What GIS can contribute to cycling safety research

Three years ago, I finished by PhD with a thesis on GIS and cycling safety. A few months later, I submitted a manuscript to gis.Science, in which I had summarized the main arguments and results of my thesis. This is the story of a very, very long publication process:

  • Manuscript submission: December 2017
  • Acceptance notification: April 2018
  • Re-submission of revised manuscript: May 2018
  • Final acceptance: June 2018
  • Publication: December 2019

Anyway, whoever is interested in how GIS can contribute to cycling safety research, finds a brief summary of my PhD thesis in this internet recently published paper.

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Shifting modes: the potential of short commuting trips

A shift from motorized individual transport to “green modes” is desirable for multiple reasons, but hard to achieve. We have been working on this topic in the context of the GISMO internet research project, which revolved around healthy commuting, and collected some valueable insights. However, the effects of mode shift go far beyond individual health benefits.
For this blog post, I did some reading and tried to summarize factors, which are relevant for stimulating a mode shift from car to sustainable modes – interestingly, many of them are linked to geography. The most basic geographic variable in mobility is distance. I am going to highlight the huge potential of short commuting trips being substituted by active modes by presenting some basic analysis results based on mobility survey data.

Car stickiness
In a lab experiment, Innocenti et al. (2013, link internet) proved that mode choices are rarely made on a rational basis. Instead, they are biased by various individual factors (routine, memory, perception etc.). These biases lead to a preference of the car, although travel time and monetary costs might be higher compared to alternatives. Subjects in the experiment showed a tendency to repeat their initial mode choice, which is the car for a majority, regardless of the costs. In other words, people do not like to change modes and information provision has little influence.
Garcia-Sierra et al. (2015, link internet) put the car stickiness into a broader context and provide an extensive list of behavioural biases and anomalies, which influence long-term and short-term mobility choices.

It is frequently repeated that the car is loosing attractiveness for younger generations and is not an object representing status and prestige anymore. In fact, numbers of car ownership or trips taken are have been going down among millennials for quite a while. However, as Garikapati et al. (2016, link internet) impressively show, this mobility behaviour fades and millennials are adopting the mobility lifestyle of preceeding generations, but at a later stage in their lifes.

In contrast to the rather conservative conclusion of Garikapati et al., Canzler & Knie (2016, link internet) are convinced that the digitalisation of the mobility sector is going to disrupt the way we are moving. In their opinion, flexible, intermodal mobility services, facilitated by the ubiquity of the smartphone, will substitute conventional, private vehicles (cars) entirely. With this, the relation between producers (car manufactorers) and consumers (private car owners) is ultimatively transformed into an interplay of demand (being mobile) and supply (service). Thus, the authors do not argue for a mode shift within the existing system, but for an entire transformation of the mobility system, which will automatically reduce the number of motorized vehicles on the road.

Individual or society?
Many strategies for stimulating a mode switch target the individual and his or her particular behaviour pattern. Clark et al. (2016, link internet) regard life events as major factors for mobility behaviour change. The authors found residential relocation, change of employer and gaining a driving license as most effective life events in terms of mode switch. Spotswood et al. (2015, link internet) argue for targeting society instead of individuals. In their (very inspiring!) paper, the authors propse the application of Social Practice Theory (SPT) for changing mobility behaviour towards active modes. The SPT is built upon three pillars: materials (everything external, physical), meaning and competences. With regard to mobility, the first two pillars can be translated to infrastructure and service provision and mobility culture respectively.

Types of interventions that are intended to stimulate mode switches from car to public transport or active modes are very diverse. They can be physical (built environment), communicative, legal or economic. Scheepers et al. (2014, link internet) investigated the effects of various interventions and found an overall positive correlation between interventions and mode shift in an extensive meta-study. In most cases, multiple interventions were simultanously implemented, what increases the overall effect. However, the authors note that the robustness of available evidence is rather weak, since most studies lack of control groups and do not control for statistical significance.

