A Path Forward: Using AI to Improve Remote Vehicle Assistance for AVs
As Motional’s robotaxis drive more, our vehicle assistance system will use machine learning principles to become smarter and require less human intervention over time.
Polar Stream: Simultaneous Object Detection and Semantic Segmentation Algorithm for Streaming Lidar
Motional’s research has unlocked an approach to streaming object detection that reduces latency while increasing accuracy, giving AVs even better data needed to make safe decisions.
Technically Speaking: Predicting the future in real time for safer autonomous driving
Motional uses multi-modal prediction models to more accurately predict and anticipate what agents around our AVs are going to do next.
Technically Speaking: Mining For Scenarios To Help Better Train Our AVs
Motional is using AI to sift through mountains of vehicle data to find the unique driving scenarios needed to make AV tech smarter.
Technically Speaking: Auto-labeling With Offline Perception
Motional is building a world-class offline perception system that will automatically label the data required to train our next-generation vehicles.
Two-thirds of Americans Agree: The Future is Driverless
Motional's first Consumer Mobility Survey found that a majority of Americans look forward to a future where driverless vehicles are the norm, that 62% of respondents agree that self-driving vehicles are the way of the future, and one in four Americans are excited to ride in one.