Collaborative Research: Ideas Lab: Breaking Low: DRIVE-SAFE: Remote and Cooperative Autonomous Driving in Dynamic Environments using 5G/NextG Technology

NSF Award Search · 01002627DB NSF RESEARCH & RELATED ACTIVIT · $470,000 · view on nsf.gov ↗

Abstract

This project aims to break the low latency performance barrier in today’s fifth generation (5G) networks that hinders progress and adoption of remote driving industry (the “vertical” application). It advances an innovative “vertical-aware” framework to optimize both 5G networks and the vertical application. Despite tremendous progress, today’s “self-driving” cars may encounter many situations where they cannot drive themselves safely. Examples include construction zones and traffic accidents on the road. By ensuring low latency needed for remote driving, the developed solutions will allow a human teleoperator to remotely steer a “connected and autonomous” vehicle (CAV) through complex situations as if sitting in the driver seat. Technological advances enabled by this project will help (re-)establish the U.S.’s leadership in next-generation (NextG) wireless telecommunications and major vertical industries such as automotive and robotic automation. This project also provides a unique educational platform to train students and expand the STEM (Science, Technology, Engineering & Mathematics) workforce. Two major hurdles in ensuring low latency over 5G networks are i) high mobility of vehicles leads to poor radio channel conditions, causing data delivery errors; ii) frequent handovers among radio base stations further prolong data delivery. The project will develop a novel Open Radio Access Network (O-RAN) enabled, vertical-driven framework with mobility-aware, proactive mecha

Key facts

NSF award ID
2453817
Awardee
University of California-Riverside (CA)
SAM.gov UEI
MR5QC5FCAVH5
PI
Hang Qiu
Primary program
01002627DB NSF RESEARCH & RELATED ACTIVIT
All programs
Estimated total
$470,000
Funds obligated
$225,556
Transaction type
Cooperative Agreement
Period
08/15/2025 → 07/31/2027