Spatiotemporal Traffic Forecasting: Review and Proposed Directions


Abstract: This paper systematically reviews studies that forecast short-term traffic conditions using spatial dependence between links. We extract and synthesise 130 research papers, considering two perspectives: (1) methodological framework and (2) methods for capturing spatial information. Spatial information boosts the accuracy of prediction, particularly in congested traffic regimes and for longer horizons. Machine learning methods, which have attracted more attention in recent years, outperform the naïve statistical methods such as historical average and exponential smoothing. However, there is no guarantee of superiority when machine learning methods are compared with advanced statistical methods such as spatiotemporal autoregressive integrated moving average. As for the spatial dependency detection, a large gulf exists between the realistic spatial dependence of traffic links on a real network and the studied networks as follows: (1) studies capture spatial dependency of either adjacent or distant upstream and downstream links with the study link, (2) the spatially relevant links are selected either by prejudgment or by correlation-coefficient analysis, and (3) studies develop forecasting methods in a corridor test sample, where all links are connected sequentially together, assume a similarity between the behaviour of both parallel and adjacent links, and overlook the competitive nature of traffic links.

Postdoctoral Research Associate in Transport – Closing date: 11:30pm, Tuesday, 27 March 2018

Postdoctoral Research Associate in Transport

School of Civil Engineering

Faculty of Engineering and IT

Reference no. 779/0417B

  • Join an organisation that encourages progressive thinking
  • Be valued for your exceptional knowledge and experience in Transport Networks
  • Full-time fixed-term for 3 years, remuneration package: $106k (which includes base salary, leave loading and up to 17% superannuation) 

About the opportunity

Applications are invited for the appointment of one Postdoctoral Research Associate (Level A) in the School of Civil Engineering, within the Faculty of Engineering and IT at the University of Sydney. The position will support the research and leadership of School of Civil Engineering in the newly launched Transport Engineering program.


The successful applicant(s) will help build the new research group headed by Professor David Levinson to further the analysis of Transport Networks, understand the relationships between Transport Networks and Land Use, and consider the implications of changing Transport Technologies on optimal Network Structure.


About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance in recruiting talent aligned to these values in the pursuit of research excellence. We are looking for a Postdoctoral Research Associate who:


  • Holds a PhD in civil engineering, or related fields
  • Has published ground-breaking research in the area of transport networks, geo-spatial analysis, and/or econometrics in high quality international journals
  • Possesses strong communications skills as the position requires liaising with government and industry stakeholders.

About us
We are undergoing significant transformative change which brings opportunity for innovation, progressive thinking, breaking with convention, challenging the status quo, and improving the world around us.

Since our inception 160 years ago, the University of Sydney has led to improve the world around us. We believe in education for all and that effective leadership makes lives better. These same values are reflected in our approach to diversity and inclusion, and underpin our long-term strategy for growth. We’re Australia’s first university and have an outstanding global reputation for academic and research excellence. Across 9 campuses, we employ over 7600 academic and non-academic staff who support over 47,000 students.


The University of Sydney encourages part-time and flexible working arrangements, which will be considered for this role.


For more information about the position, or if you require reasonable adjustment or support filling out this application, please contact Emmen Saeed, Recruitment Partner, on

If you would like to learn more, please refer to the Candidate Information Pack for the position description and further details.


To be considered for this position it is essential that you address the online selection criteria. For guidance on how to apply visit: How to apply for an advertised position.


Closing date: 11:30pm 27 March 2018

The University of Sydney is committed to diversity and social inclusion. Applications from people of culturally and linguistically diverse backgrounds; equity target groups including women, people with disabilities, people who identify as LGBTIQ; and people of Aboriginal and Torres Strait Islander descent, are encouraged.


If we think your skills are needed in other areas of the University, we will be sure to contact you about other opportunities.


The University reserves the right not to proceed with any appointment.

Candidate Information Pack

Selection Criteria

How to apply:

Normalizing Citations – Beyond the H-index

The proper metric for an academic’s influence on the academic world of academic publishing is academic citations. An academic might make many (say 100) small contributions, each cited a small number (say 10) of times, or one contribution cited widely (say 1000) times. Neither is inherently superior, despite claims to the contrary, a

Citation needed. Source: Unknown.
Citation needed. Source: Unknown.

nd for the academic in question, it was probably easier to write one widely cited piece than 100 smaller ones, but that was unpredictable at the time.

