Seminar on Computational Learning and Adaptation




Automobile Traffic Management through Intelligent Lane Selection:
A Distributed, Machine Learning Approach


David Moriarty
ISI
moriarty@isi.edu



In this talk, I will present a novel approach to traffic management through coordinating driver behaviors. Current traffic management systems do not consider lane organization of the cars and only affect traffic flows by controlling traffic signals or ramp meters. However, drivers can increase traffic throughput and more consistently maintain desired speeds by selecting lanes intelligently. I pose the problem of intelligent lane selection as a challenging and potentially rewarding problem for artificial intelligence, and I propose a methodology that uses supervised and reinforcement learning to form distributed control strategies. Initial results are quite promising and demonstrate that intelligent lane selection can achieve higher traffic throughput, maximize desired speeds, and reduce the total number of lane changes.




Date: Thurs., January 22; Time: 4:15-5:30PM; Place: Gates 100


The goal of this seminar is to increase communication among local researchers with interests in computational approaches to learning and adaptation. If you would like to be added to (or removed from) the mailing list, or if you are interested in giving a talk in the seminar, please send email to iba@isle.org.


Return to seminar schedule.