BusGraphs

Last month, I used arf’s network modification capabilities to develop a small restructure of King County Metro’s transit network in Seattle. This change to routes 3 and 11 produced an access gain, while reducing the overall amount of service time expended. To explore ways to reinvest the service time, I expanded arf’s route modification capabilities to support frequency changes and adding new stops.

With these capabilities, I created two changes that branched off of the baseline restructure of the previous post. The first proposal ups route 11’s frequency to every 15 minutes from 6 AM to 7 PM, allowing it to meet Seattle’s definition of frequent transit service. The second maintains the existing frequency, but extends route 11 to the Eastlake neighborhood, using streets that have not had transit service for 10 years. A third change combines the two. Subsequent sections of this post will address each change.

A useful access analysis tool should allow analyzing hypothetical transit networks, not just existing ones. As such, these tools can modify transit routes and their schedules.

Consider Conveyal’s scenario editor, as shown in this demo,

or this clip demonstrating Remix’s route editing functionality.

While these tools accept modifications with a point-and-click interface¹, I take a different approach. My previous access analysis tools accepted a modifications file in a text format that is both machine- and human-readable². In March, I added basic network modification functionality to arf, using an updated version of this approach.

As a transit rider in Seattle, ten years ago was an exciting time. The expansion of the Link light rail to Capitol Hill and the University of Washington portended significant changes to King County Metro’s bus network. This was coinciding with my transition from a passive rider to someone interested in the design of public transit networks.

Back then, I began to appreciate access maps as useful for making comparisons when public transit networks are in flux. These same maps can also look backward to see how access has changed over time. I recently built three styles of sector-centered comparative access maps that use arf’s outputs, and will demonstrate them by comparing Seattle’s present day transit service to that which existed just before the University Link extension opened.

The first map uses a diverging color scheme to show the change in the number of times of day one can reach destinations, within a 30-minute time budget, from an origin at the cursor. The origin point can be locked in place by clicking, and released by clicking again.

Last August, I presented a map that could quickly show sector-centered access. That is, when considering a single start point and a fixed time budget, how often can one reach all other points within a region, when starting at that point at every minute of the day. This prototype map used reachability data produced by an early version of arf and clumsily combined it with spatial information extracted from running the Access Analyzer. After working on disentangling arf from the Access Analyzer late last year, and focusing on arf’s performance in January, I wanted to spend February expanding its visualization capacities beyond the region-wide access maps shown in the last two posts. The first product of this work expands on the sector-centered approach seen in the August prototype.

I’ve spend much of January improving arf’s performance. The 30-minute time budget access map for Washington state that used to take around 70 minutes now takes approximately 40 on my M1 2020 MacBook Air. A map of Seattle with the same parameters takes around eight. With the performance enhancements in place, I wanted to subject arf to a new trial: creating a 30 minute unweighted access map of New York City.

Arf is a new tool for generating unweighted access analyses, like the ones seen in this blog. Its outputs have the same 80 meter spatial resolution as those generated with my previous access analysis tool, the BusGraphs Access Analyzer, but arf can assess areas of sizes on the order of US states, and runs on conventional personal computers rather than cloud computing infrastructure. This 30-minute transit and walking access map of Washington state took around 70 minutes to generate on a 2020 M1 MacBook Air laptop.

This is a proposal to use Interstate 5 between Northeast Northgate Way and the Spokane Street Viaduct as the “second downtown tunnel” planned for Seattle in the Sound Transit 3 project (ST3). Between these two points, the entire highway would be converted into a transit corridor. This would require a feat of political courage and interagency cooperation, but would provide the exceptional public transit network that ST3 promised, while eliminating costly and disruptive portions of the project.

In Human Transit, Jarrett Walker describes his consulting work as being a domain expert who asks communities questions about the transit networks that they want to build. The questions present two endpoints to a spectrum. Each end has advantages and disadvantages. The position a transit agency takes depends on what the community that it serves values; there are no wrong answers. Walker then can help design a transit network conforming to these positions. There are four overarching questions.

• Ridership or coverage?
• Connections or direct service?
• Peak-first or base-first?
• Exclusive or compromised right of way?

I propose a fifth question: cooperation or insurgence?

I’ve been revisiting Jarrett Walker’s book Human Transit¹. Reading it crystalized the disjointed thoughts that I had as a transit rider into opinions on how public transit networks should operate. It is one of the most important books I have read, and I suspect that is true for many people with a stake in public transit.

I’m revisiting it by way of processing the response to my cost-neutral redesign of King County Metro’s network, which overlaid Seattle with 24/7 frequent service . It appeared in Seattle Transit Blog, where comments on it were more uniformly negative than I anticipated. These commenters are not fools. They recognized that widespread frequent overnight service would involve tradeoffs, like more crowding at rush hours, and fewer one-seat rides to population and activity centers like downtown and the University District. They insisted that riders would not favor this exchange.

A network-wide access map colors sectors, uniform areas of a region, according to an access score. For an unweighted access measurement, the score corresponds to how often a rider originating in that sector can reach others throughout the region. But it doesn’t allow a transit rider with an interest in a specific sector to see exactly which destinations are within reach. The same data can generate a sector-centered access map that reveals this, so my maps allow transitioning between the network-wide and sector-centered modes. Unfortunately, it’s slow to the point of being unusable.