Communications of the ACM
Complexity Scientist Beats Traffic Jams Through Adaptation
Carlos Gershenson ran simulations that found self-organizing traffic lights could reduce emissions and cut travel times by 25%.
Credit: Meghan Dhaliwal / Quanta Magazine
The traffic jams of Mexico City are the kind of problem that for the past two decades has been a favorite of Carlos Gershenson, a computer scientist at the National Autonomous University of Mexico.
To solve a complex problem, Gershenson believes, scientists need to let go of traditional methods and find novel ways to study ever-changing challenges. "Science and engineering have assumed that the world is predictable,," he wrote while he was a visiting professor at the Massachusetts Institute of Technology and Northeastern University in 2016. "But the study of complex systems has shown that this assumption is misguided."
By using computer simulations that specialize in adaptation, Gershenson uses self-organization as a tool to improve urban mobility. Although most of the transport-system solutions he has proposed to various cities have encountered political and bureaucratic obstacles, his ideas were implemented successfully in Mexico City's metro system in 2016.
"Carlos' work has significantly advanced the state of the art of our understanding of self-organized traffic flows and their implications for real world control and optimization," says Yaneer Bar-Yam, a professor of physics at MIT who supervised a postdoctoral fellowship with Gershenson in 2007-2008. "[He] has reframed questions, which is the most important impact that one can have."
From Quanta Magazine
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