Transportist: December 2021

Books

Now available for download: Applications of Access.

Applications of Access edited by David Levinson and Alireza Ermagun

About

Our open access book Applications of Access, edited by David Levinson and Alireza Ermagun has launched!

Applications of Access was inspired by our belief that planning should reach beyond mobility and incorporate all intricacies of reaching your destination. We set out to publish a book examining topics such as (1) Equity and social justice, (2) Resilience and crisis, (3) Active transport, (4) Public transport, (5) Auto travel, (6) System performance, and (7) Project evaluation.

But this book is not intended to simply be a “how to” manual, but rather to inspire researchers, practitioners, and policymakers to spark a broader array of research and practice in the nexus of transport access.  
This was a labor of love that included the work of many of our colleagues and thought leaders in the transport community. We are thrilled to finally be able to share our work with you, and we hope to embolden our greater transport community to examine access through the many lenses that impact our daily commutes and quality of life.

Table of Contents

1 An Introduction to Applications of Access
Alireza Ermagun and David Levinson 15

2 Fostering Social Equity and Inclusion
Pâmmela Santos and Geneviève Boisjoly 23

3 Justice, Exclusion, and Equity: An Analysis of 48 US Metropolitan Areas
Chelsey Palmateer and David Levinson 45

4 Disparity of Access: Variations in Transit Service by Race, Ethnicity, Income, and Auto Availability
Elisa Borowski, Alireza Ermagun, and David Levinson 69

5 Access During COVID
James DeWeese, Kevin Manaugh, and Ahmed El-Geneidy 87

6 Access to Shelters
Mahyar Ghorbanzadeh, Kyusik Kim, Eren Erman Ozguven, and Mark Horner 105

7 Access and Centrality-Based Estimation of Urban Pedestrian Activity
Brendan Murphy, Andrew Owen, and David Levinson 117

8 Which Station? Access Trips and Bikeshare Route and Station Choice
Jessica Schoner and David Levinson 133

9 Cargo Bikesharing as a Last-mile Connector
David Duran-Rodas, Aaron Nichols, Benjamin Büttner 149

10 Spatio-temporal Transit Access to Food Stores
Xiaohuan Zeng, Ying Song, and Na Chen 165

11 Multi-destination Access
Andrew Guthrie and Yingling Fan 193

12 Non-work Vehicle Trip Generation from Multi- week In-vehicle GPS Data
Arthur Huang and David Levinson 217

13 Job Access and Spatial Equity of a Toll Road
I Gusti Ayu Andani, Lissy La Paix, Shanty Rachmat, Ibnu Syabri, and Karst Geurs 239

14 Access and Transit System Performance
Alireza Ermagun and David Levinson 261

15 Intraurban Access and Agglomeration
Michael Iacono, Jason Cao, Mengying Cui, and David Levinson 277

16 Transit Access Performance Across Chicago
Fatemeh Janatabadi, Nazanin Tajik, and Alireza Ermagun 291

17 Interactive Access for Integrated Planning
Anson Stewart and Andrew Byrd 307

18 The Role of Transit Service Area Definition for Access-based Evaluation
Chelsey Palmateer, Alireza Ermagun, Andrew Owen, and David Levinson 327

19 Access-based Evaluation of Transit-Oriented Developments
Chelsey Palmateer, Andrew Owen, and Alireza Ermagun 347

20 Physical and Virtual Access
Tanhua Jin, Long Cheng, and Frank Witlox 363

Editors and Contributors 377

Bibliography 387

FEATURES

  • 424 Pages
  • Publisher: Network Design Lab

DOWNLOAD

Geo-Engineering Wars

“It’s 2040, and while annual carbon emissions have been dropping for decades, planet Earth remains nowhere near net zero, and CO2 continues to accumulate in the atmosphere. Global institutions have failed (again) to resolve the issue.  Temperatures are rising. Glaciers are melting. The permafrost is a lot less perma. Sea-levels are rising. Fires are increasing. Tensions are rising.

This affects some places more than others, and those governments take it upon themselves to mitigate the effects. The once fringe field of geo-engineering, attempting to control the earth’s climate, has come to the fore. From relatively innocuous technologies like carbon capture and afforestation, to more radical attempts at blocking the sun and adding iron to the oceans are leaving the simulator and being tested in the field.”

That was a blog post I started a couple of years ago and never finished. Two new novels have finished it (and I have finished them). Kim Stanley Robinson’s “Ministry for the Future” and Neal Stephenson’s “Termination Shock” both deal with Climate Change, Geo-Engineering and the conflicts around them. Just as the cyberpunk novels of the 1980s predicted our era surprisingly presciently, I believe the new climate novels will help lay the groundwork for openly discussing the still verboten topic of geo-engineering once we realise we are going to have unacceptable climate if we rely on public policy, emissions reduction, and technology substitutions alone.

