NVIDIA Alpamayo 2 Super
NVIDIA Alpamayo 2 Super is a frontier open model for robotaxis and autonomous vehicles, built to reason through rare, complex driving situations and produce decisions developers can inspect, validate, and trust. Based on NVIDIA Cosmos 3 Super Reasoner and post-trained with reinforcement learning, it combines commercial openness with multitask capabilities for autonomous driving. The model reasons across full-surround camera coverage, fusing front, side, and rear views to understand lane changes, merges, unprotected turns, and complex intersections. For each scenario, it can generate a planned vehicle trajectory, a chain-of-causation trace explaining the decision, a meta-action such as yielding or stopping, reasoning auto-labels for training and validation, and visual question-answering responses grounded in specific image regions. These linked outputs make it easier to connect what the model observed with the action it selected.
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Waymo
Waymo is an autonomous driving technology company that develops self-driving vehicles and operates fully driverless transportation services. Originally created as Google’s self-driving car project in 2009, the company later became an independent subsidiary of Alphabet with the goal of making transportation safer, more accessible, and more efficient through autonomous mobility. Its core technology, known as the Waymo Driver, combines artificial intelligence, high-resolution cameras, radar, lidar sensors, and detailed digital maps to allow vehicles to perceive their surroundings and navigate roads without human intervention. It continuously analyzes traffic signals, pedestrians, other vehicles, and road conditions to determine safe driving actions in real time. Before operating in a new area, Waymo vehicles map roads in extreme detail, identifying lane markings, signs, and intersections, and then combine this information with real-time sensor data to maintain precise positioning.
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Apollo Autonomous Vehicle Platform
Various sensors, such as LiDAR, cameras and radar collect environmental data surrounding the vehicle. Using sensor fusion technology perception algorithms can determine in real time the type, location, velocity and orientation of objects on the road. This autonomous perception system is backed by both Baidu’s big data and deep learning technologies, as well as a vast collection of real world labeled driving data. The large-scale deep-learning platform and GPU clusters. Simulation provides the ability to virtually drive millions of kilometers daily using an array of real world traffic and autonomous driving data. Through the simulation service, partners gain access to a large number of autonomous driving scenes to quickly test, validate, and optimize models with comprehensive coverage in a way that is safe and efficient.
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sunnypilot
sunnypilot is an open source driver assistance system designed for customization, transparency, and driver empowerment. It upgrades Adaptive Cruise Control (ACC), Automated Lane Centering (ALC), Forward Collision Warning (FCW), and Lane Departure Warning (LDW) across a growing range of supported vehicles, while camera-based Driver Monitoring alerts distracted or sleeping drivers. Its Modular Assisted Driving System (MADS) can decouple lateral control from longitudinal control, allowing steering assistance to remain active even when cruise control is disengaged. Enhanced Speed Control can adjust cruise speed using the vision model, OpenStreetMap data, and Speed Limit Assist, while Enhanced Automatic Lane Changes supports customizable lane changes initiated by the blinker or a steering nudge and can use Blind Spot Monitoring for obstacle prevention. A Driving Model Selector lets users switch between available driving models directly from the sunnypilot interface or through sunnylink.
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