and AI
Scalable from ADAS to full autonomy
Crowdsourced REM mapping for real-world coverage

Contre

Primarily B2B, not accessible to individual consumers
Heavy reliance on camera-based perception
Integration requires deep automaker partnerships

Avis

4.2

Moyenne sur 5 avis.

Connecte-toi pour laisser un avis.

Wei Chen

Solid for our team

We rolled this out across the team last quarter and scalable from ADAS to full autonomy. Road Experience Management (REM) HD mapping fits neatly into how we already work, and mobileye Drive autonomous driving platform removed a step we used to do by hand. Integration requires deep automaker partnerships, which is the main caveat, but it has held up under daily use.

Robert Ainsworth

Solid for our team

We rolled this out across the team last quarter and proven technology adopted by many global automakers. EyeQ SoC for on-vehicle AI processing fits neatly into how we already work, and road Experience Management (REM) HD mapping removed a step we used to do by hand. but it has held up under daily use.

Priya Nair

Does the job

Pretty happy overall. ADAS solutions for OEMs and fleets just works and crowdsourced REM mapping for real-world coverage. Integration requires deep automaker partnerships can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Tariq Aziz

Years in this space

I've evaluated a lot of these over the years. What stands out here is aDAS solutions for OEMs and fleets — handled better than most — and scalable from ADAS to full autonomy. Integration requires deep automaker partnerships is my one real gripe. Worth the time if this is your use case.

Tomáš Novák

Years in this space

I've evaluated a lot of these over the years. What stands out here is eyeQ SoC for on-vehicle AI processing — handled better than most — and crowdsourced REM mapping for real-world coverage. Integration requires deep automaker partnerships is my one real gripe. Worth the time if this is your use case.