Speaking of which, I did the following Twitter poll: 

Considering global change and the desire to stay below 1.5C temperature rise from the baseline. Which of the following will ensure that. Tech includes substitutions (EVs, Solar, etc.) and Carbon Capture and Storage etc. of various types:

  • Technology changes 11.1%
  • Behavioural changes 14.8%
  • Technology + Behaviour 63%
  • Nothing 11.1%

More on: How to value transport projects

Following up on the October newsletter:

JW:

In your newsletter today you seem to argue that land value uplift is a reliable reflection of access, so that access can be measured either directly or through the value the real estate market places on it.

I was puzzled about this, because the real estate market clearly has all the stupidity of any investment bubble. US streetcars increased land value even when they provided no access, for no other reason than that access-ignorant investors believed that they did.

Do you believe, then, that land value tends to reflect access in the longer run? This would require believing that the effects of marketing are temporary but that access is a permanent value and thus tends to count for more after the marketing wears off. That’s my view, but it’s more an abstract philosophical assumption than something I could support with data.

This probably deserves textbook length treatment, more than a newsletter in any case, but my view in brief:

Land values are a good measure of relative value in the short and long run, better in the long run than the short run if only because the number of transactions is larger and the marginal value of the particular buyers at a given time will lead to speculative excesses (optimism and pessimism) and when averaged over time will more closely approximate the average value of all prospective land owners. 

Value is determined by people (the subjects), not by the observer (the modeler), and their weights on access to different types of things varies over time (yesterday it was jobs, today beaches matter more, tomorrow it will be a particular public school, the day after that it will be access to snooty neighbours). The land market summarises their willingness to pay to access to everything, though the modeller can at best capture only a limited amount of that (concrete things like jobs and beaches, assuming they don’t change). So our model of 

land value = f ( access)

Won’t have an $R^2$ of 1, but it is better than most people would think (we routinely can get $R^2$ of 0.7 in these kinds of models on individual properties with access and all the typical property attributes, it might be better if we aggregate to neighbourhood level land values).

The key point though isn’t the absolute but the relative value.

The government will dial in the amount of revenue they want to receive, and allocate taxes proportionate to land value (i.e. proportionate to measurable access), and that would be far superior to anything we are doing now.

Two questions:

* When you talk about relative land value are you talking about delta of land value? Or value of a parcel relative to other parcels of the same size and with other differences controlled for? I’m guessing the latter. So the land value variable is a ratio (or absolute difference?) to some baseline rather than a \$ amount?

* In your formula land value = f (access), there are, as you say, many kinds of access (both destinations and travel time thresholds) that could be calculated. Do you achieve this high r-squared by querying the market about how different kinds of access are weighted, and if so how is this not circular? If not, how do you define this variable?

I meant relative across places. The absolute land value is just an arbitrary price (how much people value land compared to travel or tourism etc.), and sometimes real estate rises faster than the economy as a whole (or changes in access dictate) and sometimes slower, and depends on things like tax policy and interest rates. 

The proportion of total (say metropolitan) real estate value associated with each place is largely proportional to its access to things. I recognise what things people value is in a large sense arbitrary too (cafes vs brothels vs stadiums etc.), compared with other places in the same metropolitan area, but I suspect it is more stable in the long run, with slower changes over time as preferences and technology change, for instance we would expect the value of access to office buildings dropping over time as work from home becomes more common. 

We have used different kinds of access. It turns out transit access (30 or 45 minutes) seems to be the best predictor in Sydney (explain the most variation) if you have only one measure. We think this is because auto access is fairly invariant across the region, while transit access concentrates pretty highly. I have attached a working paper (currently under review, not for citation or sharing). 

The statistical issue with having lots of access measures in a single regression is autocorrelation … access to jobs is not really that independent of access to shops or access to restaurants etc, and access by bike is similar to access by auto, etc.

The idea here is ensemble models, this paper is a just a starting point. Different models are estimated with different clusters of variables and different statistical methods. The model predictions are combined, and this improves the prediction compared with any single model.

JB:

Regarding the below, do you think that the same principles apply to freight projects in regional/rural areas? And if yes, do you think they would have a significant impact on their valuations?

Yes in principle. It may be harder to capture the land value benefits or determine the accessibility changes associated with industrial or mining or agricultural land with a freight-oriented highway or rail project (though I haven’t really tried). But the general idea of taxing land should capture an appropriate fraction of the benefits that arise.

