The 30-Minute City – Open Access

I am pleased to announce that you can now download a PDF version of The 30-Minute City: Designing for Access from the University of Sydney eScholarship Repository. (Free)

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Date

  • 2019-12

Author

  • Levinson, David M.

Metadata

This book describes how to implement The 30-Minute City. The first part of the book explains accessibility. We next consider access through history (chapter 2). Access is the driving force behind how cities were built. Its use today is described when looking at access and the Greater Sydney Commission’s plan for Sydney. We then examine short-run fixes: things that can be done instantaneously, or nearly so, at low budget to restore access for people, which include retiming traffic signals (chapter 3) and deploying bike sharing (chapter 5) supported by protected bike lane networks (chapter 4), as well public transport timetables (chapter 6). We explore medium-run fixes that include implementing rapid bus networks (chapter 7) and configuring how people get to train stations by foot and on bus (chapter 8). We turn to longer-run fixes. These are as much policy changes as large investments, and include job/worker balance (chapter 10) and network restructuring (chapter 9) as well as urban restoration (chapter 11), suburban retrofit (chapter 12), and greenfield development (chapter 13). We conclude with thoughts about the ‘pointlessness’ of cities and how to restructure practice (chapter 14). The appendices provide detail on access measurement (Appendix A), the idea of accessibility loss (B), valuation (C), the rationale for the 30-minute threshold (D), and reliability (E). It concludes with what should we research (F).

URI

The 30-Minute City by David M. Levinson

The 30-Minute City: A Review

Tom van Vuren reviewed my recent book, the The 30-Minute City in Transport Reviews. I abstract some of it here.

cropped-30-minute-city-cover-r1-front.jpg
The 30-Minute City: Designing for Access

The author describes the book as a fast read. He is right – it is written in a very straight-forward style, avoids jargon and as such, I think it would be enjoyed by practitioners, first-degree students and even those with just a general interest in transport planning and accessibility. This is the fifth book published by Network Design Lab in David Levinson’s Access series.

Much of the book describes ways in which a 30-minute city may be created; and as Levinson says, “we do not require autonomous vehicles, hyperloops, drones, trackless trams, micromobility, or multi-copters, even if we eventually see such things widely deployed”. After the introductory chapters, chapters 3 to 10 provide practical examples of how accessibility has been eroded and conversely, how it can be improved by interventions that can be copied from elsewhere.

I was particularly taken by Chapter 3 on Traffic Signals. Through a simple example, Levinson illustrates that in a typical urban environment pedestrians lose 25%–30% of their effective speed because of traffic signals that are coordinated for cars, reducing their accessibility to jobs and other opportunities in a 30-minute walk space by almost half. He also offers solutions that can be implemented immediately. Essential reading for all practising signal engineers!

Another excellent illustration is given in Chapter 8 on Interfaces. The design of a station can have a big impact on accessibility. Through another Sydney example, he explains how saving just 75 seconds entering and leaving a train station can improve accessibility by 8%, for example by increasing the number or relocation of entries and exits, or changing the interfacing with buses.

In his last Chapter Levinson makes a plea for a new profession, Urban Operations – people engaged in improving today’s city, not just planning for tomorrow, but optimising for the system as a whole, using resources on-hand. As he says: “we have enough problems today. We also have solutions available to us today and we don’t implement them”.

Levinson’s arguments around urban restoration and retrofitting deserve a space in all transport planning courses. He makes a strong case to always consider the era during which an urban area evolved when developing solutions to address currently experienced traffic problems. Levinson advocates to restore what worked at that time (such as trams in historic centres of the early twentieth century), but not to try and impose such solutions in locations that were built for the motorcar in the fifties and sixties. The latter can only be retrofitted, at a cost and not necessarily effectively. In terms of retrofitting, Levinson provides a telling example of the temporary land-banking in urban at grade parking lots and concludes wistfully that unfortunately, temporary is often indefinite.

I enjoyed this book for two reasons: As a dyed-in-the-wool, it challenged me to think differently about what transport planning and traffic engineering should really achieve. Secondly, Levinson peppers his text with memorable one-liners and inventive terms: who had heard of gradial before? Two noticeable examples that I might use myself:

  • Gradial, or the unreasonable network – Embedded infrastructure cannot adapt much to the world around it. But if it were optimal for the world in which it was designed, it is unlikely to be optimal as that world changes. The network, designed for a given technology, is very hard to adapt to a different technology. Instead, we expect the world to adapt to the infrastructure. And
  • There are many techniques for making the most popular mode, the automobile, greener. We need to think more about making the greenest modes much more popular.

As would be expected, the book finishes with an extensive and useful bibliography.

To get our cities moving again, we need a new kind of urban professional

In this extract from my new book The 30-Minute City,  I argue that in designing our cites, we need ‘Urban Operations’ experts who can straddle the realms of both strategy and tactics. Reprinted from Foreground

Access is the driving force behind how cities were built – which is to say, cities developed with the goal of making it as easy as possible for people to reach the opportunities and activities contained within them. In the contemporary city, though, the professionals tasked with designing and developing our cities for access can often seem to be working at cross-purposes.

Our engineers are trained in engineering school to ‘do it right.’ They are trained intensively in calculations to make sure the math works out. This is very important: structural engineers do not want to misplace a negative sign or they would build the bridge upside down. In contrast, our planners retort to the engineers ‘do the right thing.’ What are the right values? And that’s really important, too. Meanwhile, our public citizens say: ‘do the right thing right’, synthesising this apparent conflict.

30-minute-city
The 30-minute City: Designing for Access, David Levinson

In designing and managing our cities for access, we need to think about both strategy and tactics. We need to think about ideas and implementation. For instance, at train stations with entrances on only one end of the platform, the objective of enabling people to leave the station is supported, but not the broader objective of enabling them to reach their destinations in the least amount of time. Traffic signals presently are timed to minimise delay for vehicles, but not for people, and fail to count vehicle occupancy (buses wait in the same traffic as cars) or pedestrians.

“Traffic signals presently are timed to minimise delay for vehicles, but not for people” – David Levinson @trnsprtst

 

A Nihilistic Theory

I’m going to introduce a ‘nihilistic’ theory of transport and land use: everything is ‘pointless.’

