How Traffic Simulation and Digital Twins Improve Urban Mobility
Traffic congestion is a major problem for cities around the world. Leave a big event like a concert or a sports game, and you’ll see a whole lot of it. Fifteen minutes may be how fast it takes to clear the Colosseum in Rome, but that doesn’t solve the problem of the traffic jams afterward.
Enter simulation models, or “digital twins,” which are virtual replicas of real-world transportation networks. These models help traffic experts in finding ways to ease congestion, reduce accidents, and improve overall traffic experience.
Google Research teamed up with the Seattle Department of Transportation (SDOT) to create and test a traffic guidance plan using simulation models. The aim was to help people leaving stadiums after events get out of the area faster and safer. The plan successfully reduced average trip travel times by 7 minutes during large events.
The team also developed routing policies and evaluated them using the simulation model. For example, they tried routing northbound/southbound traffic from the nearest ramps to further highway ramps to shorten the wait times.
Based on the simulation results, traffic management strategies were implemented during large events. These policies led to an average of 7 minutes of travel time savings per vehicle, rerouting 30% of traffic.
The work highlights the potential of simulations to model, identify, and quantify the effect of proposed traffic guidance policies, which can ultimately lead to better spatial distribution of traffic. The hope is that by investing in more scalable techniques, simulation models can be brought to more cities and use cases around the world.
In conclusion, traffic simulation and digital twins offer a promising solution to urban mobility challenges and represent an innovative way to help cities improve traffic flow before, during, and after large events.