I don’t know the NSW context well enough, but in the US I also tend to think that today’s freight projects (compared with 60 years ago) don’t add much value. Widening (i.e duplicating) an uncongested 2 lane to a very uncongested 4 lane road adds nearly zero time savings value for freight (a little bit more for non-freight traffic which can overtake the slower moving freight), and may or may not make things safer, depending. A new bridge or tunnel is likely to be more significant. 

Adam Smith talked exactly about the value of agricultural land rising after turnpikes and canals were built in the 1700s.

TL: 

I would add that improvements to more affordable and slower modes, and the disadvantaged groups that rely on them, help achieve social equity goals more than comparable size improvements to expensive and faster modes.

I would also add that the analysis should consider indirect and down-stream impacts. For example, a highway expansion assumes that beneficiaries will use an automobile, and that somebody will provide parking at their destinations, costs that are reduced or eliminated if the same travellers arrive by biking, ridesharing or public transit. Project cost comparisons often overlook those impacts, which further exaggerates highway expansion benefits.

More of a comment than a question, but indeed they do.

Types of Problems

  • Via Kevin Kelly: Class 1 / Class 2 Problems “There are two classes of problems caused by new technology. Class 1 problems are due to it not working perfectly. Class 2 problems are due to it working perfectly.” Apply this to AVs.

What Remains Unknown in Transport and Land Use Research

I asked on Twitter:

Q: What do we *not* know about transport and land use interaction, that is knowable?  I don’t meant the third digit of precision on some relationship, but more fundamental things?  What are the big unanswered questions?

Some responses below. I am not sure I agree with these. I am not sure I have a strong opinion on what are the big unanswered questions? Maybe we know everything and we just need to put it in practice.

Patrick Zilliacus

act of NIMBYism (not in my back yard), PIITBYism (put it in their back yard), PIBBY (place in blacks’ back yard), BANANA (build absolutely nothing anywhere near anything) and CAVE (citizens against virtually everything) is worthy of more and better research.

Juste Raimbault

A general theory and models of co-evolution of land-use and transport: circular causal relationships seems overlooked – these occur on multiple temporal and spatial scales. When does transport drives land-use, when does land-use drives network development, when do both strongly interact and are in circular causality? Also the role of governance in transport network growth-we did some preliminary work on that here

David King

I think a lot of what we know is based on a strong transport/land use interaction. If that relationship is weakening, then much of what we do know may not matter as much.

We also know less about transport/land use with many transport providers/price setters (e.g. fees/tolls).

Jago Dodson

I would argue we don’t know the isolated effect of the automobile on land-use and transport. It’s almost impossible to fully exclude as a variable among the historical development of urban structure. What would a zero-car contemporary city be like? We can guess, but not know.

James Milne

The full relationship between residential and workplace density vs % active and public transport use vs number of small businesses in a given location. Or in other words, the “formula” for a 15minute city.

Vic Walks

Governments very interested in job creation through construction, but seems almost no research on job creation in construction of walking and cycling infrastructure

Josephine Roper

How important it is or is not for wellbeing and happiness for people to live close to people they know. Because this has implications when we assume that people will or should efficiently relocate to be near the destinations (land use) they need to access

Tamara Kerzhner

Agreed – we underconsider social and personal life travel. Frame it as “access to social capital” and “mobility of household reproduction” if it gets it past the economists.

Mikael Valstead

The full societal cost of driving a car (health, noise, inactivity, CO2 and other GHGs, micro plastic from tires, destruction of housing and green areas, congestion, etc.)

Peter Rickwood

The political economy of land-use/transport. Government action is absent or poorly understood in transport/land-use theory and modelling, but in practice very important (zoning, infrastructure spend, value-capture & congestion charges, user fee structure, etc).

Soren Have

[rewritten] Why does the amount of land devoted to transport purposes keeps growing.

John Macilree

That land use for airports involves a much larger area than the physical confines of the airport property when noise and glide slope considerations are taken into account. That land developers see related vacant land and will try to use political pressure to exploit this land.

Recent Research by Others

  • Ryerson, Megan S., Carrie S. Long, Joshua H. Davidson, and Camille M. Boggan. “New Rules for Old Roads.” Issues in Science and Technology 37, no. 2 (Winter 2021).“Collecting and analyzing biometric data from nonmotorists would shift the way safety is measured by the entire transportation and public health community—with implications for infrastructure policy and design.”

News

Applications of Access

Now available for download: Applications of Access.

Applications of Access edited by David Levinson and Alireza Ermagun

About

Our open access book Applications of Access, edited by David Levinson and Alireza Ermagun has launched!