Academic citations are cumulative distribution function, they can never go down (they can with retractions, but we will neglect that). So by this measure on average senior academics appear more influential than younger academics, which they of course are. But this is not a useful measure for filtering prospective candidates for hiring and promotion, which is why these metrics exist, to sort people based on productivity and establish a social hierarchy.

So to begin, we have two corrections to make. First, senior academics have more opportunities to write papers. A junior academic simply has not had the cumulative time to author 100 papers. Second, the senior academic’s papers have had more time to accumulate citations. So I suggest dividing total citations by Years^2 to account for these two temporal accumulating factors.

But which “Years”? Years since terminal degree? — This favors the young who start publishing before their degree. Years since they began their degree? Almost no one has any paper in year 1 of their graduate career. So we can estimate and split the difference and say years since graduation with terminal degree +2, on the theory that by the time you graduate you should have had at least 3 papers, and that means you started about 2 years before graduation. Still this is highly sensitive to assumptions for younger academics, it will wash out for the older academics. Domains will vary of course in terms of publishing culture.

There are other problems, for instance, co-authorship. At the extreme, all 108 billion people who ever lived have contributed fractionally to every paper, but they don’t all get co-authorship (except on experimental physics papers). But someone who puts all of their PhDs on all of their group’s papers is gaming the system to the detriment of those who assign more individually authored papers. So each citation should be divided by the fraction of authorship that the academic in question deserves. While this is impossible to assess, (promotion files sometimes ask for percentages on co-authored papers, but this is never systematically estimated or consistent). Computing an average dividing by the number of authors on the paper is a good surrogate.

I am not in this business of bibliometrics, I will leave that to others. But hopefully someone in the industry (Scopus, Web of Science, Google Scholar) can run the proposed corrections on these databases and produce a normalized citation measure as a standard output.

How traffic signals work: Some terms


Traffic engineers have developed terminology to aid in communication

The ‘approach’ is the set of lanes that are coming into a particular intersection, from a given direction. So, there might be an eastbound approach of traffic that is moving in the easterly direction.  A ‘cycle’ is the complete amount of time that it takes to go from a red light to a red light. We think of it as a clock. ‘Cycle length’  is the amount of time it takes to complete a cycle, measured in seconds.  A ‘phase’ is part of a cycle that is allocated to a particular movement, which receives the right-of-way. There might be multiple movements that receive right-of-way simultaneously, as long as they are not conflicting.  The northbound and southbound movements might both get the green light at the same time. They’re on the same phase, and they’re not conflicting.

“What do you do with right (left – in right hand drive countries) turns?” Do you give them a separate phase? Or do they share the phase? If they share the phase, then it becomes more complicated. There are many possible patterns, from which traffic engineers aim to select the ‘optimal,’ but that depends on the objectives and conditions.

There are ‘movements’. ‘Protected’ movements have right-of-way, and don’t have to yield to any other conflicting movements,  opposing vehicles, or to pedestrians. The ‘permitted’ movement is most common for right turns (in left-hand drive countries like Australia), for instance when making a turn without a green arrow, the driver has the permission to make that movement, so long as it is safe, but is not protected by a red light in the conflicting direction. Left turns are also permitted if there are no conflicting pedestrians or bicyclists.

‘Lost time’ occurs at the start of the phase because the first car has to accelerate from a dead stop, which takes some time: drivers first perceive the green signal, then check to make sure the intersection is clear, and then accelerate from a stop. So the speed at which that first (and second, and third) car goes through the intersection is slower than subsequent vehicles. There is also lost time at the end of the phase as some drivers are reluctant to go through on an amber (yellow) signal. There is also an ‘all red’ phase in some places to make sure the intersection is fully cleared of vehicles and pedestrians.

How much time is spent at traffic signals?

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 = 2.5 minutes (vs. 1  minute in motion time). In this case, 2.5/3.5 minutes (or 5/7 or 71.4%) 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.


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.


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.)


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).


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.


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.

The Transportist: March 2018

Welcome to the March 2018 issue of The Transportist, especially to our new readers. As always you can follow along at the blog or on Twitter.

Thank you to all who purchased Elements of Access. Copies are still available.

