Achievement

Trainees Daniel Ayala and Bo Xu of Computer Science worked with faculty members from Computer Science and Civil and Materials Engineering on the problem of spatio-temporal matching where agents compete for spatio-temporal resources. Examples could include drivers who compete for parking spaces; taxi-cabs that compete for customers. They developed algorithms that guide an agent to the most promising resource. They also developed economic models so that the rational behavior of the agents automatically leads to minimized costs system-wide. Out-performance of naive method in which a driver always goes to the closest parking space. In some cases, the algorithms save 47% of driving distance. In a city like Chicago, this yields a reduction of over 3.9 million gallons of gasoline and over 60,000 tons of CO2 emissions per year. Invention was disclosed to UIC, which filed for provisional patent. Commercialization efforts are underway.