Applications of Access was inspired by our belief that planning should reach beyond mobility and incorporate all intricacies of reaching your destination. We set out to publish a book examining topics such as (1) Equity and social justice, (2) Resilience and crisis, (3) Active transport, (4) Public transport, (5) Auto travel, (6) System performance, and (7) Project evaluation.

But this book is not intended to simply be a “how to” manual, but rather to inspire researchers, practitioners, and policymakers to spark a broader array of research and practice in the nexus of transport access.  
This was a labor of love that included the work of many of our colleagues and thought leaders in the transport community. We are thrilled to finally be able to share our work with you, and we hope to embolden our greater transport community to examine access through the many lenses that impact our daily commutes and quality of life.

Table of Contents

1 An Introduction to Applications of Access
Alireza Ermagun and David Levinson 15

2 Fostering Social Equity and Inclusion
Pâmmela Santos and Geneviève Boisjoly 23

3 Justice, Exclusion, and Equity: An Analysis of 48 US Metropolitan Areas
Chelsey Palmateer and David Levinson 45

4 Disparity of Access: Variations in Transit Service by Race, Ethnicity, Income, and Auto Availability
Elisa Borowski, Alireza Ermagun, and David Levinson 69

5 Access During COVID
James DeWeese, Kevin Manaugh, and Ahmed El-Geneidy 87

6 Access to Shelters
Mahyar Ghorbanzadeh, Kyusik Kim, Eren Erman Ozguven, and Mark Horner 105

7 Access and Centrality-Based Estimation of Urban Pedestrian Activity
Brendan Murphy, Andrew Owen, and David Levinson 117

8 Which Station? Access Trips and Bikeshare Route and Station Choice
Jessica Schoner and David Levinson 133

9 Cargo Bikesharing as a Last-mile Connector
David Duran-Rodas, Aaron Nichols, Benjamin Büttner 149

10 Spatio-temporal Transit Access to Food Stores
Xiaohuan Zeng, Ying Song, and Na Chen 165

11 Multi-destination Access
Andrew Guthrie and Yingling Fan 193

12 Non-work Vehicle Trip Generation from Multi- week In-vehicle GPS Data
Arthur Huang and David Levinson 217

13 Job Access and Spatial Equity of a Toll Road
I Gusti Ayu Andani, Lissy La Paix, Shanty Rachmat, Ibnu Syabri, and Karst Geurs 239

14 Access and Transit System Performance
Alireza Ermagun and David Levinson 261

15 Intraurban Access and Agglomeration
Michael Iacono, Jason Cao, Mengying Cui, and David Levinson 277

16 Transit Access Performance Across Chicago
Fatemeh Janatabadi, Nazanin Tajik, and Alireza Ermagun 291

17 Interactive Access for Integrated Planning
Anson Stewart and Andrew Byrd 307

18 The Role of Transit Service Area Definition for Access-based Evaluation
Chelsey Palmateer, Alireza Ermagun, Andrew Owen, and David Levinson 327

19 Access-based Evaluation of Transit-Oriented Developments
Chelsey Palmateer, Andrew Owen, and Alireza Ermagun 347

20 Physical and Virtual Access
Tanhua Jin, Long Cheng, and Frank Witlox 363

Editors and Contributors 377

Bibliography 387

FEATURES

  • 424 Pages
  • Publisher: Network Design Lab

DOWNLOAD

The End of Traffic and the Future of Access | Spontaneous Access: Reflexions on Designing Cities and Transport | Elements of Access: Transport Planning for Engineers, Transport Engineering for Planners | A Political Economy of Access | The 30-Minute City: Designing for Access | Transport Access Manual | Applications of Access

The Unprotected Left (right) Turn

It is said the unprotected left turn (right turn in left-hand drive countries like Australia, but I will write as an American here) is hard for autonomous vehicles (AVs). (Even ignoring pedestrians, which magnify the complexity if there were to be treated as full-fledged users rather than an after-thought.)

With an unprotected left turn there is ambiguity about whether gaps between vehicles are large enough for the AV to squeeze through safely, and whether oncoming traffic will yield to an attempt to cross, particularly as the wait gets longer and longer and the passengers in the turning vehicle become more and more impatient.

It’s hard for humans too, left-turns comprise a quarter of all pedestrian crashes. So why do we have it? I.e. why don’t we protect the left turn.

It is  a matter of vehicle delay and storage space. On a one lane per direction road, or even a two lane per direction road, vehicles that are queued to turn could block vehicles that might otherwise go straight (or vice versa) when there is no turn bay and they don’t simultaneously have a green.  