Spatial context
Besides the aforementioned life events, Clark et al. (2016, link internet) identified distance and public transport service level as additional drivers for mode change. The probability for switching to non-car commuting becomes 9.2 times higher when the commuting distance drops below 4.8 km (3 miles). However, car availability counteracts the effect of distance, according to Scheiner’s (2010, link internet) analysis of longterm longitudial data from Germany.
Heinen et al. (2015, link internet) report on effects of new public transport, cycling and walking infrastructure on the modal split among a group of commuters: by building a busway with parallel cycling and walking ways the share of trip chains with active parts significantly increased, while the share of car-only commuting trips decreased. Commuters living within 4 km from PT stops were twice as likely switching modes than the rest. Sallis et al. (2016, link internet) come to very similar conclusions in their seminal study on the relation between the built environment and physical activity. They identified four environmental key factors, which are linearly related to physical activity: residential density, intersection density, public transport density and the number of parks. Such environments stimulate active mobility and physical outdoors activities and are thus fundamental for public health.
Regardless of the investigated variables, it is of great importance to differentiate between statistical correlation and causal relation. For instance, Schoner et al. (2015, link internet) point to the fact that a direct, causal relation between the environment and mode choices are hard to be proven statistically. In general, environmental factors are either catalysts (making people switch their mode) or magnets (attracting people who are already prone to respective modes). Thus, the authors designed a model that is able to account for these different effects. Applying this model to a dataset from Minneapolis, Schoner et al. found that bicycle lanes and workplace accessibility contribute significantly to the level of commuting by bicycle.

Two sides of the coin: internal and external factors that are relevant for promoting sustainable, active commuting.

Probably, there are some more factors, which need to be considered in the context of stimulating a shift from car-depended to sustainable modes. However, what became obvious so far clearly indicates that motivators and deterrents for active commuting can be roughly grouped into internal (personal) and external factors. Moreover, these two sides of the coin are interrelated in multiple ways and thus, need to be addressed in integrated approaches.
Many factors can be changed or influenced, either at an individual or at a societal level. However, some factors, such as residential and employment location, require long-term decisions and are related to numerous dependent variables (availability, price, social involvment and obligations etc). Consequently, the distance between place of residence and workplace is given for many employees; at least in the short run.
Taking commuting distance as fixed, the mode choice for commuting trips becomes central. Two fundamental questions emerge in this context: How big is the potential for mode shifts from car to any alternative? What does it take to trigger this shift? In order to answer the first question, I took a closer look to the most recent, available data for Austria, the mobility survey “Österreich unterwegs” internet).

The following analysis is based on the full dataset, which we are using in the Bicycle Observatory internet research project. The analysis steps are straightforward and do not consider any correction factors etc., which are used for the official report. Thus, the outcome could diverge a little bit from other results, which are based on the same dataset. However, the magnitude should be correct.
In a first step, I was interested in distances for commuting trips. I selected all trips with the trip purpose work, used the distance classes of the original dataset, and differentiated between federal states. The chart below shows the cumulative distribution of distance classes:

It becomes evident that at least half of all commuting trips are below 10 kilometres. This distance can be regarded as cyclable, especially when e-bikes are taken into account. But despite this potential, it is not reflected in the modal split statistics:

For large parts of Austria, especially for rural regions, the car is the preferred commuting mode. Consequently, short distance commutes remain a theoretical potential for sustainable mobility. In order to activate it, integrated efforts with a mix of pull and push measures are required. The (social) context of companies offers reasonable opportunities for addressing commuters. As we could demonstrate in the GISMO project, it is possible to change mobility behaviour internet of employees with specific interventions. However, the evidence from literature is clear that the less car-centric the physical and cultural environment is, the more attractive public transport and active mobility become. The analysis results of the national mobility survey leave no doubt: the length of trip distances cannot serve as valid argument for the car as prime commuting mode.


Some reflections on VeloCity 2019

Dublin was a great place to be last week. Not only mild temperatures contributed to the attractiveness of Ireland’s capital, but also this year’s VeloCity internet conference. A varied program with lots of opportunities for networking brought together international cycling experts and enthusisasts from academia, industry, NGOs and the public sector. After sorting out my notes, pictures and experiences, I am trying to summarize and reflect this super packed cycling week.

The conference

Organized by the European Cycling Federation (ECF internet), the VeloCity conference series is the annual meeting point for the international cycling community. The mix of academic and practical contributions as well as the expo and a rich side program with workshops, excursions and social events make the VeloCity an event, which has to be highlighted in the conference calendar.
This year, VeloCity took place in Dublin for the second time after 2005. The Convention Centre Dublin at North Wall Quay hosted over 1,000 delegates from around the globe.

