This won't amaze readers in places like San Francisco or Boston, which have had Nextbus.com for years. But it's an important step for Australia. Realtime locations of Sydney's buses, via a new app by Flink Labs of Melbourne.
Not sure what the colours mean. They need to be colour-coded for inbound vs outbound, which otherwise can't be distinguished.
Thanks to Chris Loader, who blogs about Australian public transport at Charting Transport, for the tip.
Can animation help people understand their transit options? The Rotherham Metro Borough Council in the UK has done some simple "map movies" that highlight the paths followed by buses and trains. Here's a still:
Watch the actual animation here.
As they stand, they're limited in usefulness, as the icons move along the routes with no indication of frequency. They certainly do advertise complexity, which is accurate; this looks like a very complicated network.
But it's easy to imagine taking this to the next step, showing by animation the scheduled paths of all the services in a transit system. This would be especially helpful in helping citizens understand pulse systems, where the integrated scheduling pattern is an essential part of how the network gets you where your going. Now that I think of it, I'm pretty sure this has been done, but I've never seen it on a public information website, which is the obvious next step.
The Frequent Network mapping campaign continues. Here's a Cincinnati map by Nathan Wessel, which can be compared to the agency's full map here. It reveals an intensely radial system, with not many chances to connect other than downtown. (Click pic to enlarge, or download sharper PNG file here.
Matt Lerner of WalkScore.com and I recently exchanged emails about WalkScore’s “Transit Score” product, which provides a two-digit score supposedly capturing the usefulness of transit at any address in the USA. It’s designed on analogy to the successful (if still controversial) Walk Score, a similar tool for summarizing how friendly a place is to walking. For example, 300 Turk Street, San Francisco is scored 100 (perfect) on both Walk Score and Transit Score.
Toward another extreme, here’s 7000 Lake Mead Blvd in the far east of Las Vegas. Walkscore is 52, Transit Score is 33.
Tools like these have huge potential relevance to the real estate industry, and more broadly to anyone who makes locational decisions about anything. To the extent that we encourage people who value transit to locate where good transit is viable, everyone wins.
Earlier, Matt’s team had created a “transit travel time tool” which can be used to show you the actual area you can get to in a specified amount of time. I used this tool as the core of my definition of mobility, in one of this blog’s earliest posts.
So which is more useful, the simple two-digit Transit Score, or an actual map of where you can get to in a given time?
Here’s what I wrote to Matt:
Dear Matt,
About a year ago I mentioned your transit [travel time] tool as a useful way to visualize mobility …
The first draft of the book I’m writing … praises this WalkScore tool in some detail, as a way for people to understand the degree of freedom that transit will offer them. I think it may be a crucial tool for helping people see beyond modal fetishes to understand how transit actually works and how to determine if transit can actually get you where you’re going.
… Transit Score is useless to me because it encodes an intrinsic bias toward rail modes, as though rail is intrinsically faster, which is utterly misleading in a world of 6.5 mph streetcars and 60 mph busways. [I’m referring to the Transit Score methodology’s use of a “mode weight” defined as “(heavy/light rail is weighted 2X, ferry/cable car/other are 1.5X, and bus is 1X)”. Note that unlike the travel time tool, Transit Score lacks a way to capture how far you can get how fast, so it uses mode as a proxy for speed, fatally in my view.]
In short, whereas the earlier tool presented raw information in a compelling way that the user could use for her own purposes, Transit Score contains value judgments (“we know you’d rather ride a slow streetcar than an express bus”) which the user may not share, and thus may be an obstacle to her ability to make transit meet her needs.
So I guess I will praise mapnificent.net instead.
This issue sits at the very foundation of my current book, so as an admirer of your work, I’d like a better understanding of why you abandoned the original accessbility tool. Was it a matter of the processing required to do what’s basically a massive search of trip planners? I can see that Transit Score is a much faster calculation, but wonder if that was the key issue.
All the best for ’11,
Jarrett Walker
Matt replied:
HI Jarrett,
Good to hear from you.
You’re right that we are promoting Transit Score over Transit Time Maps — but we haven’t abandoned the transit time maps. We are working on new ways to use them and they are still available here: http://www.walkscore.com/transit-map.php).
Here’s why we’ve been promoting Transit Score more heavily. Our mission is to promote walkable/transit friendly neighborhoods and we think the best way to do this is to have Walk Score / Transit Score on real estate listings.
As we developed Transit Score we looked at a few methods of calculating a Transit Score. The two finalists were our current method (detailed here) and a method where we summed the Walk Score under the area of the transit shed in our Transit Time Maps. In practice, the scores were very similar between the two methods so we chose the current method which is much easier to scale (we show millions of scores per day).