Transit facilities are pointless. A station is not a point, it is a place.

Junctions are pointless. A junction, or intersection, is not a point, it’s a space. It has conflict points, which are also spaces, but it takes time to traverse, and those traversing it take up space.

Cities, too, are pointless, and yet planners often abstract away important details – as in the Greater Sydney Commission’s Metropolis of Three Cities plan, which, like so many regional plans, has dots on maps to represent whole communities.

Everyone working in the urban sphere should recognise this ‘pointlessness.’

Just as small spatial relations matters, so too does time. Do small amounts of time savings matter? Yes! Absolutely!

A traffic engineer proposes a change that will save somebody five seconds, and someone inevitably retorts that nobody cares about five seconds. But we can never get to larger time savings (or accessibility gains) when we’re always talking about how unimportant the small changes are. There is no way to save 15 seconds if you don’t save five seconds. There is no way to save 30 seconds unless you save 15, or one minute unless you save 30 seconds, or five minutes unless you save one minute.

Trips comprise many time elements, and use many bits of the transport network, and we are not going to save time all at the same place or with the same project or process. So the better practice is to take the gains that are possible, as they will accumulate over time. Saving time, or increasing speed, increases the area that can be covered in the same amount of time, and since accessible area increases with the square of the radius, time savings have disproportional effects on accessibility.

This argument applies to all modes. The traffic signal engineers use it to justify their signal timings for automobiles. The potential flaw here is not in saving time, but in doing so at the expense of pedestrians and the neighbourhood at large.

There is the argument that time, unlike money, cannot be ‘saved’, as there is no way to store it. And of course there is an element of truth there. But I would argue that time can be used for things that are valued more highly than standing at an intersection waiting to cross – which is to say, anything else. The time not spent waiting at the intersection might be spent in a more pleasant environment, or walking or riding farther to a slightly better or higher paying job, or a shop with somewhat better goods, or from a slightly better or less expensive home. These are the trade-offs people make all the time, and by increasing the area that can be traversed in a given amount of time, we increase opportunity and choice.

A profession that is interdisciplinary in real time – or, doing the right thing right

To do the right thing right, we want to forge a new profession that is interdisciplinary in real time. Planners create long-term plans covering large areas – they, at least in theory, aim to optimise for all of society. Analysts develop policies over large areas, which have a shorter-term time horizon, and also should at least consider all of society. But the local-looking professions – engineers, architects, urban designers, and technicians of various kinds – whether they are involved in building for the long-term or managing and operating the system in the short-term, by definition optimise locally, for the site, rather than the city. How the site interacts with the city is neglected.

We need a profession not of more urban planners, nor of more transport engineers, but urban operators – people engaged in today’s city, not tomorrow’s, but who can optimise for the system as a whole (that is, by thinking about accessibility) and not just their small piece of it.

The world is changing ever-faster. Yet strangely, today’s professionals undertake and celebrate very long-term plans where they acknowledge the existence of a problem (i.e. congestion), and technology (i.e. autonomous vehicles), but don’t acknowledge that anything changes.

Instead, we should forge new urban operators as a strong alloy of planning, engineering, economics, and design. Urban operators take ideas in real time and solve today’s problems with resources on-hand, rather than solving imagined problems that bring distant dangers near. We have enough problems today. We also have solutions available to us today, and we don’t implement them. And yet people are employed to work on 40-year plans.

“We need a profession not of more urban planners, nor of more transport engineers, but urban operators – people engaged in today’s city, not tomorrow’s, but who can optimise for the city as a whole” – David Levinson @trnsprtst

Today’s disciplines are excellent for admiring and nurturing today’s problems, but not nearly so adept at solving them. Engineers and planners are so focused on the long term, their jobs effectively require them to build it and then abandon it. Operating and maintaining the system is someone else’s responsibility. Once they have made their design they hand it over to a contractor for construction, who then hands it over to the client.

And then we have people who are making microscopic decisions without thinking about the big picture. Where do you put the bus stop relative to the train station? This affects accessibility, but the decision is made based on what is convenient for the bus operator rather than passengers, or worse, to minimise delay for cars.

As Bill Garrison argued, we want people who can bridge the hard and the soft – the hardware engineering of infrastructure and vehicles and the software of management, control, and financial systems.

Bridging or merging the soft and the hard would vastly improve policy and policy-making processes. We should be able to simultaneously think of engineering and policy, not be restricted to engineering or policy. Those of us in the transport field should identify as transportists – not transport engineers or transport planners or transport economists. The problem must come before the mechanism of solution.

We want people who can bridge the site and the city. People who think about the position of a train platform in the greater context of the metropolitan area, so that people living on the south side of the platform can easily reach it, rather than semi-circumnavigating the train station to its only entrance on the north.

We want a fusion of planners and engineers who would focus on the ends not on the means, who can think in multiple scales and multiple time horizons.

The goal of the 30-minute city aligns with travel time budgets and human behaviour. We know that, historically, land developers and the railway builders were keen on the idea of a feasible commute, and they were keen on this idea when they deployed tram and train networks and concomitantly subdivided large tracts into lots and built homes that were within a 30-minute commute of the central city.

Lower case ‘d’ design

Architects are famous for BIG design ideas. But cities are not amenable to big designs any more. They grow (and should grow) incrementally, not comprehensively. So instead let’s talk about what I will call “lower case ‘d’ design,” the humble design decisions about where to put bus stops relative to station entrances, and how to time traffic signals. These are small urban design decisions that don’t get sufficient attention.

There are many things that we can do that involve rethinking the details – like adding train station gates to both ends of platforms to expand catchment areas, and thus patronage. Details like stop spacing and location, practices like all-door boarding, payment before boarding, optimising timetables and frequency, may just squeeze a few seconds per stop or minutes per route out of the existing configuration, but collectively they greatly expand people’s accessibility.

More strategically, this requires thinking about transport and land use balance. Offsetting today’s imbalance can give us growth without additional travel or commuting-related congestion. To achieve a 30-minute city, cities need to put new jobs in housing-rich areas and new housing in job-rich areas systematically as a way of growing. This contrasts with local government’s desire to focus employment in the central city, and developers who will tend to put more housing in the outer suburbs where there are many fewer jobs.

