Is it wrong to wish on space hardware?
I'm recruiting PhD students in Transport at the University of Sydney. Get in touch if interested.
Five Years Car Free
This is not to say everyone in Greater Sydney could be carless, just a large fraction of the people. About 22% of the population lives within a 15 minute walk of a rail station, while 43% works within 15 minutes of a station. The number within walking distance of a bus is much higher, or 15 minutes by bus to rail.
Presently, by strategy not luck, I live 11 minutes downhill in one direction and 13 minutes downhill in the other direction to rail stations on different lines, only the second of which goes to Redfern which is 8 minutes from my office. So I have a 21-minute walk and 13-minute ride, if I time it perfectly without waiting time. To be clear, if I wanted to and didn't have other family members to consider, I could optimise the arrival time, given the fairly high reliability of Sydney Trains in non-COVID, non-Industrial Action, non-Rainy times (which I guess is to say “cromulent” reliability given the circumstances, and better than similarly sized US transit systems would deliver). My previous commute in Minnesota was a 30-minute walk. My commute from my previous home in Alexandria was a 19-minute walk, circumnavigating Redfern station, but would have gotten shorter once the southern concourse opens.
That’s right, I am calling “BS” on many of the people who say they “need” their car. Cars are nice to have sometimes. Private cars are convenient and allow dynamically choosing destinations without planning or forethought. But cars themselves can be rented when they are needed. Taxis can be called when urban point-to-point transport off convenient public transport routes is required.
We can imagine a hierarchy of preferred modes:
Avoid the activity
Telecommute, work from home, etc.
Walk (or Cycle)
Now there are people, e.g. tradies who work at different sites every day and have equipment to carry with them, who would be much better off if everyone else didn’t drive and congest the roads, pollute the air, and endanger their lives.
In our five years without a car, we have used ride-sourcing (i.e. Uber, Didi, Bolt, etc.) multiple times, but probably no more than one round trip per week for the five-person household, so maybe $AU2000 per year tops, probably less with COVID. This is significantly less than the cost of car ownership.
We have rented cars on exactly 3 occasions in the past 5 years.
Once shortly after arriving, for about 2 hours of GoGet, a car sharing service, to drive on the wrong side of the road. I disliked it, the lanes are narrow and drivers aggressive.
Second when my family arrived, to collect them and their stuff from the airport, and do a road trip to Brisbane for WSTLUR, while we were between housing.
This is for a family of five, three of whom attend school, two work, thus none are in car seats or strollers.
No one in the family has really asked for more long car trips, though I am sure they would like to be driven to work or school on a rainy day (which seems like every day now in Sydney) or when they are carrying stuff because their school has implemented some stupid anti-COVID no locker policy (since retracted).
So do I not drive to save money, save the earth, save my sanity, be able to lord it over others? Who knows?
I will be online presenting at the 2022 Smart Urban Futures Conference (May 5-6) talking about Traffic Signals and Pedestrians. My Talk is 09:40 am Friday May 6 (Melbourne Time).
National Roads and Traffic Expo 2022 May 18-19 at Sydney. I am scheduled for 14:00 Wednesday May 18, on a panel about the pipe dream of a Blue Mountains Tunnel ($$$)
UDIA 2022 National Congress in Sydney May 25-26 talking about Governing for Access. My Talk is scheduled for 15:30 on May 25.
Master of Transport
I will be talking about the University of Sydney’s interdisciplinary Master of Transport program at Post-Graduate Information Evenings on
Tuesday 10th May, 4.30pm to 7.30pm at MacLaurin Hall
Thursday 12th May, 6.30pm-7.30pm online, email for details.
Wu, Hao, and Levinson, D. (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.
Wang, Yadi and Levinson, D. (2022) Time savings vs Access-based benefit assessment of New York’s Second Avenue Subway. Journal of Benefit Cost Analysis. (online first, open access) [doi]
Under the current practice of benefit-cost analysis, the direct economic benefits produced by a newly built transit facility are assessed based on how it affects travel time and various costs that are associated with transport needs and travel behavior. However, the time-saving-based benefit calculation approach has been questioned and criticized. Given the strong correlation between accessibility and land value, we propose the access-based land value benefit assessment as an alternative, and apply this assessment method to analyzing the Second Avenue Subway project in Manhattan, New York. The primary principle of the access-based method is that the economic value of a transport project’s intangible gains is largely capitalized by nearby properties’ value appreciation, which is directly caused by improved transport accessibility. We find that: (i) the actual travel time saving is lower than originally forecast; (ii) a strong positive correlation between residential property value and job accessibility by transit is observed; (iii) the appreciation in sold property value and rented property value both far exceed total project cost; and (iv) such results support the decision to approve and construct the Second Avenue Subway.
Rayaprolu, H., Wu, H., Lahoorpoor, B., and Levinson, D. (2022) Maximizing Access in Transit Network Design. Journal of Public Transportation. [doi]
This study adopts an Access-Oriented Design (AOD) framework for optimizing transit network design. We present and demonstrate a method to evaluate the best combination of local and express alternative transit system designs through the novel concept of ‘iso-access lines’. Two bus network system designs were explored for a greenfield development in suburban Sydney: through-routed transit lines (T-ways) with higher speeds and more direct service, but longer access and egress times, and local routes that provide additional spatial coverage. We developed scenarios with T-ways only, local routes only, and both, and computed transit access to jobs as a cumulative-opportunities measure for each scenario. Local routes offer greater overall access, while T-ways provide greater access-per-unit-cost. The optimal combination of the two was established by generating ‘iso-access’ lines and determining access-maximizing combinations for a given cost by applying production-theory principles. For 15-min access, the optimal combinations had T-way service frequency equivalent to 0.48 times that of local routes. This ratio increased to 1.45, 2.05 and 2.63 for 30-min, 45- min and 60-min access respectively. In practice, the method can be applied to determine optimal transit combinations for any given budget and desired access level.
Congratulations to Ang Ji for “satisfying the requirements for the award of the degree of Doctor of Philosophy at the University of Sydney.”
Lead Supervisor: Professor David Levinson.
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) Estimating the Social Gap with a Game Theory Model of Lane Changing. IEEE Intelligent Transportation Systems Transactions. 22(10) 6320-6329. [doi][VIDEO]
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]
Dr. Ji now has a position at Southwest Jiaotong University in Chengdu, one of China’s leading transport programmes.
The idea of Traffic Programming was first raised in this blog a while back (in 2016).
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.
Research by Others
Hall and Madsen (2022) Can behavioral interventions be too salient? Evidence from traffic safety messages in Science.
A. Coutrot, E. Manley, S. Goodroe, C. Gahnstrom, G. Filomena, D. Yesiltepe, R. C. Dalton, J. M. Wiener, C. Hölscher, M. Hornberger & H. J. Spiers (2022) Entropy of city street networks linked to future spatial navigation ability
Nature volume 604, pages 104–110.
Kelcie Ralph, Jesus M. Barajas, Angela Johnson-Rodriguez, Alexa Delbosc, CarlynMuir, (2022) Can a racial justice frame help overcome opposition to automated traffic enforcement? Transportation Research Interdisciplinary Perspectives Volume 14, June 2022, 100594
News and Opinion
The utility of a color-coded battery [Blue, Green, and Brown Hydrogen]
Australia leads world in rooftop solar as share of renewables jumps to 35% [No thanks to the government that is trumpeting this news]
Cautionary Tales with Tim Harford: The False Dawn of the Electric Car