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Electric Scooters and a Case for Improved Collaboration

Priscilla Nagashima Boyd, Senior Manager, Data Analytics

Recently, I had the honor to present at the National Conference of State Legislatures Smart Communities Summit about transport innovation and data-driven initiatives.

I live in Austin, Texas, where we have roughly 3,000 electric scooters in the city. They are a great option for short trips, require less parking space, are cost-effective and better for the environment. But there are downsides, too, including accidents involving pedestrians and scooters abandoned all over the city. It’s a careful balancing act for cities to adopt new technologies without creating policies so stringent they deter innovation.

Prior to moving to Austin, I spent 10 years working in the UK, where I worked very closely with governments to introduce more R&D. This collaboration enabled the acceleration of new ideas and technologies by the private sector. For government, it allowed private-sector investment in technologies that could reduce road congestion while improving air quality and safety.

When I returned to the U.S., though, I learned that most cities lack the bandwidth to explore new ideas with the private sector, either because of rigid procurement rules or due to lack of resources.

Now think about the scooter example. If those scooter companies could easily engage with the public sector to share their plans and ideate together, local government could influence developments, anticipate disruptions sooner and ensure innovations have a positive impact on citizens’ lives.

At Siemens Intelligent Traffic Systems Digital Lab in Austin, we focus on innovation using data science, artificial intelligence and machine learning. Cities already have systems and infrastructure in place which generate a lot of data, and we look for opportunities to use that data to solve practical problems.

For example, Lisbon, Portugal now has a very successful bike sharing scheme that’s been in operation for over eight years. It’s a mix of electric and conventional bikes, dock-based and dock less. For the dock-based bikes, the City sends vans throughout the day to move bikes around the city – particularly to higher trafficked areas – to make it easier for folks to find bikes when they need them.

However, every so often they couldn’t predict demand. Maybe there was a change in weather or a special event in the city – this meant that people would sometimes get to a dock and find no bicycles available. The result was use of shared ride services that exacerbated the traffic and frustration from citizens who relied on this mode of transportation.

To solve the issue, our ITS Digital Lab built an application that combined data from historic bike trips, historic weather and events to provide an “engine” that could predict demand for scooters up to 4 hours in advance. With the ability to predict demand, the City could plan their operations more efficiently to ensure the docks had bikes when most needed. This helped increase revenue as well.

We did this work in an iterative and agile way, using design thinking processes, with the City at the core of what we do without having to enter complex procurement agreements in advance. Neither us nor the City knew whether we could solve the problem before we started – but both parties put effort into it, and we got to a solution that ultimately benefited both sides.

The field of artificial intelligence is evolving quickly. The beauty of what we are doing at the ITS Digital Lab is that we can bring data-driven innovation through the outputs of projects that are evolving the field of AI and machine learning every single day. We take specific problems, analyze the data available and then bring our data science expertise to address the problems.

It’s now time to bring emerging technology to the physical world, the critical infrastructure cities rely on every day. Let’s take the amazing research that academia has done in the U.S. and use it to solve practical problems that can help our citizens.

And that’s what Siemens is doing with our ITS Digital Lab: helping cities use AI to improve the quality and safety of transportation. The U.S. has enormous potential to lead data-driven innovation. With new partnerships between cities and technology companies – and by modernizing procurement rules to really speed things up – we can start advancing the projects and solutions that growing cities need for the future.

#siemensusa #siemensmobility #NCSL #mydigitalcity

This article was originally published on Siemens Stories