And we need to design for the cities we want, not ‘predict and provide’ for the city we forecast. Our future cities cannot be delivered by the same disciplinary thinking that created the cities we have.

This is an abridged extract taken from David Levinson’s book The 30-Minute City: Designing for Access, available here in PDF format and here in print.

Levinson joined the School of Civil Engineering at the University of Sydney in 2017 as Foundation Professor in Transport Engineering. He conducts research on accessibility, transport economics, transport network evolution, and transport and land use interaction.

Gradial: Or the Unreasonable Network

The reasonable network adapts itself to the world; the unreasonable one persists in trying to adapt the world to itself. Therefore all progress depends on the unreasonable network.1

The physical location of network infrastructure is one of the most permanent decisions cities make. The Cardo Maximus in the old city of Jerusalem is still a main north-south shopping street, constructed when Emporer Hadrian rebuilt the city in the 130s CE.

The 30-Minute City by David M. Levinson
The 30-Minute City by David M. Levinson 

A street right-of-way, once created is seldom destroyed. A segment of that infrastructure is designed to be optimal at a moment of time, with a particular land use (either the realized development of today or an imagined place of tomorrow), enmeshed within a particular network context of all the other nodes and links, compatible with a particular technology. That it functions at all when land use, networks, and technologies change radically, as they do over centuries, is testament to the general flexibility inherent in networks. But the implication is that if it is optimal for the world in which it was designed, it is unlikely to be optimal as that world changes.

Some adaptations do occur. Streets designed for horses were adapted for streetcars (trams) and bicycles and cars and buses and pedestrians.

Still, it may be the best that can be done. Embedded infrastructure, the dictionary example of sunk costs,2 cannot adapt much to the world around them. Instead we expect the world to adapt to the infrastructure.

Following Shaw, we might say such infrastructures are `unreasonable’, in that they cannot be reasoned with.

Many, if not most, planned cities have been laid out with a network of streets “with the sombre sadness of right-angles,” as Jules Verne, quoting Victor Hugo, described the American grid in Salt Lake City, of streets at 90-degree angles to each other, in his classic road trip story: Around the World in 80 Days. Street grids don’t plan themselves, so while all street grids were planned, not all plans result in street grids.

Organically developed3 cities are often more naturalistic, radial cities, with streets feeding the city from the hinterlands, allowing more than 4-directions of entry. All roads lead to Rome, as the saying goes. The Romans themselves were a bit adverse to this organic radial system once they got their own growth machine going, laying out encampments and new settlements on the grid system. The radial system leading to and from the town would bend once it reached the town gates. But as cities themselves were generally not conceived of as whole, but rather themselves emerged, often as conurbations of smaller settlements, towns, and villages, there are often radial webs centered on town A overlapping radial webs centered on town B. Rome was famously built on seven hills, which can be read as meaning Rome is a conurbation of seven earlier villages. (See Elements of Access, Chapter 3.3)

Each of these networks typologies has its advantages and disadvantages.

DCMetro
Washington DC Metro. The center is a space, not a point. A `triangle’ is formed by L’Enfant Plaza (Yellow/Green with Orange/Blue/Silver), Metro Center (Red with Orange/Blue/Silver), and Gallery Place (Red with Yellow/Green)

 

We observe that radial networks are optimal to maximize access for many-to-one types of movements (suburbs to central city). So rail transit networks, which serve the high loads demanded by, and making possible, high density city centers tend toward being radial. But when they are large they are usually not so radial that all the branches meet at one junction. From a network design perspective, intersecting more than two lines at a station can lead to other types of conflicts, and many systems are designed with triangular center to avoid overloading a single transfer station. Washington DC’s largely radial Metrorail system, shown in  the first figure, illustrates this design. Cities are spaces, not points.

In contrast, the 90-degree grid is reasonably well-suited to maximize access for scattered trips, what network analysts would call a many-to-many pattern. We see this especially in dispersed point-to-point (suburb to suburb, within city to within city) flows that are enabled by and reinforce the grid. This is the network for the automobile. The Los Angeles freeway grid, the famous Milton Keynes arterial grid, and numerous other  late twentieth century cities have been designed in a grid-like way (though not so orthogonal that Victor Hugo would object). Even though the topology is not as efficient from a distance perspective as say a 60-degree mesh, by remaining out of the city core it can keep speeds higher.

But in response to the landscape that emerged with the automobile, transit planners like Jarrett Walker (2012) have called for more grid-like transit networks, so people can move, via public transport, from suburb to suburb without going through the city centre. This is relatively easy to reconfigure for buses, the very definition of  mobile capital, while very difficult for the more capital intensive rail networks with their physically embedded infrastructure.

Still, core radial lines will always be the backbone of transit systems so long as at least one important center justifies a disproportionate amount of service.

So how can we grid the radial, or square the circle, so to speak?

A better network topology might be the 60-degree, hexagonal pattern. (Ben Joseph 2000) But remaking street grids for existing cities is tough-going, as property rights are well established, and requires efforts like those of Haussmann in 19th century Paris. (Willms 1997).

daganzo
Possible system layouts: (a) hub-and-spoke; (b) grid; (c) hybrid. Source: Figure 1 in Daganzo (2010)

Instead, we have overlapping network topologies, ideally which are grade-separated in some fashion, so trains are radial and don’t intersect streets or motorways, and bus services can be more grid-like, and rapid or express bus networks serve the market niche in-between.

Thus the original street level networks are still topologically grids, but the services running on that grid, while still largely parallel and perpendicular, are compressed near the center, so the bus lines, for instance, bend towards the center, as illustrated in the second figure. The regulatory layer of through streets for automobiles may be constructed to defer to the orientation of bus services.

There are no optimal network configurations independent of the enveloping land use pattern or the technological regime. Similarly there are no optimal land use allocations independent of the network pattern or technology. Finally, there is no optimal mode independent of the land use or network. All three of these systems are interlocking. Moving one requires adapting the others.

The unreasonable network forces the land use pattern to adapt to it, such that relocating network elements is more costly than keeping them in place. Similarly, in many ways the network, designed for a given technology, is very hard to adapt to a different technology. That doesn’t stop people and cities from trying, the misfit we see with the automobile in the urban core is the product of failing to acknowledge this unreasonableness. But as the number of European cities restricting cars in the city center are showing, the unreasonable network wins out over technology too.

