Abstract: This dissertation explores the rationality of drivers’ risky and aggressive behaviors in lane-changing scenarios and discusses some feasible ways to hold selfish drivers accountable for their decisions. Regardless of potential congestion and crashes suffering by other road users, rational drivers prefer to maximize their gains and demand others’ yielding. However, when all of them have such thoughts, conflicts (dilemmas) are embedded in their interactions, leading to unexpected consequences for the whole traffic. This question is investigated analytically by exploiting the game theory concept. A simplified 2×2 non-cooperative game is built to model strategies executed by human drivers without communications. This research learns driver behavior in two predefined sub-phases: `Stay’ and `Execution’ from empirical data. This procedure examines the factors that impact drivers’ execution of lane changes. From the results, we understand that lane-changing is motivated by the urgency to change and the dissatisfaction with current circumstances. The analytical model is then established by integrating driver incentives into payoff functions. The `greed’ and `fear’ of drivers in this process are quantified by speed advantages and possible crash costs respectively, so they trade off these factors and make decisions based on their own and opponents’ estimated payoffs. Using a numerical case study, we find that social gaps exist between user-optimal and system-optimal strategies when drivers mostly engage in selfish behaviors, significantly deteriorating the total system benefit. Pricing can be a sufficient tool to incentivize users to cooperate with others and achieve win-win outcomes. It is posited that the designed pricing schemes may promote the negotiation between drivers, reducing collision risks and improving operational traffic efficiency. Several simulation experiments are then conducted to evaluate this dissertation’s hypotheses on the performance of pricing rules. Overall, the proposed framework develops a behavioral model and improvement schemes from the perspective of microscopic vehicular interactions. The conclusions will hopefully find their applications in autonomous vehicle-human interaction algorithms and future transportation systems.
Journal articles related to the dissertation include:
Ji, Ang and Levinson, D. (2020) Injury severity prediction from two-vehicle crash mechanisms with machine learning and ensemble models. IEEE Open Journal of Intelligent Transportation Systems. [doi][VIDEO]
Ji, Ang and Levinson, D. (2020) An energy loss-based vehicular injury severity model. Accident Analysis and Prevention. 146 October 2020, 105730. [doi][VIDEO]
We recently were awarded a grant from the Australian Research Council to examine this question in further depth.
Design of micro-decisions in automated transport. Australian Research Council DP220100882 Professor David Levinson; Professor Michael Bell; Dr Mohsen Ramezani; Professor Dr Kay Axhausen; Professor Dr Hai Yang.
Wu, Hao and Levinson, David (2022) Ensemble Models of For-Hire Vehicle Trips. Frontiers in Future Transportation. 3 [DOI]
Ensemble forecasting is class of modeling approaches that combines different data sources, models of different types, with different assumptions, and/or pattern recognition methods. By comprehensively pooling information from multiple sources, analyzed with different techniques, ensemble models can be more accurate, and can better account for different sources of real-world uncertainties. The share of for-hire vehicle (FHV) trips increased rapidly in recent years. This paper applies ensemble models to predicting for-hire vehicle (FHV) trips in Chicago and New York City, showing that properly applied ensemble models can improve forecast accuracy beyond the best single model.
Lahoorpoor, B. and Levinson, D. (2022) In Search of Lost Trams: Comparing 1925 and 2020 Transit Isochrones in Sydney. Findings, March. [doi]
Abstract: Has Sydney lost access by removing its extensive tram network? We compare the 1925 tram network with today’s bus network, and conclude that the access provided today exceeds what would have been provided by just trams. The Sydney CBD would have had better access if 1925’s central tram lines were still in operation.
In the present it is better to be optimistic than pessimistic. In short, you feel better about the future, hope brings more happiness than fear. And if everyone is optimistic, and acts as if the optimistic future will come about, it may help bring that reality, as in a self-fulfilling prophecy. The self-fulfilling prophecy rewards the optimist. They can claim credit for correctly predicting the future and live in that better future. The self-negating prophecy of the pessimist does not reward the pessimist, who had to be wrong to warn people off the wrong path. The pessimist may say:
“If you don’t get off that path, you will get run over by the trolley.”
They are warning
“Get off the path.”
“You will get run over by the trolley”.
Perhaps they got off the path so did not get run over by the trolley. Thus the pessimist was wrong. Alternatively, they did not get off the path, someone died, and people hate “I told you so”. People don’t like pessimists because Misery loves company.
However, if the future brings risks, and the optimist fails to prepare for those risks, (“She’ll be all right, mate”) bad outcomes occur that could have been averted by a more realistic or pessimistic take.
So perhaps we can think of a spectrum of reality-distortion:
In the absence of other information, the realist is best, having an accurate assessment of the risks and rewards of actions on future outcomes. But in a world that favours optimists, the accurate forecast faces the same problem as Cassandra, uttering the truth but not being believed. One may need to be more strongly negative to bring others to a realistic position, splitting the difference between optimism and pessimism. By expanding the Overton Window, pessimism is a palliative to excessive optimism, repositioning realism in the centre, and reminding everyone that outcomes are probabilistic, not guaranteed.
In short, we need a distribution of behaviours and ideas (an Ensemble) to enhance both individual and group survival. Individuals can and should specialise, it is how we make progress by going deep in selected areas, rather than wide across them all, yet schools, bureaucracies, and other institutions aim at homogenisation in skills, thoughts, and actions, as if we are all (at least those of us in schools) are to be as close to interchangeable parts as we can be made. Everyone is supposed to be slightly optimistic, extroverted, enthusiastic, and so on (but not too much!). Those who see the risks or downsides of whatever the hive mind has asserted is the proper course of action are dismissed, ostracised, or ignored.
