Dockless in Sydney: The Rise and Decline of Bikesharing in Australia.

Recent working paper:

Percentage of static bikes in Pyrmont by company and day (Bikes unmoved for 48h or more)

In mid-2017, dockless, (or stationless) bikesharing appeared on the streets of Sydney. The birth of dockless bikesharing, its evolution as well as its consequences, and use habits are studied with review of policies and field investigations. It is found that bicycle use in Sydney is less than hoped for, vandalism is high, regulations unfavourable, and thus, the conditions for successful bikesharing are not met.

Does bike sharing have a future in Australia?

I was interviewed by Jonathan Hair last month for the ABC on The World Today. Does bike sharing have a future in Australia? My bit is at 2:20.

It seems soon you’ll be hard pressed to find ‘dockless bicycles’ in some of Australia’s biggest cities.

One bike sharing company has announcing it’s shutting up shop here, and the future of a number of others is in doubt.

But one expert believes there’s a way for the companies to continue to operate here, by harvesting your travel data.

Duration: 2min 53sec

Broadcast:
More Information

Featured:

Professor Emmanuel Josserand, UTS
Professor David Levinson, University of Sydney

On the Four Paths

timeless
Photo by Jesse Vermeulen, posted at Unsplash.

First Path

In the beginning was the path. It was undifferentiated, shared by people and animals alike, and eventually wheeled vehicles pulled by humans and animals. While dating the First Path is impossible — the very first First Path must have been a path that was reused once, and slightly better than the unimproved space around it — it operated both in early settlements and on routes connecting nearby settlements.

Today’s version of that is the sidewalk or footpath. It is now used for people walking, sometimes for people moving goods, and occasionally for people on scooters and bicycles. It should not be used for storing cars, though it is. New uses will include low speed delivery robots, as shown in the photo from Starship.

When we see a raised crosswalk, we know the First Path is given the pre-eminance its venerable status warrants. When we see shared spaces, we know those harken back to the early undifferentiated path-spaces of earlier centuries. When we see pedestrian-only zones, we see a First Path that has grown up.

Starship
Starship Technologies

Second Path

The Second Path diverges from the first path with the emergence of the first street or roads with sidewalks (footpaths).  Spiro Kostof (1992) dates it to about 2000 BCE in Anatolia. And it is clear many Roman and Greek cities separated sidewalks from streets, which the Romans called Semita.

Post-Rome, sidewalks were rare, making appearances in London after the Great Fire, and in Paris after Haussman.

But to be clear, today’s sidewalk is not the second path, it is the first. The second path is the road which is largely free of pedestrians, intended for the movement of vehicles. Originally these were animal powered vehicles, as well as human. Later fuel-powered machines took over the street and roads.

camel
It is easier for a camel to go through the eye of a needle, than for a rich man to enter into the kingdom of God.

Third Path

Cyclists Avenue Sydney Cyclists Avenue Sydney (1900)

The Third Path actually emerged well before the Second Path was colonized by motorized vehicles. It is for bicycles, and initially was paved in contrast with the unpaved streets and roads of its time. Given the first Velocipede was only 1817, and the first bike chain (which we associate with modern bicycles) was 1885, these came relatively quickly compared with the First and Second Paths. While ascertaining the first bike lane or separated bike path is tricky (there are many claims, differing in nuance), I have compiled some claimed firsts and earlies here (thanks to people who replied on Twitter):

While bike lanes have now been around as a technology for well more than a century, throughout most of North America and Australia, bike lanes are not provisioned, so bicyclists have the Hobson’s Choice of driving in traffic with much heavier and much faster automobiles and trucks on the Second Path, the roadbed or illegally in many cases on the First Path, the sidewalk.

With the advent of the smart phone, new modes are becoming feasible, most notably dockless shared bikes and scooters.

Regulations in many places limit the use of bikes on footpaths. The reasons for this are clear from the pedestrian’s point of view, bikes are traveling up to 4 times faster than walkers, and collision can create injury. Dockless shared bikes emerged in Australia in 2017, after a few years on the road in China. Their main contribution has however not been transport (they are used about once every 3 days) but instead as a the recipient of complaint about sidewalk clutter (unlike say cars, which are always parked perfectly). As a consequences they have been targets of vandalism. The obvious solution will eventually get adopted, geofenced corrals for parking bikes (shared and private), taking away one parking space per block perhaps.