The Grid/Radial Gradial network is also Gradual. These systems seldom change all-at-once, instead they gradually evolve over decades, centuries, and millenia.


Notes:

1. This is an adaptation of a famous George Bernard Shaw quote.

The reasonable man adapts himself to the world; the  unreasonable one persists in trying to adapt the world to himself. Therefore all progress depends on the unreasonable man.

2. The economist’s adage that “sunk costs are sunk” means that once something has been built, and that money spent, it no longer factors into benefit-cost analysis about how prospective decisions should be made, except to the extent it changes the costs of various options. Logically, you shouldn’t go to a concert just because you bought tickets if you don’t want to go, though if you are considering going to a concert or a bookstore after you bought the tickets, you don’t need to account for paying for the tickets again. You might also consider the `opportunity cost’ of going as the loss from not scalping the tickets. You shouldn’t throw good money after bad. But the sunk infrastructure cannot be unbuilt.

3. Organic development is often largely systematically unplanned, though obviously some degree of planning often goes into laying out a street, even if it is disjoint from any other decisions. When we think of `planning,’ we are generally referring to longer-term more strategic type spatial plans, that consider interactions between prospective decisions, rather than short-term tactical plans that optimize a single decision alone decontextualized from the rest of the city.

How to increase transit ridership by up to 35% with one weird trick.*

This is a reprint from an article I wrote for The Conversation about our recent report “Catchment if you can: The effect of station entrance and exit locations on accessibility.”

The 30-Minute City by David M. Levinson
The 30-Minute City by David M. Levinson 

Train riders have to get to stations somehow. This is often referred to as the “first mile” or “last mile” problem. There are many technical solutions to help travellers get from home to the station and back, ranging from cars to electronic scooters, but most people use a much older technology, their feet, to get from A to B. What is seldom considered is access to the train platform itself.

Stations are not points but places. They occupy a large area. A person walking at average speed takes about two minutes to walk from one end of a full-length eight-car train to the other.

Often platforms have a single access point on one side of the station, which makes it more difficult for people on the other side of the station to get to the platform. Passengers may need to almost circumnavigate the station to get to the platform. At an average walking speed, the extra distance they must backtrack adds up to six minutes per trip each way, our research has found.

Imagine being so unlucky to have an extra 12 minutes of travel time every day if you take the train. You might be tempted to drive instead.

Catchment.jpg
Illustration of worst-case scenario, traveler lives west of the station with an East Platform and works East of a station with a West Platform, adding 6 minutes of travel each way, 12 minutes per day.

The table below shows the extra travel time in minutes depending on platform locations and access points for a traveller’s origin and destination. The average time for such a one-sided configuration of train stations is 3.25 minutes each way.

Work

East

West

Live

Platform

East

West

East

West

East

East

0

4

4

2

West

4

4

6

2

West

East

2

6

4

4

West

2

4

4

0

Table 1: Additional Travel Time Depending on Origin and Destination Residence and Workplace Location vis-a-vis Platform Location.

While this example is hypothetical, it is drawn from experience in Sydney, where 44 of 178 train stations have only a single side entrance.

So what impact will a second entrance have?

We examined those stations and access to their platforms: how many people lived within 5, 10 and 15 minutes of the station platform, considering actual entrance location, and how many jobs were within 5, 10 and 15 minutes of the platform. Using existing ridership data from Opal cards, we estimated a model that related the passenger entry and exit flows at each station to that station’s accessibility.

Accessibility at train stations across Sydney. Author provided

We sketched a second entrance at those 44 stations and measured accessibility again. It’s now higher, as having two entrances instead of one means more people can reach the platform in the same time. We then estimated the increase in ridership from the model due to the improved accessibility, assuming no change in population or employment.

Over all 44 stations, total morning peak period entries increased by 5%. But some stations benefit a lot, and others not at all, so prioritisation of investments matters.

It will be no surprise to locals that Erskineville station comes out on top with a nearly 35% increase. While many of the new apartment-dwelling residents west of the station make the extra hike every day, even more would catch the train if there were a convenient entrance.

Other top 10 stations include: Bankstown, Newtown, Villawood, Redfern, Burwood, Sydneham, Caringbah, Meadowbank and Penshurst. Planning is already under way to improve Redfern station.

While this result considers existing development, adding a second entrance can make new transit-oriented development that much more valuable. This is because it will likely increase activity on the previously less accessible side of the station, as the example of Erskineville shows below.

Author provided

 

Other considerations include accessibility for people who cannot use staircases, as many of the stations are older and will require lifts. The prospects of park-and-ride lots, the costs of construction, the presence of nearby stations, and site feasibility also play into final decisions.

Our formal findings and details methods are summarized in this Executive Summary, and written up in this report: Catchment if you can: The effect of station entrance and exit locations on accessibility

The full Atlas is here: Atlas

 

A brief interview was ABC NSW News, Friday May 3, 2019, starting at 13:24 into the broadcast.


*Results vary by station.

How more development can lead to less travel: Examples

The 30-Minute City by David M. Levinson
The 30-Minute City by David M. Levinson 

Balancing housing and jobs, so that they are located near each other, logically reduces travel compared to a situation where those same jobs are far apart. This has long been understood in the transport planning community (see e.g. Cervero 1989, or my 1998 paper), but is not well grasped among the general public.

However, moving a fixed number of things around is not how cities actually grow. Telling place A you taking away their employment is controversial. More generally new things are added.

Development in Mascot. Photo by author.
Development in Mascot. Photo by author.

It is commonly asserted that more development adds to congestion. And often this is true. But not always, it depends on the type of development. More housing in a housing-rich and job-poor area will result in more total travel. More employment in a job-rich, housing poor area will do similarly. More housing in a job-rich area, and more jobs in a housing-rich area can actually reduce travel.

For our baseline case, imagine a city with two precincts separated by 2 km.

Precinct A: 1000 Jobs, 0 Resident Workers

Precinct B: 0 Jobs, 1000 Resident Workers.

The one-way (morning commute) trip table looks like:

Jobs 1000 0
Workers A B
0 A 0 0
1000 B 1000 0

Total daily travel to work is 2000 person km per day. (Everyone commutes from B to A). Travel on Link BA is 1000 at 2 km per trip, or 2000 person km traveled. (This just analyzes one-way trips. Round trip commutes would double this.)

