MobileyeComputer vision and AI powering driver assistance and autonomous driving systems.
Overview
Key features
- 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
Pricing
- Model
- Freemium
- Category
- Computer Vision
- Rating
- 4.2 / 5 (5)
Use cases
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.
Pros & Cons
Pros
- 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
Cons
- Primarily B2B, not accessible to individual consumers
- Heavy reliance on camera-based perception
- Integration requires deep automaker partnerships
Reviews
Average from 5 ratings.
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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.
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.
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.
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.
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.
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