We could have a phasing configuration which gave each approach (North, South, East, West (N, S, E, W)) its own green time.  In this  case, if flows were more or less equal between left turns and through/right movements, this might be the optimal solution. But if flows were dominated by one or the other, then it would be less than efficient. 

Alternatively, if we have turn bays (dedicated turn lanes) to keep vehicles out of each other’s way, we could have a configuration (N/S Through/Right, N/S Left, E/W Through/Right, E/W Left) which paired the turns. But turn bays use up lots of space that could be alternatively used for just about anything than temporarily storing cars.

And of course these could be mixed (N/S Through/Right, N/S Left, E, W) depending on relative flows.

But if the North flow > South or East flow > West (or vice versa), then these strategies will leave large gaps that could have been used by crossing traffic, but weren’t because the signal wasn’t timed for it.

With sufficient real-time information about flows, the signals could be adjusted to turn the lower flow approach to red when there are no vehicles approaching to protect the higher flow approach. This information requires knowing total approaches, but would be more accurate if the number on each turn (left, through, right) were also known, but this might be hard to discern simply by their location if the use of turn signals is imperfect, and there are too few dedicated lanes.

Update: We could prohibit left (right) turns. This is down in Moscow, so I understand. The left-turn ban at intersections is useful with low-rate flow turning left, assuming all left-turn vehicles are willing to do right turns several times to get to their destinations. But, this may impose a heavy burden of additional traffic on other road sections.

Or we could just have more roundabouts. These create other issues.

Porsche waiting to make a left turn, despite a presumably high value of time.

Sydney’s Traffic Returning to pre-COVID Levels as Driving Skills Deteriorate | SMH

Andrew Taylor in the SMH writes: Sydney’s traffic returning to pre-COVID levels as driving skills deteriorate

My quotes:

But David Levinson, professor of transport engineering at the University of Sydney, said: “In general low traffic levels lead to higher speeds and to more dangerous driving, so as traffic returns to normal, we may see lower rates of fatal and injury collisions per kilometre travelled.” …

Professor Levinson said empty CBD offices meant train carriages would also continue to be empty.

“Walking to work is also much more common for people in high-density areas, which are more likely still to be places where workers are effectively locked out,” he said. “And if the CBD is relatively empty, driving and parking there is not as difficult.”

My own sense is the trains are indeed pretty damn empty compared to the before-times, and driving still feels down (though not as down) in my observation. Traffic counts are taken at specific locations, and I am not sure any one data source is right on this.

TRANSPORTIST: OCTOBER 2021

How to value transport projects

Instead of measuring and monetising the fairy dust of `travel time savings’, a transport facility should be assessed on how much access it produces per unit of investmentAccess is the ease of reaching destinations. E.g. you might measure how many jobs (or restaurants or hospitals, etc.) can be reached in 30 minutes and/or $5 (or the dual of this measure, such as how many prospective patients an ambulance can reach in 12 minutes). A transport facility that increases access to destinations for a cost effectively is good. 

So the question is: does a streetcar or road or bike path enable people to reach more activities in less cost (time, money, aggravation, risk, negative externalities, etc.) than before, at a reasonable expenditure? (This cost includes the social and financial costs of building and providing the infrastructure). In short, are the upfront capital costsand ongoing maintenance and operations costs of the facility justified by the lower variable costs of its users? 

Sometimes (which is to say, often) transport projects are promoted for real estate. Real estate prices monetise the transport benefits (above what the user bears in time, money, and effort) in land value (time savings are not actually money, they become money through land value). We can build models that estimate the real estate value provided by additional accessibility.

So a better way of assessing the transport benefits is through real estate price uplift, as the market captures how people value the transport benefit. (We cannot simply add land prices to travel time and travel cost reductions, as that would be double counting). Places with higher access, and where access is more valuable, are more expensive and more productive and pay higher wages. We don’t really need to understand the detailed market mechanisms, nor attribute costs to detailed categories, the land market tells us how much access is worth, and transport models tell us how much access is created by a change to the network – from those two facts we can estimate the value created.

Because many projects are promoted by real estate interests, who presumably believe they will get the monetized benefits of those projects through higher land values, the public has a reasonable expectation that those interests pay for the costs of the project (that is, the tax incidence falls on the land owner). There are a variety of approaches, generally lumped as value sharing or value capture. The most general of these, a land value tax, originally promoted by Henry George, captures all of the uplift caused by all the access created by both transport investments and changes in the distribution of human activities.