VeloCity 2019 was hosted in Convention Centre Dublin (Samuel Beckett bridge and River Liffey in the foreground). Foto: M. Loidl

Each day was framed by plenary sessions, which were dedicated to specific topics. Papers, projects and initiatives were presented and discussed in six parallel tracks between the plenaries. A poster exhibition, technical sessions and a large expo complemented the program.
In total, VeloCity 2019 offered 7 plenary and 78 parallel sessions. The selection of the plenary topics was excellent – relevant fields, from planning to technology, infrastructure, health and tourism were covered. The quality of the presentations in most sessions I attended was very high. However, it happened more than once that time for Q&A was lacking. I know the dilemma of including as much contributions as possible, giving speakers reasonable time and facilitating in-depth discussions. Besides session chairs with their eyes on the watch, I would regard slightly longer coffee breaks as most effective. Further limiting the length of presentations would end up in rather superficial talks.

VeloCity is a comparable expensive conference. In my opinion, the speaker fee is too high, given the fact that it is the speakers, who fill any conference with quality and life. Although it was a great opportunity for sharing and networking and an attractive package (impressive conference dinner in Guinness Storehouse, free bike rental etc.) was offered in Dublin, it (literally) cost me quite a lot to scrape together travel funds from my research projects.

Usually, the VeloCity conference goes overseas every second year. Since Mexico City withdraw its bid, the magnificent capital of Slovenia, Ljubljana is going to host next year’s conference. I’m looking forward very much to this!

Program highlights

The plenary sessions were very well curated: highly relevant topics were presented and discussed by inspiring speakers and panellists.

The very first plenary was probably the one with the largest impact, as it addressed the future of where the majority of people are living. In his keynote “The City of the Future” Philippe Christ internet, innovation adviser at ITF internet, deconstructed technology-driven scenarios of future cities (“Smart Cities”) and presented a perfectly balanced, human vision of how to shape cities. Philippe pointed to three aspects, which, in my opinion, should become cornerstones of any discussion on urban development:

  • Future visions
    Philippe referred to widely-used pictures of future cities, which are solely shaped by an efficiency and control paradigm (try your own Google image search internet). In contrast to this, he reminded the audience that in the past, cities have always benefited from creativity that emerged at the fringe of planned, formal spaces. Thus, the question is, if we would really want to go for sterile, manageable cities, or for cities that offer opportunities for unfolding the potential of all its citizens. The latter requires human interaction, unplanned activity, spontaneity, and unsupervised playing.
  • Future humans
    Although many proponents of smart city initiatives are not that much used to it, the question of what defines and characterizes humans is fundamental for any future development (also see Calzada & Cobo 2015 internet). According to Philippe Christ, humans are active, frictious, social, and free.
  • Future technology
    The following panel discussion often related to this part of Philippe’s keynote. Neither Philippe nor any of the panellists were radically against technology as such. However, they strongly argued for – how Klaus Bondam put it – a future that should be shaped by humans, not by technology. In the past 50 years, the car gained technological monopoly status, which became manifest in how cities are built and organized. The current smart city paradigm pushes the next monopoly technology in cities: code. Of course, the highly interconnected, automated city can be beneficial in several regards, but it also bears the potential to isolate and segregate individuals and communities respectively.

The only question that remained open after this powerful statement for a people-oriented future city was, “What if the auditorium was not full with cycling enthusiasts, but with representatives from car industry and the ITC sector?” I wish that such a message does not only reach the converted (such as VeloCity delegates), but also those who are influencing (political) decisions with their unreflected, narrow tech-optimism.

After the opening keynote, I attended a session on autonomous vehicles and cycling – a perfect follow-up. Ceri Woolsgrove internet of ECF claimed that autonomous vehicles will partly improve the situation for cyclists, as there won’t be any drunk driving, for example. However, industry is not ready to ensure full safety for cyclists yet and thus, it might take a while until AVs will be common on our cities’ roads. No wonder that Renault’s former CEO, Carlos Ghosn complained over cyclists. In a Forbes article by Carlton Reid internet, Ghosn is quoted as follows:

One of the biggest problems is people with bicycles. The car is confused by [cyclists] because from time-to-time they behave like pedestrians and from time-to-time they behave like cars.
Carlos Ghosn in Forbes internet