Case 1. 

There is a proposal to intensify development in Precincts A and B, so each is more locally balanced.

Precinct A: 1000 Jobs, 500 Resident Workers

Precinct B: 500 Jobs, 1000 Resident Workers.

The new one-way (morning commute) trip table looks like (rounded):

Jobs 1000 500
Workers A B
500 A 498 2
1000 B 503 497
  • assuming 0.5 km intrazonal travel distance, using a doubly-constrained gravity model with a d_{ij}(-2) impedance function.

The Daily Travel on links:

AB = 2 @ 2 km

BA = 503 @ 2 km

within A = 498 @ 0.5 km (walking)

within B = 497 @ 0.5 km

TOTAL = 1507 pkt.

This is considerably less than the baseline case as many more travelers can reach their destinations locally. While there is still some commuting, it is far less than before.

Case 2.

There is a proposal to build a locally-balanced Precinct C halfway between Precincts A and B.

Precinct C has 500 Jobs and 500 Workers

The new one-way (morning commute) trip table looks like:

Jobs 1000 0 500
Workers A B C
0 A 0 0 0
1000 B 666.666667 0 333.333333
500 C 333.333333 0 166.666667
  • assuming 0.5 km intrazonal travel distance, using a doubly-constrained gravity model with a d_{ij}(-2) impedance function.

The Daily Travel on links:

BC = BA + BC = 1000 @ 1 km

CA = BA + CA = 1000 @ 1 km

within C = 166 trips @ 0.5 km

TOTAL = 2083 pkt.

In this example, the total person kilometers traveled (pkt) on the links connecting inter-city precincts is essentially identical to the base case, despite adding 500 residents and 500 workers halfway between each. There are an additional 167 pkt daily on the intrazonal market (within C), which is likely walking.

The total one-way commute travel per person however drops, from 2 km/person per day to about 1.38 km/person per day. The average trip length is reduced. The experienced travel is thus about one-third lower.

Case 3

Building on Case 1, completely balancing A and B (so each has 1000 jobs and 1000 workers) reduces one-way commutes further (to 1176 pkt)

The new one-way (morning commute) trip table looks like (rounded):

Jobs 1000 1000
Workers A B
1000 A 941 59
1000 B 59 941
  • assuming 0.5 km intrazonal travel distance, using a doubly-constrained gravity model with a d_{ij}(-2) impedance function.

So, it should be clear from this example that adding development can actually reduce total travel, if it is the right kind of development in the right places.

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King

Signalling inequity – How traffic signals distribute time to favour the car and delay the pedestrian.

An edited version of this appeared on The Conversation June 11, 2018. The original is below.

Traffic signals are a source of great inequality in the urban realm, giving priority to motor vehicles over pedestrians.  Cities and states say they want to encourage walking and biking for many reasons: it is space efficient, it has less environmental impact, it is healthier, it is safer for other travelers, and, since,  it reduces the numbers of cars on the road, even motorists should be in favour of other people walking. To help achieve that, road management agencies should take the lead in reprioritising traffic signals by redistributing intersection delay from pedestrians to cars.

The 30-Minute City by David M. Levinson
The 30-Minute City by David M. Levinson

 

While planners tend to focus on the long-term decisions, like infrastructure and land development, it is the shortest of short-term decisions, how many seconds of green light each movement gets at an intersection, that shapes daily perception of the feasibility of walking or driving to a destination at a given time, and thus the choice of route, destination, and mode of travel. Traffic signal timing involves math, so it has been historically delegated to the engineers, but it also involves values and priorities, and so is the proper subject of public policy.

Since the early twentieth century dawn of what Peter Norton calls ‘Motordom’ in his book ‘Fighting Traffic‘, street space has steadily been regulated and enclosed, limiting the rights and privileges of pedestrians while promoting those of drivers as a class, in the name of safety and efficiency. But we should ask safety and efficiency for whom? Prior to traffic signals, pedestrians could and did cross the street whenever and wherever they wanted, before the term ‘jaywalking’ was invented and street crossing was regulated. The introduction of signals prioritised the movement of motor vehicles at the expense of pedestrians, whose effective walking speed through the city necessarily slowed. The consequences of making it easier to drive and harder to walk on people’s choice of mode is pretty straight-forward, and consistent with the rise of the automobile in the 20th century.

Phases

Pedestrians take longer to cross streets than cars because they move slower. As a result, the ‘don’t walk’ signal flashes before the light turns red for cars. But at many intersections it is worse than that. In Sydney, the traffic signal policy is set at many intersections to give less green time to pedestrians on a phase (from the time the light turns green to when it turns red, or from ‘walk’ to ‘don’t walk’)  than to automobiles, to give autos a protected left turn without having to yield pedestrians. This guarantees the average pedestrian arriving randomly at the intersection waits longer than a random car.

Cycle length

The cycle length (time from the start of the green light to the start of the next green) tends to be longer at busier intersections (and busier times of day) as a longer cycle length reduces the number of phases per hour, and thus reduces the amount of lost time associated  each phase, when the intersection is not being effectively used by any approach. Lost time can never be reclaimed, so one understands why engineers might want longer cycle lengths if the objective were moving cars.

However long cycle lengths particularly disadvantage pedestrians, who stand out in the open exposed to the elements and the tailpipe emissions of cars, motorcycles, trucks, and buses. Even more significantly, people systematically misperceive travel delay, so waiting at a traffic light feels even longer than it actually is.

Coordination

First introduced in 1922 in New York City, traffic signal coordination aims to ensure vehicles arrive at the traffic signal when it is green, so they don’t have to stop. By correctly timing traffic signals in sequence, platoons of vehicles move together through a ‘green wave’. So let’s say the wave is set for a speed of 40 km/h. Then as long as a car accelerates from the first signal to 40 km/h, and maintains that speed, it should then hit the following lights on their green phase as well.

Typical_Signal_Schedule_and_Traffic_Flow_Diagram,_North-South_across_Market_(1929).png
Typical Signal Schedule and Traffic Flow Diagram, North-South across Market Street, San Francisco (1929). Green wave set to 10.5 MPH (about 17 km/h).