From a project assessment point-of-view, land value uplift has often been part of the ‘wider economic benefits‘, which are optionally added after the value of travel time savings, which is considered the main benefit. ATAP for instance writes:

WEBs are improvements in economic welfare associated with changes in accessibility or land use that are not captured in traditional cost–benefit analysis (CBA). They arise from market imperfections, that is, prices of goods and services differing from costs to society as a whole. Reasons include economies of scale and scope, positive externalities, taxation and imperfect competition.

The international literature to date has concentrated on four types of WEBs that arise from major transport initiatives.

– WB1: Agglomeration economies — productivity gains from clustering by firms

– WB2: Labour market and tax impacts — productivity gains accruing to governments via the taxation system

– WB3: Output changes in imperfectly competitive markets — profit increases for firms

– WB4: Change in competition — gains to consumers and more efficient production.

ATAP goes on to write: 

“WEBs are only likely to be significant, and so worth estimating, for sizeable transport initiatives located in or improving access to large urban areas”

This logic is backwards. Because of induced demand, road projects rarely actually ‘save time’. Transit is often slower than car, so creating a project that induces someone from car to transit also doesn’t save time, but must nevertheless be preferred if people voluntarily switch.

Yet despite not ‘saving time’, these projects do create economic value. From a consumer perspective for instance, people can find a better fit for housing in the same travel effort (and may prefer to ride passively than to drive), or can engage in shopping activities that better match their desires in the same time window. From a producers perspective, WB1-WB4 from above are all embedded in land value. 

In reality, WEBs are the benefits of transport. If there were no productivity gains from clustering, we would not have cities and instead choose to be maximally spread out, and not need to be proximate in any sense. If there were no gains to consumers from competition, everyone would pay monopoly prices for everything, etc.

And these WEBs do not show up in ‘travel time savings’ but consistently show up in land value (CBDs are more expensive than suburbs are more expensive than rural areas). The WEBs are implicit in the land value uplift which occurs as a result the increased access. ‘Wider economic benefit’, properly measured as land value gains due to increased access, can and should be considered the primary benefit of new investment, not a speculative add-on aimed at juicing the numbers.

The consequence of properly and completely valuing benefits and full costs systematically may very well be a higher benefits estimate than a travel time savings-dominated metric would produce, which, if decision-making were rational, would justify more construction of public and active transport than would otherwise take place. A tax system that captured the land value that was thus created could relax whatever financing constraints currently limit that investment.

Jobs

Research

  • Wu, Hao, and Levinson, D. (2021) The Ensemble Approach to Forecasting: A Review and Synthesis. Transportation Research part C. Volume 132, 103357 [doi
    • HIGHLIGHTS
      • Review and synthesize methods of ensemble forecasting with a unifying framework.
      • As decision support tools, ensemble models systematically account for uncertainties.
      • Ensemble methods can include combining models, data, and ensemble of ensembles.
      • Transport ensemble models have the potential for improving accuracy and reliability.
      ABSTRACT: Ensemble forecasting is a modeling approach that combines data sources, models of different types, with alternative assumptions, using distinct pattern recognition methods. The aim is to use all available information in predictions, without the limiting and arbitrary choices and dependencies resulting from a single statistical or machine learning approach or a single functional form, or results from a limited data source. Uncertainties are systematically accounted for. Outputs of ensemble models can be presented as a range of possibilities, to indicate the amount of uncertainty in modeling. We review methods and applications of ensemble models both within and outside of transport research. The review finds that ensemble forecasting generally improves forecast accuracy, robustness in many fields, particularly in weather forecasting where the method originated. We note that ensemble methods are highly siloed across different disciplines, and both the knowledge and application of ensemble forecasting are lacking in transport. In this paper we review and synthesize methods of ensemble forecasting with a unifying framework, categorizing ensemble methods into two broad and not mutually exclusive categories, namely combining models, and combining data; this framework further extends to ensembles of ensembles. We apply ensemble forecasting to transport related cases, which shows the potential of ensemble models in improving forecast accuracy and reliability. This paper sheds light on the apparatus of ensemble forecasting, which we hope contributes to the better understanding and wider adoption of ensemble models.
    • This paper is the first dissertation paper from Dr. Hao Wu’s Dissertation: Theory of Ensemble Forecasting – with Applications in Transport Modeling. Hao successfully defended last month. It’s hugely important for changing how modeling is done, instead of relying on the one best model, an ensemble of models is more accurate and more reliable. Transport modeling has spent decades developing advanced (and Nobel prize-winning) methods, but has fetishised a single model approach rather than embracing uncertainty and humility. This needs to change. [Hao is also, as far as I know, the first Transport Engineering PhD from the University of Sydney since JJC Bradfield, who designed the Harbour Bridge and the Sydney Trains network] “In 1924, Bradfield was awarded the degree of Doctor of Science (for a thesis titled “The city and suburban electric railways and the Sydney Harbour Bridge”, the first doctorate in engineering awarded by the University of Sydney.”
  • Allen, Jeff, Farber, Steven, Greaves, Stephen, Clifton, Geoffrey, Wu, Hao, Sarkar, Hao, and Levinson, D. (2021) Immigrant Settlement Patterns, Transit Accessibility, and Transit Use. Journal of Transport Geography. 96, 103187 [doi]
    • ABSTRACT: Public transit is immensely important among recent immigrants for enabling daily travel and activity participation. The objectives of this study are to examine whether immigrants settle in areas of high or low transit accessibility and how this affects transit mode share. This is analyzed via a novel comparison of two gateway cities: Sydney, Australia and Toronto, Canada. We find that in both cities, recent immigrants have greater levels of public transit accessibility to jobs, on average, than the overall population, but the geography of immigrant settlement is more suburbanized and less clustered around commuter rail in Toronto than in Sydney. Using logistic regression models with spatial filters, we find significant positive relationships between immigrant settlement patterns and transit mode share for commuting trips, after controlling for transit accessibility and other socio-economic factors, indicating an increased reliance on public transit by recent immigrants. Importantly, via a sensitivity analysis, we find that these effects are greatest in peripheral suburbs and rural areas, indicating that recent immigrants in these areas have more risks of transport-related social exclusion due to reliance on insufficient transit service.
  • El-Geneidy, Ahmed and Levinson, D. (2021) Making Accessibility Work in Practice Transport Reviews (online first) [doi]
    • ABSTRACT: Accessibility, the ease of reaching destination, is the most comprehensive land use and transport systems performance measure (Levinson & Wu, 2020; Wachs & Kumagai, 1973; Wu & Levinson, 2020). Accessibility has been applied in planning research since the 1950s (Hansen, 1959), and still today, we find major barriers to adopting it in practice (Handy, 2020). Advances in computing and software have enabled researchers to generate complex measures of accessibility with higher spatial and temporal resolutions moving accessibility research at a fast pace, while the implementation of accessibility, in practice, lags (Boisjoly & El-Geneidy, 2017). Even simple measures, such as the cumulative opportunities measures of accessibility, confront challenges in adoption.