Book: Metropolitan Transport and Land Use

As cities around the globe respond to rapid technological changes and political pressures, coordinated transport and land use planning is an often targeted aim.
Metropolitan Transport and Land Use, the second edition of Planning for Place and Plexus, provides unique and updated perspectives on metropolitan transport networks and land use planning, challenging current planning strategies, offering frameworks to understand and evaluate policy, and suggesting alternative solutions.
The book includes current and cutting-edge theory, findings, and recommendations which are cleverly illustrated throughout using international examples. This revised work continues to serve as a valuable resource for students, researchers, practitioners, and policy advisors working across transport, land use, and planning.


Transportist Posts

Transport News







SVs/Taxis/Car Sharing


Intercity Rail

Land Use








Now available:

Nothing in cities makes sense except in the light of accessibility. Transport cannot be understood without reference to the location of activities (land use), and vice versa. To understand one requires understanding the other. However, for a variety of historical reasons, transport and land use are quite divorced in practice. Typical transport engineers only touch land use planning courses once at most, and only then if they attend graduate school. Land use planners understand transport the way everyone does, from the perspective of the traveler, not of the system, and are seldom exposed to transport aside from, at best, a lone course in graduate school. This text aims to bridge the chasm, helping engineers understand the elements of access that are associated not only with traffic, but also with human behavior and activity location, and helping planners understand the technology underlying transport engineering, the processes, equations, and logic that make up the transport half of the accessibility measure. It aims to help both communicate accessibility to the public.


Still available …
In this book we propose the welcome notion that traffic—as most people have come to know it—is ending and why. We depict a transport context in most communities where new opportunities are created by the collision of slow, medium, and fast moving technologies. We then unfold a framework to think more broadly about concepts of transport and accessibility. In this framework, transport systems are being augmented with a range of information technologies; it invokes fresh flows of goods and information. We discuss large scale trends that are revolutionizing the transport landscape: electrification, automation, the sharing economy, and big data. Based on all of this, the final chapters offer strategies to shape the future of infrastructure needs and priorities.

On the Second Amendment and the Right of Revolution

There are several reasons some people in the United States support the private ownership of guns. School shootings and the rest are unfortunate collateral damage of ensuring the principle of individual arms can be readily obtained.

Flintolock musket

The Second Amendment confusingly says

“A well regulated militia being necessary to the security of a free state, the right of the people to keep and bear arms shall not be infringed.”

It is not clear on what arms people can have. Almost everyone agrees people should be allowed to have knives and muskets. Almost everyone also agrees no private nuclear bombs. I like the idea that original intent of the word “arms” means that no weapons invented since 1789 are implicitly constitutionally covered. The current interpretation of the second amendment is a modern one.

In addition to the “well regulated militia” rationale, there are other reasons people might want guns, including:

  • Personal Self-defense
  • Hunting
  • Committing crimes (some of which is self-defense while doing illegal things)
  • Over-throwing a `tyrannical’ government (which also relates in part to self-defense when rebelling against a well-armed opponent, as well as offense against the same opponent). This is also known as the “right of revolution.” It is discussed in this Federalist article.

I believe most gun supporters are, in fact, though most won’t admit it, about the last point. That is, their minds foresee a dystopian outcome when a fascist (or communist, but same thing) comes to power and must be resisted by weapons that have yet to be confiscated by a weak liberal regime.

The Civil War is a morally repugnant example of this kind of resistance, in that case by a south defending slavery; but one can equally imagine a world where a slightly less demographically and economically powerful  north was resisting imposition of slavery  by the southern states.

Or, their mind foresees the US being invaded by a foreign (or alien) army which somehow the military was unable defeat. Having grown up in the 1980s and seeing Red Dawn and V, I have some empathy for that view in principle. In practice, not so much.

Yet, if you are right wing, and believe the previous administration was the illegitimate dystopia that fuels your nightmares, where was your uprising? I missed it. If you are truly anti-fascist, where is your uprising now? You, gun-owners of America, are as well-armed as any citizenry in history. The US government’s ICE brown shirts are taking people from their homes and deporting them. Police officers are systematically killing people of color. And gun owners are not systematically challenging them. Hmm. Oh, I missed the part that it was the right of revolution for white people.

Which leads me to the conclusion that over-throwing the US government with the citizenry’s privately owned weapons is just not going to happen. Which means, we can strike the justification of needing guns for keeping the government in check. At this point in history, the US government can keep the populace in check, even if armed. At best you can take someone out before being killed yourself. You will not actually win.