While this is relatively easy to maintain on a single road, it is more difficult on a network, especially a complex, asymmetric network. It also works against the idea of actuation, as interruptions to the pattern (extending or contracting phases) change the window in which cars can successfully hit a green light at a given speed. Of course, just because cars can make a green wave at a speed of 40 km/h doesn’t mean pedestrians will make a green wave unless they travel at exactly a divisor of 40 km/h (e.g. at exactly 5 km/h between intersections). This means that pedestrians will more likely wait at red lights at intersections timed for cars.

Actuation / Beg Buttons

While some signals are ‘fixed time’ which eases coordination at the expense of adapting to conditions, modern signals are ‘actuated’, that is, they respond by adjusting the phasing, and perhaps the cycle time, in response to the presence of vehicles. For vehicles, there is either a camera which detects their presence, or more commonly, a sensor in the road, often a magnetic loop. In either case, this is automatic for the car, and can detect cars upstream of the signal. This allows the signal to stay green longer for a phase if it detects a vehicle approaching, or turn red sooner when there are no vehicles. In contrast, for pedestrians, they are required to push a button to get a walk signal. If they arrive a second too late, they have to wait the entire cycle to get a walk signal. If there are many pedestrians, they don’t get a longer walk signal. Pushing the ‘beg button’ (so nicknamed as the pedestrian must request the signal) twice does not make it come faster or stay green longer. Ten, or a hundred, pedestrians do not make the ‘walk’ light come faster either. The beg button is often positioned out of the way, requiring the pedestrian to walk longer than would otherwise be required. A few seconds here, a few seconds there, add up.

There is a  reason that traffic engineers don’t automatically allocate pedestrian phases. Suppose the car only warrants a six second phase but a pedestrian requires 18 seconds to cross the street at a 1 meter/second walking speed. Giving an automatic pedestrian phase will delay  cars, even if the pedestrian is not there. And there is no sin worse than delaying a car.  But it also guarantees a pedestrian who arrives just after the window to push the actuator passes will wait a full cycle.

The role of signal policy

It turns out that one of the world’s most widely deployed traffic signal control systems, the Sydney Coordinated Adaptive Traffic System (SCATS), was developed here in Australia. Just as Australia led in traffic control to more smoothly move cars, it should lead in pedestrian-oriented traffic control. There are a number of steps that those concerned about pedestrians should insist on. To start:

  • Pedestrians, like vehicles, should be counted automatically at controlled intersections.
  • Pedestrian time must be considered (and prioritised) in the traffic signal timing algorithms so that their weight is equal to or higher than the weight of a passenger car.
  • Pedestrians should get the maximum feasible amount of green time on a phase, rather than the minimum, so that pedestrians arriving on the phase have a chance to take advantage of it, and slower moving pedestrians are not intimidated by cars.
  • Pedestrians should get a ‘leading interval’ so they can step into the street on a ‘walk’ signal before cars start to move on a green light, increasing their visibility to drivers.
  • Pedestrian phases should be automatic, even if no actuator is pushed. Instead, the actuator should make the pedestrian phase come sooner.
  • Many more intersections should have an all-pedestrian phase (what is referred to as a ‘Barnes Dance’) in addition to existing phases so pedestrians can make diagonal intersection crossings without having to wait twice.

There are numerous other steps as well that can improve the life of the pedestrian, and thus increase their number. Certainly we can demand more patience from drivers as well.  The advent of the autonomous vehicles over the next few decades is unlikely, by itself, to eliminate the need for traffic control in cities. There will be places where the number of cars and people are such that they cannot efficiently organize themselves, and where other traffic controls, like stop signs or roundabouts, cannot be effectively implemented. But autonomous vehicles should help get more throughput out of intersections, losing less time than human drivers, and behaving far more safely.

Moving the capital of New South Wales to the west

The capital of New South Wales is currently in Sydney, eastern Sydney, historic Sydney, tourist Sydney, or to speak the language the planners understand, the Harbour City. Parliament meets in a gorgeous building adjacent to the Domain, a large urban park. Government offices are scattered throughout the city and the metro area.

New South Wales Parliament Building
New South Wales Parliament Building

Policy in Sydney has recently engaged around the idea of a 30-minute city, the idea that people can get where they need to go on a daily basis (work, shop, school) in 30 minutes or less by walking, biking, or public transport. (Or that 70% of the people do so, depending on which definition.) This can be achieved through a combination of transport and land use strategies. On the transport side is the question of how fast and how direct the transport network is. On the land use side is the question of where desired activities are located relative to each other. The government of New South Wales is promoting the development of jobs in Western Sydney (and housing in Eastern Sydney) to reduce commuting times and encourage the 30-minute city. This is a noble goal, and the market may move in that direction.

The 30-Minute City by David M. Levinson
The 30-Minute City by David M. Levinson 

At one extreme we can imagine a completely functionally separated city, where all the homes are on one side of town, and all the jobs are on the other side of town. If the sides are more than 30 minutes apart, there is little that can be done to achieve the goal, though perhaps the connection between the two parts can be made faster or more direct. But since transport networks act to spread out cities physically, it might only induce more suburban development. This functionally separated city is equivalent to the classic monocentric city, with a single dominant downtown surrounded by residential suburbs.

At the other extreme we can imagine a completely functionally integrated city, probably relatively dispersed, where jobs and housing are completely integrated, so there are as many jobs in any suburb as there are workers. There is no guarantee that a worker will be able to find a job next door (or choose it), but the likelihood of finding a job nearby is higher than in the monocentric city

If everything else were equal, from a transport perspective, we would probably prefer an integrated city, as this would place the least strain on the transport network. Moving towards jobs/housing balance is a long held goal, if only weakly operationalized.

But all else is not equal. Employers have an affinity for each other. All the big banks want to be near each other, as do other big companies in various sectors. As does the government. This is what economists call economies of agglomeration.

The government is not just an employer, it is also a major player in real estate markets. It can catalyze development of western Sydney, its Aerotropolis/Parkland City, as it is called in the 2056 Three Cities plans, by moving itself there first.


 

Cities change with the pre-dominant transport technology. When the capital was established in Sydney in 1788, the dominant technology was animal and human powered, with wind and sails moving ships. Since then, much has changed, and the center of population has migrated inland.