Videos

Research by Others

Polls

  1. How long must someone be dead before we should stop referring to them as “the late so and so”? (reading newspaper article describing the “late Erik Erikson”, dead 27 years.) Or should we say the late Isaac Newton?
    • <1 year 18.6%
    • 1-4 years 34.3%
    • 5-9 years 11.4%
    • >10 years 35.7%
    The median is just under 5 years, so I will go with that. 

News & Opinion

Dr. Hao Wu

Congratulations to Hao Wu for “satisfying the requirements for the award of the degree of Doctor of Philosophy at the University of Sydney.”

Thesis Title: Theory of Ensemble Forecasting – with Applications in Transport Modelling 

Lead Supervisor: Professor David Levinson.

Abstract:

Ensemble forecasting is a modeling approach that internalizes uncertainties, combining models with different assumptions or pattern recognition methods, data from different sources, and different methods of combining models. Compared to the prevalent single-model procedure, ensemble model predictions are more useful as decision support tools.

The use of ensemble forecasting has significantly improved forecast accuracy in weather forecasting, and is increasingly adopted in other fields. We find a lack of awareness, or application of ensemble models in transport, so the benefits of ensemble forecasting are not being realized.

In this research we establish a systematic framework for ensemble forecasting, and propose the `ensemble of ensembles’ to combine uncertainties in different ensemble methods. Ensemble models are applied to transport-related cases to examine the performance of different ensemble methods, and to compare ensemble models with single-model forecasts.

We find ensemble models can improve forecast accuracy by a notable degree beyond the best single model. Simple and weighted average ensemble models have mixed results. Meta-learner ensemble models provide significant improvement upon base models, but require sufficient training data to calibrate. We find the linear meta-learner to be robust and have good performance even with small training data. Ensemble of ensembles method combining different ways of combining models improves performance upon ensemble models, and generally has the best performance.

We conclude that ensemble models, if properly applied, are able to improve model performance. We posit that transport modeling can benefit enormously from the wider adoption, and awareness of ensemble forecasting methods. We hope that this research opens the door to methodically adopting ensemble models into transport modeling, that future transport research can build upon.