The counter-argument is that it is the well-armed citizenry that is keeping the government in check, and thereby keeps it from confiscating guns (and eliminating other freedoms, but those are secondary to the guns). But if that were true, they wouldn’t be worried about the government confiscating guns. The reasoning is circular. The reason to have guns is to keep the government from confiscating your guns. If the government could confiscate your guns at any time with a change in legislation, the guns aren’t actually buying you your freedom. Instead it is that the government cannot effectively act without the consent of the governed.

Since the ‘committing crimes’ is also not really a good reason to keep guns, and ‘hunting’ doesn’t require sophisticated weapons, and ‘personal self-defense’ with guns is only necessary because everyone else also has guns and may be committing crimes, the US should just throw in the towel and follow the civilized world, or even Australia, and more significantly reduce access to firearms.

Sydney’s New Metro: A bonanza for Sydney residential and commercial property buyers or not?

I was interviewed by Clarissa Sebag-Montefiore for an article on Curtis Associates website: The Sydney Metro. A bonanza for Sydney residential and commercial property buyers or not? My quotes below:

Professor Levinson adds: “One reason, I am told, that the government chose the Metro over trains for the new lines is that because it is a different technology, it will be easier to manage separately from Sydney trains (and will be privately operated under contract). It was a technology choice to achieve a policy aim of breaking the existing bureaucracy and labour unions.”

“To help ensure the political separation, the tunnels for the Metro line are just a bit too short, and the tracks too steep, for double-decker trains to use. This could have been remedied at little or no cost, providing future technological flexibility, but the government want to reduce the flexibility of future governments,” he continues.

“Flexibility would have been a potential benefit from providing compatibility. On the other hand, separation has some value from a reliability perspective, problems on the train lines should not cause problems on the Metro (except for crowding where people have a choice between the two), and vice versa.”

As Professor Levinson, professor of transport at the University of Sydney points out: the “game is the same. Just more territory is brought into the game.”

“Since the lines and stations for the Metro North West and City/South-West are already set, the landowners have already realised their price appreciation,” he says. “There is still a small fortune to be made on the Metro West line, since where the stations land is still not set.”


Full Interview below:

What are the problems with the current [Public Transport] system?

First, the rail system in Sydney, though like all systems engendering complaints, is actually really good, reflecting on the genius of Bradfield’s original rail plan. The evidence for this is the high public transport mode share in Sydney compared to other Australian (and similarly sized US) cities. That said, it is far from perfect. The signal system on the rail lines should be modernized to increase safety and throughput. The bus network needs to be completely rethought and streamlined, so the routes don’t go hither and yon. More on-street right-of-way should be designated exclusively for buses so they move faster and are less likely to be stuck in traffic. Tap-on, tap-off should be off the bus (at the bus stop) so that the buses can board and alight more quickly. The system as a whole needs more capacity in places. The rail stations should be modernized with more exits so the access time to and from stations is shorter, and so there are lifts for each platform.

Why has it taken this long to find a solution?

There have been fits and starts on expanding public transport in Sydney for decades (nearing a century on Bradfield’s plan, which is still not built out). The best theory I heard is the city exhausted itself with all the over-building for the 2000 Olympics, and then couldn’t get anything going until recently. These lines are on the maps and have been for decades, so it’s a question of money and willpower. The recent government has been far more keep to use the private sector for financing, and using asset recycling than previous governments. The advantage to private financing and control is that the infrastructure is sort of “off-the-books”, so since it is privately funded, users pay directly, as opposed to being intermediated through the political layer. This makes it easier to charge users more. This is especially the case for toll road construction as opposed to untolled motorways, but could be applied to public transport as well.

What has been confirmed / what are we still waiting to find out?

Sydney Metro Northwest is well under construction.

Sydney Metro City and Southwest, replacing the T3 Bankstown Line, is in engineering and early construction. What happens to service at the end of the existing T3 line (beyond Bankstown, e.g. Yagoona and Birrong) that is not served by Metro is unclear.

Sydney Metro West is in early planning stages, and the line has not been set, but some of the stations are locked in.

What are the challenges facing the new metro? Critics have pointed out that it is flawed – why?

The issue of Metros vs. Double-Decker Trains is a technology choice which has some practical tradeoffs. Metros have fewer seats (1 deck) and more doors, but a greater capacity, because they can run more frequently (because they can board and alight much faster, and because they are automated with modern signal controls). So for a short trip, fewer seats might be fine, since you save time. For a long trip, not being able to sit in rush hour, but standing for say 40 minutes, might be a bit tiresome for some people (noting that this is common in transit systems around the world). So one of the questions is whether this (Metro) technology is right for this (very long) corridor. I suspect there will be grumbling from people who want to sit and can’t.

