“Usually in practice, when you want to time traffic lights, traditionally it’s been done in a local way,” Osorio says. “You define one intersection, or maybe a set of intersections along an arterial, and you fine-tune or optimize the traffic lights there. What is less done, and is more difficult to do, is when you look at a broader scale, in this case the city of Lausanne, and you want to change signal times at intersections distributed across the entire city, with the objective of trying to improve conditions across the entire city.”
Such an expansive aim triggers complications, such as the ripple effect that a change at one intersection can produce across the surrounding area, or changes in driver behavior following changes in traffic-light patterns: For example, if wait times on a particular route increase, drivers may seek alternative routes that feature fewer red lights.
The new optimization process developed by Osorio and graduate student Linsen Chong can time led traffic lights in large urban areas while accounting for the complex and diverse reactions of individual drivers. Their approach uses high-resolution traffic simulators that describe, in detail, the behavior of drivers in response to changes in travel conditions.
In detailed simulations of Lausanne’s traffic, they found that the timings produced by their approach reduced the average travel time for commuters by 22 percent, compared with timings generated by commercial traffic-light timing software.
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