Articles

Yi Wang, Senior Principal Engineer at Motional, does a deep dive into our approach for scaling our ML pipelines, and demonstrates three example design cases.

By rethinking system architecture and using machine learning to analyze and process previously discarded low-level radar data, Motional is working on dramatically enhancing radar performance to the point that it rivals the point clouds produced by lidar. 

Motional is part of Pittsburgh’s growing high tech ecosystem, which is providing opportunities for talented innovators to plant their roots in the region, instead of moving away. 

Arthur Safira, a Senior Engineering Director at Motional, talks about his background, his growth at Motional, and his mission to make a positive, large-scale societal impact with technology.

Motional’s all-electric IONIQ 5 robotaxis are trained to ignore all the lights and sights that make Las Vegas a memorable experience. and instead focus solely on safely navigating through the complex driving environment. 

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.

When faced with an unusual driving condition, Motional's robotaxis can rely on trained Remote Vehicle Assistance agents to provide guidance on a safe path forward. 

Motional's VP of Commercialization, Akshay Jaising, talks about what the company has learned as it grows its food delivery business and starts delivering Shake Shack orders made through Uber Eats  

Motional's PredictNet approach to prediction uses machine learning principles and a multi-task learning architecture to more accurately predict the future behaviors of surrounding agents.

As AV technology advances, and the global supply chain responds to industry demand, radars could emerge as the central sensors for robotaxis, says Motional's Chief Technology Officer.

When developing autonomous vehicles, nothing is more important than safety. The safety of those driving, walking, or biking near our robotaxis is just as important as the safety of the person inside the vehicle. Learn how our vehicles respond to their environment in Chapter 7 of #DriverlessEd.

Teams from around the world competed in Motional's 2023 nuPlan Challenge, which helped research into advanced autonomous driving planners.

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.

Megan Mears started as a Motional intern before transitioning to a full-time role as a Technical Program Coordinator. Megan discusses her work at Motional and passion for using AVs to increase independence and opportunities for individuals with disabilities.