One reason, I am told, that the government chose Metro over Trains for the new lines is that because it is a different technology, it will be easier to manage separately from Sydney trains (and will be privately operated under contract). It was a technology choice to achieve a policy aim of breaking the existing bureaucracy and labour unions.

To help ensure the political separation, the tunnels for the Metro line are just a bit too short, and the tracks too steep, for Double-Decker trains to use. This could have been remedied at little or no cost, providing future technological flexibility, but the government want to reduce the flexibility of future governments. See: link

Flexibility would have been a potential benefit from providing compatibility. On the other hand, separation has some value from a reliability perspective, problems on the train lines should not cause problems on the Metro (except for crowding where people have a choice between the two), and vice versa.

Sydney is the first Australian city to build a metro system. What does this mean for Sydney as a city? And for its inhabitants?

Not much. Note: Melbourne is also building a Metro. (Metro Tunnel). The distinctions between trains and Metro will not be terribly significant for most  users, they will just see it as new and old trains.  Now in the corridor that gets new service (especially the Northwest) this is new service (replacing buses rather than trains), so should increase people’s willingness to take transit for certain city-oriented trips. It will also encourage development in the corridor around stations.

What does this mean for property owners / property developers? Which suburbs will suffer and which will benefit? And how is current uncertainty over the lines affecting property / developers / homeowners? How does “value capture” come into play?

Value capture is way to help finance transport infrastructure by using property value appreciation to offset construction costs. This is not done systematically in Sydney, but should be. There are various techniques. (See my value capture study from about 9 years ago, still true)

Is the metro a game changer? i.e will it give massive buying opportunities for previously low density suburbs? Will only the long term gamblers benefit?

The game is the same. Just more territory is brought into the game. Since the lines and stations for the Metro NW and City/SW are already set, the land owners have already realised their price appreciation. There is still a small fortune to be made on the Metro West line, since where the stations land  is still not set.

One cabinet paper stated the Metro West project would trigger a high-rise boom, from the sale of development rights around a dozen new underground stations – what does that mean for standard of living?

It means people who want to live in new high-rises near Metros (and the evidence is there are many such people) will have more opportunities and pay lower prices, and people who don’t will be largely indifferent. The neighbours of those new high rises will suffer more traffic, but have better restaurants and shopping.

Will Metro West deliver on the promise of housing, jobs, and business opportunities?

Jobs will come from construction, but Sydney is pretty close to full employment now, so if that remains so, it will attract workers for these jobs who otherwise would be working on something else, driving up the costs of construction and increasing inflation.

Sydney will not become significantly larger due to MetroWest (i.e. it won’t cause more babies to be born or increase national immigration, it might keep a few people in Sydney who otherwise would have gone to Perth or Hobart or wherever). However development with Sydney will likely concentrate around new stations to take advantage of the convenient accessibility the system provides, so station areas will attract housing and jobs that otherwise would have been more dispersed.

How does the new metro reflect on the building of new roads, such as WestConnex, largely funded by the tax payer? Why wasn’t the Metro West rail project wasn’t considered as an alternative to WestConnex.

I don’t know. The answer to these questions is usually “Follow the money.”

Up or Out: Travel Demand and Thirty Minute Cities

Adapted from Levinson, D. and Krizek, K. (2017) The End of Traffic and the Future of Access. Network Design Lab. Cross-posted on the ITLS Thinking Outside the Box  blog.

Each technological advance in mobility over the past 200 years increased the size of metropolitan areas. The ability to go faster, either owing to new technologies or more completely deployed and deeply connected networks, allowed people to reach more things in less time. The Underground drove the expansion of London, streetcars did the same for many American cities,[a] while trams and trains made Sydney, Melbourne, and Brisbane among others, and highways have exploded the size of cities everywhere. Historically, the time saved from mobility gains was reflected mostly in additional distance between home and the workplace, maintaining a stable commuting (home to work) time.

Will autonomous vehicles follow the path well worn by earlier technologies?

