Enabling Technology

In early 2016, two separate events sparked excitement in the fields of autonomous vehicles and artificial intelligence. NVidia announced that their camera-based vehicle, driven by their Drive-PX computer, was trained to drive, using no prior knowledge and with just 72 hours of training video data; and AlphaGo, a computer program designed to play the game Go, defeated Lee Sedol, one of the world’s top-ranked players. These two events highlight the potential of artificial intelligence, as an alternative to the current focus on expensive sensors like Lidars. In both cases, the key enablers included rich training data sets, a learning algorithm, and a test platform.

Research Focusing on Enabling Technology


CAV Developed Vehicles as Real-Time Sensors for Assessing Greenhouse Gases
Principal Investigator:
Krishnakumar Nedunuri & Ramanitharan Kandiah
Research Thrusts: Enabling TechnologyHuman FactorsModeling & Implementation
Real‐Time Distributed Optimization of Traffic Signal Timing
Principal Investigator:
Yafeng Yin, Siqian Shen, & Yiheng Feng
Research Thrusts: Control & OperationsEnabling TechnologyModeling & Implementation
Reliable V2V Communication Networks: Applications in Fuel-Efficient Platooning
Principal Investigator:
Sridhar Lakshmanan & Paul Richardson
Research Thrusts: Enabling Technology