Given the disparities of speeds on the first (5 km/h) and second paths (30-120 km/h), there is a clear market niche for an infrastructure network  for vehicles faster than foot and slower than cars. Physically, one imagines it generally lying between the existing kerb and removing a lane now devoted to the storage or movement of cars. And for many if not most urban places globally, this has been recognized and networks of third paths have been, or will be, built out.

This Third Path is important not just for bikes, but for electric bikes (which are becoming increasingly feasible with progress in battery technology) and electric scooters.

Fourth Path

A Fourth Path for buses (and other high occupancy vehicles) is also now considered. The first bus lane emerged in Chicago in 1940. The reason for bus lanes again is in part operational differences compared with existing road users. Buses start and stop in traffic much more frequently than cars. But a second reason is in fact the opposite, not because buses would block cars, but because cars would block buses. Buses carry more passengers than cars, and so should move faster, and can do so if they are not stuck in queues behind cars.

Interfaces

The Kerb – Once a nondescript piece of concrete now forms the edge (both physically and metaphorically) of the sharing economy: taxis, Ubers, autonomous mobility services. The Kerbspace differentiates and separates paths, but we now have new questions:

  • Who manages kerbspace? 
  • How is it regulated?
  • Is it even mapped?

Comp(l)ete Streets

The complete streets movement advocates for streets with sidewalks, bike paths, and are otherwise designed to promote safety and efficiency. The figure below is not exactly what they have in mind.

JusticiaUrbana
Justicia Urbana by Todorovic (https://www.flickr.com/photos/unhabitat/23003427510)

Comments on Sydney’s Cycling Strategy and Action Plan 2018-2030

Sydney has released its Cycling Strategy and Action Plan for public comment. Mine are below:

 

I am pleased to see Sydney hopes to be a more bicycle friendly place. However the plan as laid out is insufficiently ambitious. So much more can and should be done. Sydney should be one of the world leaders in bicycling, but it remains a laggard, stuck in the mid-20th century.  A 10% target in 2030 (3-4x as many bicyclists as today) is good (better than today’s baseline), but the network doesn’t support that, it is not 3-4x as large. 

To start, think about the network: Every major street (say a street that warrants a traffic signals) which also has on-street parking has demonstrated space for separated bike lanes.  What is more important, storing cars 23 hours a day or moving people? The value of the network increases non-linearly with its connectivity. Even most streets without on-street parking have space for bike lanes. 

Among these which I am familiar with should be included Regent St/Gibbons St/Wyndham St and Abercrombie/Wattle, but there are undoubtedly more. The separated bike lane network should be as dense and complete as the arterial street network.*

Similarly, every block that has on-street parking should dedicate at least one parking space to bicycle parking, particularly for shared bikes. Action 1.5 is especially lagging. Bike parking is cheap to install and signals priorities and should lead rather than follow. 

Bikesharing is neglected from this plan.

Regulation is still hostile to bicyclists, including heavy fines and futile helmet laws. Helmets are indicator of danger. Biking should be normalised as in Europe.

A strategy for promoting and regulating eBikes would be good. Also promoting and regulating scooters, skateboards, and other wheeled vehicles (micro-mobility).

A strategy for promoting bike and ride to train and metro stations would be good.

A strategy for promoting biking to school (and Uni) would be good. Schools are at least mentioned, but it seems mostly an afterthought.

Bikes should be counted continuously at intersections (not just 2 times a year), just as cars are. There are technologies to do this, and RMS can be called on to do it. Electronic signs displaying bike counts on key routes is also a good marketing tool.

 

 

*Note: The base map p. 17 locates the Metro stations in the wrong place. The map does not distinguish between shared paths and separated bike lanes, which is a way of claiming credit for something that doesn’t actually exist.