We want to boil down transit access into a score so that it can appear on real estate listings and people can compare locations. ZipRealty.com has added our Transit Score to millions of listings and we have some more partners on the way.
We did not see a lot of consumer/partner interest in the transit time maps — which is unfortunate because of course I love them. One scenario I’m hoping to promote with our Transit Time Maps (we just need a partner) is to allow people on real estate sites to search by transit time. E.G. find me an apartment within 30 minutes of work on transit. I’d also like to integrate the transit sheds into the standard Walk Score experience.
I like the simplification Mapnificent made which was to not include walking time in their transit sheds — this makes it much easier to compute.
So to sum up, I like your suggestion of avoiding any mode weight value judgments — it just turns out that in practice our current method was very similar and easier to scale. Anyway, would love to hear your thoughts on this.
Also, we’re launching a beta of “Street Smart” Walk Score later this month and we’d love your feedback on that too.
Happy New Year!
Matt
To which I replied:
Matt
Thanks! … Suppose, hypothetically, that you had the processing power and datasets to run a purely mobility-based Transit Score. Let’s call it a Transit Mobility Score. The algorithm would be something like: Identify the area reachable in 30 minutes on transit from the selected point (I choose this because it seems to have a long history as an acceptable commute time). Then, grab the MPO’s database of population and jobs by small zone and calculate the percentage of the region’s jobs and population that are in that 30 minute band.
That also gives you a 2-digit number, but now it’s a fact rather than a score. You’re saying: “If you locate here, you’ll have convenient transit access to __% of the region’s activity.” And that strikes me as something that a realtor could value, understand and explain. How far are you (or someone) from being able to do that kind of algorithm? Obviously you’d need to have the MPO on your side, so start with somewhere like Portland where they generally are.
Frankly, you’d probably want to do two such scores, one based on your mobility at 8:00 AM and another for your all-day mobility — say, at 1:00 PM. But I think a realtor could make sense of those too. Everyone understands that transit in the peak is different from midday, and that both matter. Suburban areas, especially those under the influence of commuter rail and commuter express buses would show quite a difference between the two.
I think this could be huge. Because the output is a fact, not a judgment. …
All the best, Jarrett
Matt replies that this “sounds like an awesome planning tool and one we could potentially pursue if we had a grant or something to fund it.”
I still think this could be huge. What if everyone making a locational decision could go to something like the WalkScore travel time tool or Mapnificent and see a map of where they’ll be able to get to in 30 mintues on transit? It would finally make our mobility visible.
And if we could measure our mobility so accurately, for so many hypothetical cases, we just might value actual mobility more, and be less distracted by unreliable symbols of mobility — like, say, whether there are rails in the street. Technophiles shouldn’t be too alarmed; many people will still have modal preferences. But meanwhile, those of us who just want mobility would be able to measure it, fast, for anywhere that we might be locating something, including our homes.
The populist frequent-network mapping continues. Here's very clear frequent network map for Seattle, showing where you can get to if you don't like waiting. It's by Oran Viriyincy via Seattle Transit Blog. He discusses his process here.
If you want to understand how transit works (and sometimes doesn't) in Seattle, you need a map like this on your wall.
Early in my career, I did a number of network designs for free-standing small cities in the American West. These cities, say populations of 30,000-100,000, tend to have a similar set of problems and opportunities, and could probably benefit from a little more theoretical focus. The same issues arise in most of these cities across North America, Australia, and New Zealand, including: Continue Reading →
A reader who works for a North American transit professional organization writes:
Often transit centers only provide access to one provider and exclude others, or only provide access to local providers but not to regional providers. That silo system carries over to the information that transit agencies manage or make available to their customers in most cases. Do you have some good examples where services and customer information is more regional ie all the options in the region whether public or private.
When transit services are running every 30 minutes or worse, you can’t assume they connect with each other just because they cross on the map. Schedules need to be coordinated to make connections at low frequencies possible. The only technique that does this comprehensively is called a pulse or timed transfer.
A pulse is a regularly scheduled event, usually happening at the same time each hour, in which transit vehicles from a range of routes — usually running every 30 or 60 minutes — are scheduled to all meet together. A group of hourly local routes, for example, might all come to the pulse point between :22 and :25 after the hour and leave at :30. That way, nobody has to wait more than 8 minutes for a connection even though the services in question are hourly.
Often, pulses are organized around a main transit line, such as a trunk bus or rail line that takes you to a nearby larger city. In these cases, the main line vehicle usually doesn’t dwell as the local buses do, since it’s the most crowded service and hence the most speed-sensitive. Instead, the locals arrive a few minutes before the trunk passes through, and leave a couple of minutes after.