Hao Wu

The first journal article published from the dissertation is:

  • Wu, Hao, and Levinson, D. (2021) The Ensemble Approach to Forecasting: A Review and Synthesis. Transportation Research part C. Volume 132, 103357 [doi]

The Ensemble Approach to Forecasting: A Review and Synthesis

Recently published:

  • Wu, Hao, and Levinson, D. (2021) The Ensemble Approach to Forecasting: A Review and Synthesis. Transportation Research part C. Volume 132, 103357 [doi] [Author Link]
  • Highlights

    • Review and synthesize methods of ensemble forecasting with a unifying framework.
    • As decision support tools, ensemble models systematically account for uncertainties.
    • Ensemble methods can include combining models, data, and ensemble of ensembles.
    • Transport ensemble models have the potential for improving accuracy and reliability.

    Abstract

    Ensemble forecasting is a modeling approach that combines data sources, models of different types, with alternative assumptions, using distinct pattern recognition methods. The aim is to use all available information in predictions, without the limiting and arbitrary choices and dependencies resulting from a single statistical or machine learning approach or a single functional form, or results from a limited data source. Uncertainties are systematically accounted for. Outputs of ensemble models can be presented as a range of possibilities, to indicate the amount of uncertainty in modeling. We review methods and applications of ensemble models both within and outside of transport research. The review finds that ensemble forecasting generally improves forecast accuracy, robustness in many fields, particularly in weather forecasting where the method originated. We note that ensemble methods are highly siloed across different disciplines, and both the knowledge and application of ensemble forecasting are lacking in transport. In this paper we review and synthesize methods of ensemble forecasting with a unifying framework, categorizing ensemble methods into two broad and not mutually exclusive categories, namely combining models, and combining data; this framework further extends to ensembles of ensembles. We apply ensemble forecasting to transport related cases, which shows the potential of ensemble models in improving forecast accuracy and reliability. This paper sheds light on the apparatus of ensemble forecasting, which we hope contributes to the better understanding and wider adoption of ensemble models.

    Fig. 1. Methods of combining data and models.

    SUCE SEMINAR – The End of Traffic and the Future of Access

    I will be giving a seminar to the Sydney University Civil Engineers group today: Tuesday September 21, 2021 from 17:00 to 18:00 AEST. Zoom link for the seminar: https://uni-sydney.zoom.us/j/89457527160

    Title: The End of Traffic and the Future of Access

    Abstract:

    Two decades into the new millennium, transport is becoming interesting again. New technologies are taking root and society is responding; together, these phenomena are changing how people access places and exchange goods. This talk about the future of transport in cities discusses the implications of automation, electrification, sharing, and COVID-19 on travel demands and transport policy.

    Bio:

    Prof. David Levinson teaches at the School of Civil Engineering at the University of Sydney, where he leads the Network Design Lab and the Transport Engineering group. From 1999 to 2016, he served on the faculty of the University of Minnesota where he held the Richard P. Braun/CTS Chair in Transportation (2006-2016). Levinson has authored or edited several books, including The 30-Minute City: Designing for Access, The Transportation Experience, and Metropolitan Transport and Land Use: Planning for Place and Plexus, as well as numerous peer reviewed articles. He is the editor of the journal Findings.

    [UPDATE YouTube Link: https://www.youtube.com/watch?v=yx3WkiunkuY ]

    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.

    MULTIPLE POSITIONS – School of Civil Engineering, University of Sydney

    • Join a growing Faculty and be part of a University that places amongst the world’s best teaching and research institutions.
    • Located on the edge of Sydney’s bustling central business district, close to beaches, parks, public transport and shopping districts
    • Seeking outstanding Academics to provide leadership and help create a world-class, internationally recognised Faculty for research and education excellence

    About the opportunity 

    The School of Civil Engineering is at the forefront of civil engineering education and research. Our systems approach to teaching allows students to graduate with the much sought-after design, research and problem-solving skills needed to create and manage sustainable built and natural environments. 

    Our research strengths lie in structural engineering, geomechanics and materials, environmental fluid mechanics, transport engineering and complex systems. Our expertise and facilities continue to meet the issues associated with critical infrastructure, sustainability, climate change, water management and the natural environment.

    The School has a long tradition of engagement with industry which has led to successful collaborations with many leading national and global companies and government organisations.  This coupled with our excellence in analytical and experimental research has played a prominent role in the development of Australian and International Standards relating to many aspects of civil and structural design.

    The School of Civil Engineering at the University of Sydney is searching for faculty members at all ranks and in all areas of Civil Engineering. The school seeks to increase the diversity of its faculty and encourages women to apply.

    The School of Civil Engineering at the University of Sydney is prioritising a search for faculty members who are able to contribute in the areas of:

    • Environmental Fluid Mechanics
    • Transportation Engineering

    Click For More Details. [UPDATED LINK]

    The University of Sydney.