When Bill Lindeke reminded me that streets.mn turns 10 round about now, I was sort of surprised, it feels both younger and older than 10 simultaneously. In 1867, 154 years ago, the Minneapolis Tribune was founded, it remains with us today. Ten years ago streets.mn launched, so has been around for about 6.5% of the life of the Strib. Will streets.mn be around in 144 years? Will the Strib?
We founded streets.mn back in the era of blogging, with the idea that all of us who wrote blogs about Twin Cities transport and land use issues would be get more views at one address together than at 10 separate URLs apart. That worked out reasonably well. For the first couple of years we had exponential growth in readership. I was the Chair for the first 4 years (4 years longer than I wanted to be).
At first I imagined it would be a place to argue about the merits of topics like Minneapolis skyways or arterial buses vs LRT (I hope the answer is becoming more obvious with the H line being planned ). Billions of dollars are being spent on transport infrastructure, and it is hard to believe it is being invested well.
But things took a dark turn. This is not so much because the world changed, though it did, but more because we became unavoidably aware (with a phone in every pocket, cameras, and social media) of how it always was.
Someone said the role of journalism is “comfort the afflicted and afflict the comfortable”. Streets.mn should agitate for more systemic change, this will inevitably afflict the comfortable. Very few people reading this would look around and see that everything is alright. We might disagree about what needs changing or how it should be changed, but it should not be that hard to agree on a few things that are the opposite of ideal.
I am disappointed to regularly seeing Minneapolis on the forefront here in Sydney: Justine Diamond remains front page news. And Minneapolis claimed the front page world over with the murder of George Floyd. This follows the case of Philando Castile in nearby St. Anthony.
Police on civilian violence is very much a transport and land use issue that should be within the purview of streets.mn. Foremost because this violence often occurs on public streets, and is justified by police stops purported to enforce traffic safety regulations. But the violence has a chilling effect on the willingness to use streets, to go places, to be able to access the amenities that cities uniquely provide. This kind of state-sanctioned violence, in which everyone is implicitly complicit, is far worse (per victim) than terrible epidemic of civilian on civilian violence which is also found in excess throughout the United States, and is yet one more aspect of unfortunate dysfunctional American exceptionalism.
The reason we build cities and transport networks is so that people can readily access people, places, and activities that they value, while maintaining their ability access other things in the future. Maintaining that ability means being able to do things at a low cost. That cost includes not only their travel time and monetary expenditures, but the costs they impose on society like pollution and carbon emissions. But it also needs to include both a feeling and reality of safety and security, the belief that anyone can make a trip and return in one piece, uninjured by either car or bullet and unharassed by police or other people.
When your great-grandchildren read streets.mn in 2165, will Minnesota have at least solved the problems of today?
We have seen numerous older technologies get wiped out as new technologies emerge: email ate the post office; TV, DVDs, etc ate the movie theatre; MP3s ate the record. Now old technologies still exist, a shadow of their former selves.
From 1918 forward, the automobile began to eat public transport in the US. The pandemic had something to do with it, but the lower costs and rising convenience of cars helped. Transit had reached some stability by the beginning fo the 21st century. COVID has knocked it further for a loop, as CBD workplaces, one of the primary markets that transit served emptied out. But they emptied out because personal computers, mobile smartphones, cell towers, internet, software, and so on replaced some of the core functions of a workplace: doing office work (making virtual things: electronic reports, accounts, data manipulation, knowledge creation) and having meetings (discussing making virtual things , and occasionally real things). It turns out you don’t need to be physically anywhere to make virtual things, so long as you have access to the electronic network where such bits are moved from one side of the monitor to the other and the work is stored.
We may mourn the slow decline of office and public transit as we mourned the slow decline of department stores, shopping malls, urban factories, streetcars, which is to say, we won’t, except in some somewhat ironic articles in high-end magazines and blog posts.
This thesis utilises econometric methods in the context of bus network service prediction utilising the Greater Sydney bus network between 1926 and 2013. Using historical bus GTFS data, the method with which this is transformed to find the level of service per link, as given by the Open Street Maps network is also shown. Weighted spatial variables are described where the strength of the spatial relationship is given by a region-level correlation matrix, also described within this work. The lagged service variable is found to define to a high degree the number of services experienced on a link in any given year, with the addition of complementary and competing spatial variables improving the model fit marginally or leaving it unchanged. As expected, lagged complementary variables have positive correlations with to service levels in the proceed- ing year, while competing links show the opposite relationship. The lagged service level model for the entire Greater Sydney region is further compared against the region-level spatial model, showing that only few circumstances offer a superior performance of regional models to the aggregated.
This thesis report describes the extraction of records from the McGraw Electric Railway Manuals to rectify the lack of documentation around streetcar systems through technological means, and discusses the appropriateness of using technology to analyse century-old directories. The extracted records are analysed on a metropolitan, state and national level, and fitted to logarithmic S-curve models to describe their growth and decline.
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
“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%
More on: How to value transport projects
Following up on the October newsletter:
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.
* 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.
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.
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.
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.
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
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).
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.
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.
Governments very interested in job creation through construction, but seems almost no research on job creation in construction of walking and cycling infrastructure
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
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.
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.)
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).
[rewritten] Why does the amount of land devoted to transport purposes keeps growing.
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.”
Someone drove a car through a parade while escaping police. There are numerous causes to every failure. But we actually have a technology solution: Speed Limiters, limiting vehicle speeds in geo-fenced areas. Obviously deployment would take time, especially retrofit. But this isn’t even being discussed. When are we going to put speed limiters on cars?
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