Safety in Numbers: Pedestrian and Bicyclist Activity and Safety in Minneapolis

Recent Report:
AbstractThumbnail
This investigation aims to evaluate whether the Safety in Numbers phenomenon is observable in the midwestern U.S. city of Minneapolis, Minnesota. Safety in Numbers (SIN) refers to the phenomenon that pedestrian safety is positively correlated with increased pedestrian traffic in a given area. Walking and bicycling are increasingly becoming important transportation modes in modern cities. Proper placement of non-motorized facilities and improvements has implications for safety, accessibility, and mode choice, but proper information regarding estimated non-motorized traffic levels is needed to locate areas where investments can have the greatest impact. Assessment of collision risk between automobiles and non-motorized travelers offers a tool that can help inform investments to improve non-motorized traveler safety. Models of non-motorized crash risk typically require detailed historical multimodal crash and traffic volume data, but many cities do not have dense datasets of non-motorized transport flow levels. Methods of estimating pedestrian and bicycle behavior that do not rely heavily on high-resolution count data are applied in this study. Pedestrian and cyclist traffic counts, average automobile traffic, and crash data from the city of Minneapolis are used to build models of crash frequencies at the intersection level as a function of modal traffic inputs. These models determine whether the SIN effect is observable within the available datasets for pedestrians, cyclists, and cars, as well as determine specific locations within Minneapolis where non-motorized travelers experience elevated levels of risk of crashes with automobiles.
Recent publications from this report include:

Safety in Numbers and Safety in Congestion for Bicyclists and Motorists at Urban Intersections

Recent working paper:

The rate of number of crashes to traffic flow
The rate of number of crashes to traffic flow

This study assesses the estimated crashes per bicyclist and per vehicle as a function of bicyclist and vehicle traffic, and tests whether greater traffic reduces the per-car crash rate. We present a framework for comprehensive bicyclist risk assessment modeling, using estimated bicyclist flow per intersection, observed vehicle flow, and crash records. Using a two-part model of crashes, we reveal that both the annual average daily traffic and daily bicyclist traffic have a diminishing return to scale in crashes. This accentuates the positive role of safety in numbers. Increasing the number of vehicles and cyclists decelerates not only the probability of crashes, but the number of crashes as well. Measuring the elasticity of the variables, it is found that a 1% increase in the annual average daily motor vehicle traffic increases the probability of crashes by 0.14% and the number of crashes by 0.80%. However, a 1% increase in the average daily bicyclist traffic increases the probability of crashes by 0.09% and the number of crashes by 0.50%. The saturation point of the safety in numbers for bicyclists is notably less than for motor vehicles. Extracting the vertex point of the parabola functions examines that the number of crashes starts decreasing when daily vehicle and bicyclist traffic per intersection exceed 29,568 and 1,532, respectively.

Dr. Jessica Schoner: Mutually Reinforcing Relationships Between Bicycling Infrastructure

Jessica Schoner
Jessica Schoner

Congratulations to soon-to-be Dr. Jessica Schoner for successfully defending her dissertation: ‘Mutually Reinforcing Relationships Between Bicycling Infrastructure’ before a standing room only crowd at the University of Minnesota campus on 21 August 2017.

 

 

Theory slide. Source: Schoner, J (2017) Mutually Reinforcing Relationships Between Bicycling Infrastructure
Theory slide. Source: Schoner, J (2017) Mutually Reinforcing Relationships Between Bicycling Infrastructure

Abstract:
Researchers have long sought evidence about whether dedicated bicycling infrastructure induces people to cycle, based on a supply-driven assumption that providing infrastructure causes the behavior change. However, supply inducing demand is only one of four theoretical relationships between bicycling and infrastructure. The aims of this research are twofold:

  1. Develop a theoretical framework to identify and evaluate all of the possible relation- ships between bicycling and infrastructure and describe how these factors reinforce one another to shape diffusion of bicycling and infrastructure in cities; and
  2. Develop and execute a research plan to empirically model selected hypotheses within the theoretical framework.

The empirical portion of the dissertation tests the hypotheses that (1) bicycling infrastructure supply induces bicycling demand, and (2) bicycling demand induces additional demand. The research uses a series of cross-sectional tests at multiple points in time as well as lagged variable models to add a layer of temporal precedence to our otherwise cross-sectional understanding of associations between bicycling and infrastructure. The findings show persistent associations between infrastructure and bicycling over time, across geographies, and at both the individual and aggregate level. The association between bicycling and additional bicycling holds over time at the individual household level and for bike share membership. However, the tests failed to find evidence of bike share stations and activity affecting general population cycling rates.
This dissertation provides a roadmap for future research into feedback loops between bicycling and infrastructure. It additionally provides practitioners with guidance on both the strengths and limitations of both infrastructure provision and socially-focused bicycling initiatives.

Like most bicycling research, this dissertation is limited by the quality of data available for both bicycling behavior and infrastructure supply. Neither the data nor the tests performed are rigorous enough to infer causality; instead, the findings add strength and nuance to the existing body of literature.

