C. Gershenson (IIMAS, UNAM, Mexico)
Thursday 2017-11-02 12.00 – 12.30
Seminar room T5, T-building
Improving Urban Mobility with Self-organization
Urban mobility is non-stationary, i.e. the precise number of vehicles or passengers is changing constantly, and with a limited predictability. Transportation systems will be more effective if they can adapt at the same timescales at which the demand changes. Self-organization offers one way of implementing this desired adaptability. I will present two examples: self-organizing traffic lights which achieve quasi-optimal performance and self-organizing public transportation systems which achieve supraoptimal performance.
Carlos Gershenson is a tenured, full time research professor at the computer science department of the Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas at the Universidad Nacional Autónoma de México (UNAM), where he leads the Self-organizing Systems Lab. He is also associated with the Centro de Ciencias de la Complejidad at UNAM, MIT’s Senseable City Lab, and ITMO University. He has a wide variety of academic interests, including complex systems, self- organization, urbanism, artificial life, evolution, cognition, artificial societies, and philosophy. More info at http://turing.iimas.unam.mx/~cgg/