Good Traffic Estimates Today Can Create Better Roads for Tomorrow

Carnegie Mellon University's Zhen (Sean) Qian, an assistant professor of civil and environmental engineering , is driving to make a smoother road for urban planners by creating more accurate ways to estimate traffic conditions. The ability to estimate traffic - especially in urban environments - is important as it can allow for efficient, real-time traffic management, optimizing travel for emergency responders or the rerouting of traffic to adjust for delays. The data and estimates gathered also enable engineers like Qian to understand how the infrastructure can be better utilized, such as changing road markings or the timing of traffic lights. Qian said in the past, the sheer number of roads and intersections in an urban environment had been too large to create accurate estimations, and it would be infeasible to place a sensor on every road and intersection. His approach, which uses a link queue model, takes advantage of large amounts of data from numerous pre-existing sources - smartphones, GPS devices, probe vehicles - in conjunction with strategically positioned sensors, and performs an efficient computation to output a reasonably good estimate. Within a small portion of the Washington, D.C., area, Qian combined multiple data sets with two speed detectors to accurately estimate travel speed to an acceptable error rate within 8.5 percent. "In the longterm, we want to know on average, throughout the entire year, and over multiple years, how traffic increases," Qian said.