Ghosn might have liked John Parkin’s internet presentation on cycling-specific outcomes of the Venturer internet research project, where the interaction between AVs and other road users was investigated:

A session on cycling data, closely related to our current Bicycle Observatory internet project, took place on Tuesday afternoon. In the German MOVEBIS internet project, a vast amount of cycling trajectories are collected and further used for analysis purposes. Herbert Tiemens internet and Ilari Heiska gave an update of current features and applications of the ABM simulation environment Brutus internet. Finally, Michal Jakob of Cyclers internet, a young Czech company, addressed the challenge of using tracking data for estimating total amounts of cyclists.

André Muno (Climate Alliance), Ilari Heiska (City of Helsinki) & Herbert Tiemens (Province of Utrecht), Michal Jakob (Cyclers)

The second day of VeloCity started with a plenary on the importance of being happy and healthy. Three short keynote presentations covered a wide variety of topics. Orna Donoghue internet (Trinity College Dublin) presented outcomes of a huge, longitudinal study on ageing. The Irish Longitudinal Study on Ageing (TILDA internet), with over 8,500 participants over the age of 50 years investigates several aspects of ageing, including mobility. Accessible facilities, adequate transport options and personal mobility are known to be key factors for happy and healthy ageing. Matthew Philpott internet introduced the idea of promoting healthy lifestyles in and around sport stadia. And finally, Lucy Saunders internet gave fascinating insights into the process of implementing the Healthy Streets internet concept in London.

Lucy Saunders chaired a subsequent session on health in mobility. Victor Macêdo internet, representative from the Brazilian city of Fortaleza, gave an impressive overview of activities to promote healthy, everyday mobility. Supported by Bloomberg Philanthropies internet and the World Health Organization, Fortaleza implemented a citywide bike sharing scheme and is building dedicated cycling infrastructure (from 68km in 2013 to currently 260km). With “Bicicletar Corporativo”, the city council promotes cycling among municipal employees. A law that allocates all money from parking management and 1% of digital platform revenues to promoting active mobility insures the sustainability of all these measures..

Victor Macêdo presenting recent cycling promotion measures in Fortaleza, Brasil.

I had the honour to present rationales and results of our GISMO internet project in this session. Currently, we have nine papers with all the detailed results of the clinical intervention study under review. Please check the project website for updates; we are going to link to the papers as soon as they are out. For now, I can refer to the slides of my presentation:

In the last session before the bike parade on Wednesday, the Austria Cycling Competence internet network celebrated its 5th anniversary with a special session. Selected members, presented recent projects or gave an overview of their portfolio. I took the chance to argue for a spatial perspective on cycling.

Click on the pictures to access my slides.

The plenary session on infrastructure was very important – not only with regard to Dublin’s non-existing cycling infrastructure. Burkhard Stork, chairman of the German cycling association ADFC internet, claimed that infrastructure is the backbone of any cycling infrastructure. It reminded me of a lecture I gave at the Technical University of Vienna in 2017 internet. Back then, I showed how important dedicated infrastructure is for cycling safety. Only a day later, I received an email from a professor who attended the lecture. He urged me to prove scientifically that cycling infrastructure would enhance cycling safety and claimed that vehicular cycling would be safer, cheaper and more efficient. With this story in my mind, I enjoyed Burkhard’s comments on John Forester’s internet idea of effective/vehicular cycling a lot. Forester’s idea of treating cyclists like any other traffic participants became popular for several decades, especially in North-America and the UK. However, as Burkhard pointed out, Forester developed his idea not based on evidence, but on his own preferences as race biker. It was Roger Geller of Portland, Oregon who questioned the vehicular cycling concept and wrote his ground-breaking article “Four Types of Cyclists”. This fine piece of work internet wasn’t scientific as well, but Geller made a claim that became fundamental for subsequent cycling policies and a starting point for lots of research in this field:

Riding a bicycle should not require bravery. Yet, all too often, that is the perception among cyclists and non-cyclists alike.
Roger Geller internet

A substantial amount of research that revolves around this statement has been done by one of the most profound cycling researchers, Jennifer Dill internet. She underlined Burkhard’s critique of vehicular cycling and his unequivocal call for adequate cycling infrastructure with several studies.

