Digital Twins Take the Wheel: Google & Seattle Predict Traffic Flow After the Big Game

Leveraging digital twin technology, Google Research has collaborated with the Seattle Department of Transportation to simulate real-world traffic flows. This initiative aims to address the challenges of traffic dispersion following large-scale events involving numerous participants.

Through the use of the open-source simulation software SUMO (Simulation of Urban Mobility), they recreate the traffic conditions around Seattle’s sports stadiums at specific times. This is achieved by incorporating Google Maps data to define road traffic flow, speed limits, and traffic signals, thus simulating the traffic conditions of particular periods.

Furthermore, Google utilizes anonymized data for statistical analysis, recording the vehicular flow within the area. This approach enables a more accurate representation of real-world traffic conditions in the simulation environment. By doing so, they can analyze potential congestion on different roads and develop feasible solutions.

Currently, the Seattle Police Department provides information on the most congested routes requiring improvement under specific scenarios. Google researchers then analyze the simulation results to propose effective methods for swift traffic dispersion. These methods include opening closer gateways for vehicular egress and utilizing high-capacity lanes and alternative routes to facilitate quicker departure from congested areas.

Additionally, Google conducts simulations considering various traffic conditions, event timings, and crowd sizes to assess the time vehicles need to exit congested areas and reach their destinations. Ultimately, the simulation results guide approximately 30% of the traffic through specific routes for dispersion, averagely reducing vehicular congestion time by seven minutes. This approach also utilizes less frequently used roads to help alleviate traffic congestion.