Vmware, Inc.

Mitsubishi Electric Research Laboratories, Inc.

Tianshu Chu

Uros Kalabic

Rakesh Misra

Alexandros Anemogiannis

Rahul Tandra

Kanthi Nagaraj

Sandeep Chinchali

A system and method for training and executing an adaptive bitrate (ABR) controller can include clustering content into content clusters based on content metadata, clustering network scenarios based on network information, normalizing input measurements, training the ABR controller for each content within at least one of a given content cluster and a given network scenario cluster by determining network information and network metadata, associated with the respective content, determining a content bitrate, determining a reward associated with the content bitrate, and training the ABR controller based on the reward.

System and method for widescale adaptive bitrate selection

A system for direct and indirect control of mixed-autonomy vehicles receives a traffic state of a group of mixed-autonomy vehicles traveling in the same direction, wherein the group of mixed-autonomy vehicles includes controlled vehicles willing to participate in a platoon formation and at least one uncontrolled vehicle, and wherein the traffic state is indicative of a state of each vehicle in the group, submit the traffic state into a parameterized function trained to transform the traffic state into target headways for the mixed-autonomy vehicles to produce the target headways, and submit the target headways to a headway-based model configured to map the target headways to target speeds of the mixed-autonomy vehicles to produce the target speeds. The system determines and transmits control commands to the controlled vehicle based on one or combination of the target headways and the target speeds.

Direct and indirect control of mixed-automata vehicle platoon

Growing community of inventors

Palo Alto, CA, United States of America

Tianshu Chu