The shape and form of the pedestrian city differs from the rail (trams and trains) city, and  differs from the automobile city. Retrofitting trams into the pedestrian city, and especially automobiles into the pedestrian and rail cities broke much earlier urban functionality, while creating new problems, new opportunities, and new designs. Technology played and plays out differently on greenfields, which could be designed to serve a new transport paradigm.

As we approach the transition from the traditional automobile to the autonomous electric and shared vehicle, with all of the ancillary changes, the opportunity for a new city of the future emerges. This technology will invade existing places, which will need to adapt, and new places which can more fully adopt the new technology. But we also need to keep an eye out for the next transition, whatever that may be (flying cars?), so that what we build now is not soon obsolete.

Transport is not the only shaper of cities, other technologies are also critical, from piped water and sewer, electricity, telephony, elevators, and air conditioning historically, to wireless high-speed internet most obviously today, and robotics coming up shortly.

The new capital will need to orient itself around these new technologies, as well as new extensions of well known technologies, like trains and Metros and light rails and bicycles and pedestrians. This is a huge opportunity, and while I won’t suggest a specific design, I will say it should be forward looking as well as reflective of the changes that have come before. Canberra was an opportunity, but by spreading itself out so much, it foreclose the possibility to effectively use slower modes.

If Daniel Burnham were designing the new capital for Sydney, it might look like this.
If Daniel Burnham were designing the new capital for Sydney, it might look like this.

 

A government campus for key departmental headquarters and Parliament at the end of the Mall, a now traditional design for capitals, with the vast majority of government offices scattered throughout the rest of New South Wales, could spark development. Access to the new airport and rail lines will provide connectivity to the rest of the state.

Ancillary businesses, not just those serving lunch to government workers, but those dealing with government on a daily basis, will migrate to deal with their public sector clients and customers. There are many sites on the axis between Parramatta and the Blue Mountains that could serve this purpose.

Sydney’s soon-to-be-abandoned historic Parliament House can have a variety of uses, from appropriately sized conventions to space for a museum. Other government offices in Sydney can be sold off, retrofitted for urban housing, or replaced as warranted. The Sydney CBD is thriving, and will continue to without a few thousand additional government workers. But that could be all the difference in success for a new city for Western Sydney.

In 1908, Australia, then with a population of 4.1 million, decided to relocate to Canberra. Today (2018) New South Wales has a population 7.8 million. As Australia has proven, the political capital need not be the largest city.  In the US, most state capitals are not the largest city: St. Paul not Minneapolis, Sacramento not Los Angeles, Albany not New York, Harrisburg not Philadelphia, Springfield not Chicago, Annapolis not Baltimore, and so on to name but a few.

 

Albany, New York, another planned state capital district
Albany, New York, another planned state capital district. Source: Flickr

It is time to plan and create a new government precinct, out west, to help spark the development the government seeks. It will bring the government to the people, de-center the government from its locational bubble, and juvenate new places with new ideas.

 

How much time is spent at traffic signals?

The 30-Minute City by David M. Levinson
The 30-Minute City by David M. Levinson 

While working on another piece, I came upon the question of how much time is spent at traffic lights, for which there is not a well-sourced answer. I posted to Twitter and got some useful replies.

With that and some additional digging, I attempt to answer the question.

As the saying goes: Your Mileage May Vary. This depends on your origin and destination and path and mode and time of day and local traffic signal policies and street design. Tom VanVuren notes: “Much of the impact is in slow moving queues, rather than waiting for the signal cycle to complete. I expect you can make this number smaller than 10% (time at the stop line) or larger than 50% (time affected by traffic lights).” For simplicity, I am considering vehicles that would be stopped if they could either move at the desired speed or must stop (i.e. they are subject to “vertical” or “stacking” queues), but clearly measurement will depend on assumption. Still, there must be a system average. I had heard the number 20% bandied about, which feels right, but let’s first begin with some thought experiment, then look for some empirical results. We take different modes in turn.

A signalized but porkchop-islanded crosswalk at a Free Left (Free Right for those in the right-side drive countries). Notice the pedestrian light is red (don't walk) but the pedestrians cross anyway. If the free left is not eliminated in a more comprehensive redesign, it could easily be de-signaled and the crosswalk raised, so pedestrians dominate, and cars travel when they can.
Pedestrian Crossing at Broadway and City Road, Sydney. Pedestrians crossing against the light.

Motor Vehicles

Thought Experiments

Thought Experiment 1 A

Imagine an urban grid.

  • Assume 10 signalized intersections per km.
  • Assume a travel speed of 60 km/h when in motion. (This is probably too high with so many intersections and no platooning, but we are imagining here that you would not be stopping.)
  • Time to traverse 1 km=1 minute + signal delay.  (Some of the distance traversal time overlaps some of the signal delay time, but we will imagine a stacking queue, rather than one that has physical distance for simplicity, we can correct this later if it matters.)
  • Assume each intersection has only 2 phases.
  • Assume fixed time signals at each intersection evenly distributing green time between N/S and E/W directions.  So red time = 1/2 cycle length.
  • Assume 1 minute cycle length
  • If a vehicle stops, it waits 1/2 red time.
  • Vehicles obey traffic signals.
  • Assume no platooning.

This means that the average vehicle will stop at 5 intersections for 15 seconds each = 75 seconds (or 1.25  minutes) (vs. 1  minute in motion time). In this case, 1.25/2.25 minutes (55.5%) is spent waiting at signals.

Thought Experiment 1 B

In contrast.

  • Assume near perfect platooning.

In this case, the vehicle will stop at 1 intersection per km, for 15 seconds = 15 seconds. In this case 0.25/1.25 = 20% of the time is spent waiting at signals.

Discussion

Now, not all travel takes place on an urban grid.

  • Assume 25% of travel is on limited access roads (this is approximately true in the US),  75% on non-limited access roads.

With perfect platooning on the grid, and 25% off-grid, then 15% of travel time is intersection delay with near perfect platooning.

Clearly in practice platooning is far from perfect. My guess is the green wave breaks down after one or two intersections during peak times, but can survive well in the off-peak. As a rule of thumb, about ~10% of travel is in the peak hour, ~30% peak period. ~60% AM + PM Peak.

