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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 President and CEO Karl Iagnemma, Chief Technology Officer Laura Major, and others told NACTO attendees about the company’s driverless technology, approach to safety and accessibility, and the IONIQ 5 robotaxi. 

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.

Motional engineers and product designers are creating an AV capable of serving dual purposes without losing functionality for either.

Chapter 3 of Motional's DriverlessEd series explains how AV companies like Motional are using research to understand what makes a ride comfortable, the types of features passengers expect, ways to make the vehicles accessible, and even how AVs can communicate with people.

Motional researchers are developing an app-based feature that lets riders with disabilities ask their robotaxi for more time while being picked up.

Motional is learning how to measure whether a ride in a driverless vehicle feels safe, comfortable, or both.

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

Motional is using AI to sift through mountains of vehicle data to find the unique driving scenarios needed to make AV tech smarter.

When it comes to cybersecurity, the Autonomous Vehicle Product Development Lifecycle , or AVPDL, is intended to establish a nomenclature for communicating about the development lifecycle.