Papers related to the dissertation are available at:

  • Schoner, Jessica and David Levinson (2014) The Missing Link: Bicycle Infrastructure Networks and Ridership in 74 US Cities. Transportation 41(6) 1187-1204. [doi]
  • Schoner, Jessica, Greg Lindsey, and David Levinson (2016)  Is Bikesharing Contagious? Modeling its effects on System Membership and General Population Cycling.  Transportation Research Record: Journal of the Transportation Research Board. 2587 pp. 125-132. [doi]
  • Schoner, J., & Lindsey, G. (2015). Differences Between Walking and Bicycling over Time: Implications for Performance Management. Transportation Research Record: Journal of the Transportation Research Board, (2519), 116-127. [doi]
  • Schoner, J, Lindsey, G., and Levinson, D. (2014) Factors Associated with the Gender Gap in Bicycling Over Time. Presented at Transportation Research Board Annual Meeting 2015.

The final dissertation will be posted online soon.

As every good dissertation should, it raises as many questions as it answers, and if you are looking for a topic, there are strong research opportunities available to test Hypotheses 2 and 4 on the effect of bicycling demand on infrastructure, and infrastructure momentum. There are also opportunities to examine the new stationless bike sharing systems that are emerging in China (and Australia, and elsewhere) regarding Hypothesis 3 and social diffusion.

 

Some other bicycling research led by the newly minted Dr. Schoner includes:

The paper from her MS Thesis is available here:

  • Schoner, Jessica, Xinyu (Jason) Cao, and David Levinson (2015) Catalysts And Magnets: Built Environment Effects On Bicycle Commuting. Journal of Transport Geography 47 100–108. [doi]

Street wars 2035: can cyclists and driverless cars ever co-exist? | Guardian Cities

Laura Laker at Guardian Cities writes: Street wars 2035: can cyclists and driverless cars ever co-exist? | Guardian Cities

“Driverless cars appear unstoppable – except of course you can simply walk in front of one and force it to brake. Could this conundrum eventually mean a return to a dystopian world of segregated urban highways?”

I was interviewed, my quotes below …

A visualisation of data captured by an autonomous vehicle. Photograph: Elijah Nouvelage/Reuters
A visualisation of data captured by an autonomous vehicle. Photograph: Elijah Nouvelage/Reuters

Or how about prosecuting pedestrians or cyclists who get in the way of driverless cars? David Levinson, a professor at the School of Civil Engineering at the University of Sydney, is broadly supportive of AVs, but says: “It’s very big brother like, there’s a question of safety v freedom. How much risk to endanger yourself are we going to let you take?”

Thinking back to the kids stopping driverless cars on our imaginary future street, Levinson sees a future where blocking a driverless car could even be criminalised. “The car has a camera and the picture will be sent to the police department, and the police department will come and arrest you for annoying an autonomous vehicle.”

Given these challenges, experts including Hickman and Levinson believe segregation and AV-only roads are inevitable. But wouldn’t that risk a return to the urban dystopia of the 1960s and 70s, when planners crisscrossed cities with elevated highways and erected barriers around roads with the aim of improving safety? The unintended consequences were fast, aggressive driving, and the splitting in two of countless communities.

“I think there will be some roads that will be transformed to higher speed roads,” says Levinson. “I’d be sceptical of someone who says we will not do any of that. But if you can move traffic away from the lower speed streets that pedestrians and cyclists want to use, that’s an improvement.”

Hickman believes “the case is overwhelming against AVs” but fears the powerful motor industry lobby means there is so much private and government money already at stake that the rise of driverless cars would be hard to stop.

Is Bicycling Contagious? Effects of Bike Share Stations and Activity on System Membership and General Population Cycling

Recent working paper

Nice Ride Membership Map
Nice Ride Membership Map

This paper presents new evidence about the role of bike share systems in travel behavior using a diffusion of innovation framework. We hypothesize that bike share systems have a contagion or spillover effect on (𝐻1) propensity to start using the system and (𝐻2) propensity to bicycle among the general population. We test the first hypothesis by modeling membership growth as a function of both system expansion and the existing membership base. We test the second hypothesis by using bike share activity levels near one’s home in a model of household-level bicycle participation and trip frequency.  Our study shows mixed results. Bike share membership growth appears to be driven, in a small part, by a contagion effect of existing bike share members nearby. However, we did not identify a significant relationship between proximity to bike share and cycling participation or frequency among the general population. The findings hold  implications for marketing, infrastructure investments, and future research about bike share innovation diffusion and spillover effects.

KEYWORDS: Bike Share; Diffusion of Innovation; Travel Behavior