Articles

Motional has developed a Second-Stage Vision Network that uses machine learning principles to add important context to our object classifications -- additional fine-grain classification then flows downstream improving our perception, prediction, planning, and control substacks.

Motional uses continuous fuzzing to make sure that our software is as safe and secure as possible before deploying it – or if there is a glitch, that the system can handle it gracefully.

Pat Karnchanachari, a Senior Engineer with Motional and our nuPlan™ Team Lead, talks about why he loves working in the AV space, his favorite project, and how he decompresses.

Transformer Neural Networks are receiving increased attention about how they can improve AI-driven technology. Our latest Technically Speaking blog explores how Motional has been using Transformers to make our perception function better. 

Motional's latest Technically Speaking blog explains how we're using machine learning to speed up the process of mapping public roadways prior to launching commercial passenger service. 

Motional's latest Technically Speaking blog focuses on Planning, and how using closed-loop training will help refine the modeling AVs use to create a safe path forward quicker.

Motional is making its Autonomous Vehicle Cybersecurity Development Lifecycle (AVCDL) publicly available for others to review and adopt, in order to help the industry secure against cybersecurity threats. 

Motional recently completed a multi-million dollar expansion project that doubled the amount of office and garage space located in the heart of Singapore’s high-tech district, growing the company's R&D and Operations footprint in the country

Motional uses multi-modal prediction models to more accurately predict and anticipate what agents around our AVs are going to do next.

Motional is building a world-class offline perception system that will automatically label the data required to train our next-generation vehicles.