Intro: Welcome. I’m your host, Jess Wisse. On today’s episode we’ll talking about how something that may surprise you. Here are a few hints: the holidays, online shopping, and parking. Stay tuned to learn more.   JW: If you’re anything like me, I’m sure you’ve been busy preparing for the holidays. This includes wrapping gifts, RSVPing to parties, and online shopping. LOTS of online shopping. But have you ever considered all of the hands who’ve touched your latest shipment before it arrives on your doorstep? PNNL user experience scientist, Lyndsey Franklin thinks about this daily.LF: Maybe I should set out, you know, Gatorade and some snack bars. No, forget giving milk and cookies to Santa. Give Gatorade and snack bars to your poor delivery drivers because they are hustling. It's insane!JW: Researchers at Pacific Northwest National Laboratory are using their expertise in artificial intelligence, machine learning, and app development to ease challenges with urban freight delivery, an experience especially difficult during the holidays.Meet one of the researchers at PNNL working on this. LF: I am a User Experience Research Scientist in the Visual Analytics Group at PNNL. I try to make computers better playmates for people. I kind of take the philosophy that if something goes wrong, it's the computers fault. It wasn't designed well. Or people didn't think about it well, and it's really not the person's fault. Somebody needs to make the machine play better.JW: Lyndsey is working on a project that’s funded by DOE’s Office of Energy Efficiency and Renewable Energy’s Vehicle Technologies Office. The project is led by the University of Washington’s Urban Freight Lab. Lyndsey’s goal: to develop, test, and improve technologies aimed at cutting time spent by delivery drivers at the curb. Think of your average UPS or FedEx delivery driver. Lyndsey’s job is to increase their productivity and reduce the time and fuel spent searching for available parking.LF: What if you could make something like parking in downtown Seattle smarter? The particular problem that they were trying to address was, ‘How do we make that delivery process more fuel efficient in crazy environments like Seattle?’ So, they came to us in two capacities. They were looking for some expertise in the modeling aspect. John Feo here at PNNL is leading up that part of the of the effort. The other thing that was important to them, and very insightful of them, was to realize that this wasn't going to be something they were designing for a typical desktop environment. This this wasn't build a model, have it run on a big heavy machine, and spit out an answer, and give it to drivers. Downtown Seattle and the parking in downtown Seattle is ever-changing and always chaotic. And so, there's this noisy busy environment and you're supposed to be giving information to drivers who aren't sitting at a computer. So, what is that whole experience that the drivers are going to have. What's that going to look like?JW: Finding parking can be a major headache for freight delivery drivers. Especially in cities like Seattle. Restaurants need a constant cycle of fresh produce. Retail stores depend on delivered products to maintain a steady flow of sales. People living in a city’s apartment buildings expect their Amazon purchases delivered on time, without fail. That’s why PNNL is working with the University of Washington to develop an app that helps drivers identify open parking closest to a delivery location. The Urban Freight Lab calls this sweet spot for a delivery the “final 50 feet”—where a delivery driver stops to deliver their freight.LF: So, the focus of the app is trying to help increase awareness for when parking might be available. In the case of newer drivers who maybe are seasonal, they've been added to routes to deliver Christmas packages and things like that. They're not as familiar with the area. They don't really have that internal map in their head of: ‘Well, if I can't