Fast, driverless cars that allow their passenger to do things other than steer and brake and find parking impose fewer requirements on the traveler than actively driving the same distance. Decreases in the cost of traveling (i.e., the availability of  safe in-vehicle multitasking) makes travel easier. Faster roads arise because of capacity gains from vehicle automation (due both to closer following distances and narrower lanes, even more practical with narrower vehicles fit to serve the single passenger they usually carry). Easier travel means increases in accessibility and subsequently increases in the spread of development and a greater separation between home and work, (pejoratively, `sprawl’), just as commuter trains today enable exurban living or living in a different city.[b] Autonomous automobility reinforces the disconnected, dendritic suburban street grid and makes transit service that much more difficult (as if low density suburbs weren’t hard enough). People will live farther ‘Out.’

However, concomitant with automation is the emergence of the sharing economy, with at least some people transitioning from today, where the typical Australian owns their own car, to mobility-as-a-service (MaaS) — automated taxis. This is more likely in larger, central cities where taxis are common, auto ownership is already difficult, and parking scarce and expensive. In this world, while the total cost of travel drops as vehicle ownership costs disappear, the cost per trip might rise, as the cost of ownership is allocated to each trip. This reduces travel demand.

Driverless cars which can be summoned on-demand allow people to avoid vehicle ownership altogether. This reduces vehicle travel, as people will pay more to rent by the minute than exploit the sunk costs of vehicular ownership. By saving total expenditures on transport, more funds are available to pay for rent in cities, and more trips are by walk, bike, and transit. People who seek the set of urban amenities (entertainment, restaurants, a larger dating pool) will find these amenities increasing in response to the population. The greater value in cities with the new more convenient technology leads to more and taller development. (Hence the use of the word ‘Up.’)

At first blush, ‘Up’ and ‘Out’ appear to be contrasting scenarios; they are not exclusive, however. More people living in the outer suburbs or exurbs does not mean fewer people live in cities, because the overall size increases (with more people overall). Sydney for instance, is expected to grow from just over 5 million to about 8 million people over the next four decades.

Similarly, as the cost of travel decreases, people will be more willing to live in locations far from where they work. At safe speeds of 160 km/h on freeway lanes exclusively dedicated to automated vehicles, the commuting range expands widely. From Sydney in this new world, Newcastle can be reached an hour on road, and Kiama and Katoomba are even nearer.

Sydney planners have recently proposed the benchmark of the “30-minute city“, the idea that most people can find work, school, or daily shopping within 30 minutes of their homes by walk, bike, or transit. The threshold of 30-minutes is roughly equal to today’s one-way commute in Sydney (actually 35 minutes), shorter by car (26 minutes), longer by train (62 minutes) according to BITRE. The long times by train are because trains are designed to serve longer distance trips, and focus on the Central Business District.

The End of Traffic and the Future of Access: A Roadmap to the New Transport Landscape. By David M. Levinson and Kevin J. Krizek.
The End of Traffic and the Future of Access: A Roadmap to the New Transport Landscape. By David M. Levinson and Kevin J. Krizek.

The 30-minute city 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.

If the 30-minute city is defined for walk, bike, and transit as the relevant modes, with mobility-as-a-service easily available on-demand, the Up Scenario works best, though getting one-way commuting times for train users down from 60 to 30 minutes is a large ask. In contrast, the Out Scenario can continue to enable a 30-minute city for privately owned autonomous vehicles so long as jobs don’t centralize further in downtowns.

The interplay of AVs and road pricing is especially important. While autonomous vehicles may eventually double or quadruple road capacity, total demand will rise as well due to population growth, so long as people continue to work, shop, and play outside-the-home at today’s rates, even more if traditional patterns of induced demand hold.

It is quite possible that sharing remains a niche while most people choose to own their own cars — the ‘Out’ scenario dominates. Thus, exurbanization and AVs better leverage newly available capacity. But, in the absence of pricing, and with cheap energy, there is little to discourage tomorrow’s privately owned AVs from circulating empty on the road network rather than pay for high prices of parking, and thereby slow travel for everyone else. This possible outcome is so obviously bad, it suggests road pricing or similarly effective regulation in some form is likely.


[a] See Levinson, D. (2008). Density and dispersion: the co-development of land use and rail in London. Journal of Economic Geography, 8(1), 55-77 and Xie, F., & Levinson, D. (2009). How streetcars shaped suburbanization: a Granger causality analysis of land use and transit in the Twin Cities. Journal of Economic Geography, lbp031.

[b] For more on this reasoning, see Chapter 11 in Levinson, D. and Krizek, K (2008)  Planning for Place and Plexus: Metropolitan Land Use and Transport. Routledge.