Pulses are the only way to provide connection wait times that are much, much better than the frequency of the services involved. A pure pulse is also equally convenient for connections between any pair of lines, and thus for travel in any direction.
For this reason they are used almost universally, in North America, in small-city networks where frequencies are low and often also in suburban areas of large cities. If you’re in a North American suburb or small city and see a large number of buses hanging out together on a street corner, you’re probably watching a pulse.
I was introduced to pulse scheduling in Portland at a tender age. I was a teenage transit geek then an undergraduate working part time at TriMet, the transit agency. This happened to be the period (1979-85) when the lattice of suburban pulse networks was being constructed.
We spent a lot of time thinking about how the pulses interact with each other. For example, if you have a pulse of buses at Beaverton Transit Center at :05 and :35 past the hour, and one route goes from Beaverton to Sunset Transit Center in 12-14 minutes, how do you schedule the Sunset Transit Center pulse? Do you set it at :20 and :40, so that this connecting route can serve both pulses but with just a few minutes to spare? When this route is late, a lot of connections will be missed and a lot of people stranded. Or do we just set the Sunset pulse at :05 and :35, so that the bus linking the two transit centers has lots of spare time but now has too much time to kill and will tend to arrive inconveniently early for one pulse or the other. Or do we just accept that this line isn’t going to hit one or the other of the pulses precisely?
In lattices of multiple pulses, the travel times between the pulse points become critical. In this example, if Lines 1 and 2 have different travel times between the two pulse points, the timing may not work well for both of them. Good network design thinks about this problem as routes are being designed.
To do pulse scheduling, we have to plan the pulse schedule as we’re designing the network. In the two-pulse problem I outlined above, we will think hard about the line connecting the two pulses and ask if we can either make it a little shorter (so that it will get there more reliably in 15 minutes) or a little longer (so that it will get there in 30 minutes without so much time to spare). I have designed some large networks with multiple pulse points, all designed to work harmoniously. To do that, I’ve always designed lines between pulse points with the specific goal of making them a certain length.
Pulse scheduling requires an intimate two-way conversation between the planning and scheduling tasks, but not all public transit authorities are not set up to have this conversation. Sometimes, planning and scheduling are too far apart organizationally and become structurally incapable of noticing and exploiting pulse opportunities. In other cases, pulses may simply not be the prevailing habit; there may be nobody around who is in the position to suggest them.
The organizational challenge presented by pulsing is, to me, a positive feature of the concept. Better integration of planning, scheduling, and operations management has many benefits, and if the pulse challenge helps motivate an agency to get there, so much the better.
But pulse scheduling does have some practical limitations. In particular, it struggles in any environment where the running times are prone to vary a great deal.
Pulses are about managing a low-frequency network, so they aren’t generally needed in inner cities where frequencies are every 15 minutes or better. Pulses are almost universal in small-city design in North America, because most such cities have little traffic congestion and can therefore run a pulse reliably. The best big-city agencies also do some kind of pulse late at night, when their services are very infrequent.
But in the suburban areas of big cities, running times vary due to traffic congestion and pulse operations struggle. I suspect that the difficulty of guaranteeing pulses in these settings is the main reason that big suburban agencies are reluctant to advertise their pulsing too much. Small-city agencies, which don’t deal with such severe congestion, are more likely to emphasise that at the heart of their network, they have a pulse.
A lattice of interconnected pulse points, all beating as planned in unison or alternation in a pattern that repeats each hour, is a thing of beauty if you can visualize it, especially because if the motion of pulsing suggests the movement of blood through the heart. It’s like watching the inner life of a large multi-hearted organism. This can be a nice metaphor for other kinds of thinking about your city.
1 Ross R. Maxwell, “Converting a Large Region to a Pulsed-Hub Public Transport Network.” Transportation Research Record, paper 03-4020, p 128. Original paper here.
Peter Parker of Melbourne on Transit recently sketched some frequent network maps for that city, the second largest in Australia. You can find a range of efforts for various cities using the Frequent Network category. My original post arguing for the value of frequent network maps is here.
Although Melbourne is mostly flat and its street network is mostly gridded, it’s striking how few crosstown or “orbital” services they are. Over the past few years the main government initiative in this area has been the SmartBus program, a set of new frequent orbital routes. Yet compared to comparably dense parts of Los Angeles, say, the grid is thin. Continue Reading →
Washington DC’s transit agency WMATA is preparing to publish a frequent network map, and wants your comments. To start, they’re taking the approach of showing frequency as a highlight on the main network map, as this makes it easier to show how multiple overlaid routes combine to form a frequent line. Continue Reading →
