Dick Walker, a manager in Metro's Research Center, is retiring after 43 years of public service, the last 39 of which have been at Metro. He is believed to be the longest-serving employee working at the Metro Regional Center – one of the first 100 people hired by the regional government.
A native of Montana, Walker came to Oregon to run transportation modeling of greater Portland for ODOT in Salem. But when a new government – Metro's predecessor, the Columbia Regional Association of Governments – wanted to do its own modeling with a decreased focus on cars, Walker moved to Portland and hasn't left.
This Q&A has been edited for brevity.
So, what did transportation modeling look like 43 years ago?
I guess that's what's fun about being around a long time, seeing the technologies and the type of project. When I first started, these were back in the days where there were keypunch cards. There was none of this interactive graphic stuff obviously.
What we had to do was have abstract representations of our street system, and so when we wanted to make our travel forecast we'd submit a request to do that and we'd get a printout, and by hand, you'd have a partner go through and say, "OK, from that number to that number." The whole thing was very manually intensive in those days.
Even though our models were so much simpler, they would take like all night to run, at a cost of $2,000, $3,000. It was a big-time expense and you had to really be careful what you were doing back then.
What we are doing is so much more interactive. You can see the whole thing on your screen – you can see cars moving, you can see cars queuing.
And furthermore, we run it all on our own desktops so essentially you have to pay your planning software cost but there's no computer usage fee per se.
It's come a long way.
How did you wind up at Metro?
We wanted new models. The models being used by ODOT were all about the car. It was right about that time is when this region did not want its future to be all about the car. We wanted to think about transit and those things. So you needed a new set of models to be able to do that.
Keith Lawton was hired to lead that effort and he had to build a team to help him do so and that's when I was hired from ODOT.
It was a big effort. We started with a big household survey to understand the travel patterns in this region. We then used that survey to build models, and said, at that time, it wasn't just focused on the car, we really wanted models that were going to do equally a good job on transit, because that was the time that we were making decisions about light rail – this is right before the big switch of funds between the Mt. Hood Freeway onto the light rail.
That's the timeframe we're looking at and that's the charge we were faced with.
What's been the most significant change in forecasting?
The thought process in the 70s and early 80s, it was all about the car. But that's not good enough. This region wanted more. So the focus was on transit. We turned the page and built our expertise up with regard to be able to do the transit forecasting as well. We added to our portfolio and we got very good at it. But that's not good enough. Time goes on, bikes, pedestrians, active transportation, so the page turns, and that's kind of where we are now where we're building tools and expertise to do just as good of a job in those areas as we are with auto and transit.
As you look to the future, that page is going to turn again. We're talking about health, we're talking about equity in the transportation system. These are getting to be harder and harder questions to answer, but the tools are getting to be more complex and sophisticated and detailed to get us to be able to drill down to that level, so frankly that's one of the things that's kept me in the business for so long. You wonder how could one person stay in a job that long, but the job evolves, and the questions are changing, and as I mentioned, the tools have evolved with that.
The ability to answer so many more questions is just evolving. It used to be, how many cars were on the Interstate Bridge, for example.
Now you can say how many cars are on the Interstate Bridge, how many are in this income range, that income range, how many are single occupancy, how many are carpools, how many are going to work, how many are shopping, how many are – it's getting so much more disaggregate and we're basically next year going to begin the evolution, into our next type of modeling which is the activity based model.
You can, based on census information, survey information, you can make pretty good estimates of what kind of decisions these people are making based on XYZ. You can imagine, once you get that information, you can really drill down to see how individual projects affect Joe vs. Sally vs. Mary and that's getting us closer and closer to really being more and more useful in this whole equity analysis.
What's been the biggest challenge in transportation modeling in your time working on it?
I would say the biggest challenge, and I can give you a really good example, is in the ideal world, you want to anticipate the coming issues. You want to have that tool ready and poised when the questions emerge. That was easy to do in the 70s, 80s and 90s. We have a very sophisticated region here. They ask the tough questions and they're informed and they are thinking, so these questions are coming faster than technology can really address them.
This whole notion of automated vehicles. You read all about it in the science pages now, it's coming, but you look at the academic research as to how that will impact the travel, you can read, here's one opinion, here's one opinion, here's one opinion, it's all over the board. We don't have any empirical evidence to concretely understand how it's going to impact travel. But, rightfully so, our decisionmakers are asking tough questions about that.
So the challenge is to keep on top of being able to be useful and relevant in addressing those kinds of things. So what I think it comes back to is the whole notion of, we need to be strategic. Here's a set of assumptions that automated vehicles might take us, and this is what the future might look like.
Why retire now?
I think some of those come into play, some are personal, some are maybe on the professional side as with everyone. From a personal side, I think it's just time. I'm going to be 66. You have emerging talent. It's time for them to have their turn to step up, be the leaders for the next thing. As I said, you can feel the page turning on these questions. My era was all about cars, transit and AT. We made really great strides. The page is turning and now it's about digging into that even further.
There's a whole new set of questions and it takes a lot to keep up with all the science nationally behind those things, what are the correct ways to address them.
My wife and I like to travel, we certainly want to have time for that. I have kids who live here in town. I have grandkids.
What is your advice to the next generation?
I ride the streetcar back and forth. Inside the streetcar there's a little poster that I've seen over the last 3-4 months, it's a quote from OHSU, and the statement is this: "If you know the answer, ask harder questions."
Every time I see that I just think how appropriate that is for the kind of work we do here. As we find more and more ways that we want to shape our region, we find more and more things that are relevant that need to be addressed, issues that need to be understood. So it's not good enough just to know how to forecast cars. It's not good enough to just know how to forecast transit. There's all these other issues that come into play. That's what's motivated me in my career and why I've stuck around so long.
Those questions just kept on coming. We've mastered this, what's the next big question and we went onto it. I would hope the next generation of leaders, the people here today, can espouse that and I hope they're challenged by asking those harder questions.