Data

GPS Studies

Eric Fischer of MapBox was kind enough to offer to run this question on their open traffic data. The results are not yet in. I will update when they are.

Arterial Travel Time Studies

There are a variety of Arterial Travel Time studies for specific corridors, but nothing that is universally generalizable.  (And logically where people do arterial travel time studies, there is a congestion problem, otherwise why study it.)

I recall that in my childhood, I did a study in Montgomery County, Maryland using such data (from 1987 traffic counts and a floating car study published by Douglas and Douglas), I did not actually compute the percentage, but fortunately I reported enough data that allows me to compute the percentage now. (The sample is of course biased to what is measured). For the average arterial link, the speed was

 Variable Inside the Beltway  Outside the Beltway
 Speed (km/h) 34.88  41.60
 Length (km)  0.46  0.72
 Time (min)  0.792  1.04
 Downstream Delay (min)  0.27  0.24
 Percentage of Signal Delay  25%  18.75%

Which is consistent with expectations that signals are more significant in more urbanized areas (inside the beltway is basically Bethesda and Silver Spring, MD), and with our general estimates. Now of course the speed here is impacted by downstream signals, and so is lower than the speed limit and certainly lower than the free-flow speed sans-signals. More details are in the paper.

Engine Idling Studies

Moaz Ahmed pointed me to a Vehicle Idling Study by Natural Resources Canada.

The percent of time of vehicle idling ranged from 20-25%. (Not all vehicle idling is at signalized intersections).

(Engine idling of course burns fuel without doing work, so if the engine is going to be idling for an extended period, it would save fuel (and reduce air pollution) to turn it off. Turning the engine on and off also has costs, so the estimate was if idling was going to be longer than 10 seconds, it uses more fuel, but considering other wear and tear costs, the recommended threshold is if idling is longer than 60 seconds, then turn off the engine.  But at a signalized intersection, how will vehicles know how long they will wait? Smart traffic signals with connected vehicles could provide this, but now they don’t. Eventually this will be moot with a full electric vehicle fleet. Until that time, it matters. I suspect given the longevity and sluggishness of the traffic control sector, smart signals informing trucks will not be widely or systematically deployed before trucks are electrified.)

Pedestrians

Now as noted above, Your Mileage May Vary. If you are a pedestrian, you are unlikely to hit a greenwave designed for cars, though of course your travel speed is slower is well. So redoing the Thought Experiment

Thought Experiment 2

Imagine an urban grid.

  • Assume 10 signalized intersections per km.
  • Assume a travel speed of 6 km/h when in motion. (this is a bit on the high side, average pedestrian speed is closer to 5 km/h)
  • Time to traverse 1 km=10 minutes + signal delay.  (Some of the distance traversal time overlaps some of the signal delay time, but we will imagine a vertical stacking queue, rather than one that has physical distance for simplicity, this is a much better assumption for pedestrians than vehicles.)
  • Assume each intersection has only 2 phases.
  • Assume fixed time signals at each intersection evenly distributing green time between N/S and E/W directions.  So red time = 1/2 cycle length.
  • Assume 1 minute cycle length
  • If a pedestrian stops, she waits 1/2 red time. (That is the “walk” phase for pedestrians is as long as the green phase for cars. Strictly speaking this is not true, it is more true in cities with narrow streets than it is in suburban environments with wide streets, as narrow streets can be crossed more quickly, so the amount of “walk” time allocated can be most of the phase. This is certainly not true in Sydney, where the “walk” phase is cut short so turning cars have fewer conflicts with late pedestrians.)
  • Pedestrians obey traffic lights.  (This is not as good an assumption as vehicles obey signals, pedestrian signal violation is probably higher. This is not a moral judgment one way or the other, people tend to obey authority, even when authority abuses power.)
  • Assume no platooning. (This is probably too severe, a quick pedestrian with some signal coordination can probably make a couple of lights in a row).

Here the average pedestrian will stop at 5 intersections for 15 seconds each = 2.5 minutes (vs. 10  minute in-motion time). In this case, 2.5/(2.5+10) minutes (or 20%) is spent waiting at signals. Now, this number is probably true for more pedestrians than the vehicle delay estimate is for vehicles, since pedestrians are more likely to be found on an urban grid and less in a suburban or limited access environment. (Self-selection at work).

Bicyclists

If you are a bicyclist, you are unlikely to hit a greenwave designed for cars unless you travel at exactly an integer fraction (1/1, 1/2, 1/3) of the green wave, as your travel speed is slower is well. So redoing the Thought Experiment

Thought Experiment 3

Imagine an urban grid.

  • Assume 10 signalized intersections per km.
  • Assume a travel speed of  20 km/h when in motion. (This is a typical for experienced riders). Time to traverse 1 km=3 minutes + signal delay. (Assume a stacking queue)
  • Assume each intersection has only 2 phases.
  • Assume fixed time signals at each intersection evenly distributing green time between N/S and E/W directions.  So red time = 1/2 cycle length.
  • Assume 1 minute cycle length
  • If a bicyclist stops, she waits 1/2 red time. (That is the ‘bike’ phase for bicyclists is as long as the green phase for cars.)
  • Bicyclists obey traffic lights.  (This is not as good an assumption as ‘motor vehicles obey signals’, bicyclists signal violation is probably higher.)
  • Assume no platooning. (This is probably too severe, a quick bicyclists with some signal coordination can probably make a couple of lights in a row).

In this case the average bicyclists will stop at 5 intersections for 15 seconds each = 2.5 minutes (vs. 3  minute in-motion time). In this case, 2.5/(3+2.5) minutes (or 45%) is spent waiting at signals in an urban environment.

Strava Data

Strava, an app for tracking bicyclists and runners can produce some useful data. Andrew Hsu, e.g., reports “28 mile bike commute. 1:30-ish moving time. 10-15 minutes waiting at lights.” From this, for him, we estimate 15 / (15+90) = 14%. To be clear, 1:30 is an extreme commute. I don’t have access to the full database, and obviously this is biased by the nature of the trip.

Buses

Alejandro Tirachini produced an estimate of travel time for buses finds delay at traffic signals (in suburban Blacktown, Sydney, NSW) is 10-13% of total time.