The fight against COVID-19 has without a doubt accelerated the digital transformation on many fronts. Amid wildly varying degrees of disruption and shut-down across the country, Siemens Mobility has continued to innovate to ensure that when we do return to day-to-day predictability and continuity, we have a more efficient approach to traffic and ground transportation. That’s why Mobility has created an app called Eventflow.
This app scrapes tons of data off the web—data about what is happening in your city and region—and uses AI and machine learning to predict where changes in traffic patterns will occur as a result of events. This lets municipal traffic managers know in advance where bottlenecks could occur and do something about them, such as change the timing of traffic lights, but it can also help transit managers enable social distancing by provisioning more bus services where they know demand exists.
The app helps citizens know what parts of a city or highway system to avoid ahead of time (think convention-center traffic or construction zones). Overall, Eventflow will enable more efficient, more practical traffic and transit management planning so that municipalities don’t have to invest in event-specific consulting—all while focusing on essential social distancing to prevent the spread of COVID-19.
My section of Siemens Mobility focuses on creating new products and services using expertise in AI and machine learning for traffic and transit management. We take technologies that have worked well for other industries and tailor those to the transportation sector. Our customers—often state, municipal, and city governments—are sometimes constrained by changes in technology and have significant responsibilities to taxpayers; they have to put solutions in place that will work well and easily and fit their budget. An app fits that bill.
Siemens Mobility customers tend to have a lot of data, and that’s a big benefit because the solutions to various problems often can be found in that data through the application of AI and machine learning. And the applicability of Eventflow can spread across multitudes of traffic and transit operational scenarios.
Consider the future taxis. Eventually these will be driverless vehicles. Traffic managers will want to position these vehicles in places where events are scheduled, or if momentary changes in public transportation occur. The ultimate goal of Eventflow is efficiency—for both piloted and driverless vehicles.
Beyond that, the municipalities that use Eventflow can develop a bank of predictive conditions that they then can provide as a service, offering the information to private transportation providers and other transit systems to proactively plan and to minimize disruption. Such data collection over months and years—including impacts of weather, holiday traffic, and road conditions—can even be a part of plans to network infrastructure and build up the local Internet of Things (IoT).
Ultimately, Eventflow is about time—yours. Products, “things,” can be repaired and brought back online, but time lost is gone. So the time you save, having not wasted it stuck in traffic, has a direct, often immediate, impact on the quality of your life. If you’re still late to meetings, you won’t be able to blame the traffic.
Published: December 16, 2020