Jennifer Dill (Portland State University) provided loads of evidence for the effect of dedicated infrastructure.

The importance of cycling research is also emphasized by the ECF. The European Cycling Federation connects researchers who are working in the wide area of cycling mobility. Throughout the conference, special sessions of the Scientists for Cycling internet network were organized. One of these academic sessions was dedicated to measuring the impact of cycling.
Ray Pritchard internet of Norwegian University of Science and Technology (NTNU) shared outcomes of two observational studies in which the effect of newly built infrastructure was investigated. In order to properly assess the impact of such measures, it is necessary to differentiate between mode shift (infrastructure attracts new cyclists) and route shift (cyclists change their routes). Ray did this by using GPS trajectories and survey data. In both use cases, in Trondheim and Oslo respectively, route shifts became obvious, whereas no significant mode choice could be proven. The Oslo study was recently published in the Journal of Transport Geography internet.
Among other objectives, the research project Bicycle Observatory internet seeks to lay the foundations for assessing the impact of measures in various dimensions. Thus, my contribution to the session perfectly built on Ray’s presentation:

In France, Stéphanie Mangin internet is leading a project called observation du tourisme à vélo. The aim is to estimate the economic value that is created by cycling tourism. For this, Stéphanie and her team collect data from all permanent counting stations along national routes and combine these data with on-site survey data on average expenses and durations of stay. Monetizing the impact of cycling (tourism) builds a perfect evidence base for pushing public authorities to further build attractive, safe infrastructure.


Cycling parades are one of the major highlights of cycling conferences. Usually, this event is used to show delegates the host city and to raise awareness for cycling among citizens and politicians. For VeloCity 2019, the organizers chose a different strategy and guided us to St. Anne’s park outside the city. Probably, this was the best-protected (securities at every intersection and private driveway), but also shortest parade ever. The length of the parade might have something to do with infrastructure … The largest part of the parade led along the seafront to St. Anne’s park – one of the very view segregated cycle ways in Dublin. Honi soit qui mal y pense.

On Twitter, the parade was heavily discussed. Here are some examples:

Dublin and its difficult relation to cycling

Dublin is a beautiful city with a rich history and charming citizens. It has a lot to offer … but definitely not to cyclists. Although the Lord Mayor and all representatives, who appeared at the parade or gave an address at the conference, tried to give the impression of a cycling friendly city, it did not work out. Dublin is by no ways a cycling city! I captured this everyday street scene on my way to the conference:

During VeloCity, several articles on cycling were published on the newspaper. The Guardian was pretty clear with the headline Dublin disappoints internet and even the Irish Times titled We’ve lost our way with private cars internet. On stage, Klaus Bondam was the first who articulated what many experienced in the city:

As Klaus pronounced his critique in the very first plenary session, delegates had enough time to collect evidence for what he had said. These contributions were favourably received by local cycling activists and picked up by local newspapers. Mark Wagenbuur internet did a great job by collecting some bits and pieces – have a look at his blog post. In order to get an impression of what was going on, I curated some more or less randomly tweets (do not miss the discussions and read the whole threads!). Let’s start with some of my own:

… and some more

Okay, as it becomes clear, there is a lot to do in Dublin. At least, VeloCity might have increased the pressure on the City Council to really build and improve adequate infrastructure for cyclists. And of course, cycling in everyday clothes, without helmets and not necessarily on sport bikes must make it into the mainstream attitude towards cycling. Since the parade was a disappointment for many delegates, the local cycling advocacy, I BIKE DUBLIN internet, organized a critical mass from the Convention Centre to the conference dinner at Guinness Storehouse. I decided to walk and witnessed a very funny, but self-revealing situation:

Brief conclusion

The conference wasn’t cheap and Dublin is no cycling city, but VeloCity 2019 was definitely worth to attend. It was inspiring and fun. I learned a lot and was able to connect to others who are working on similar topics or who gave me valuable input for our further research. I enjoyed the diversity among the delegates – be it in terms of geography or domain background. The excitement for cycling turned out once again to be a very strong common denominator.

Mobility behaviour change & health promotion

The evidence is very clear: physical inactivity due to sedentary lifestyles accounts for more premature deaths than smoking worldwide (Wen & Wu 2012 internet). A reduction of physical inactivity by 25% could prevent 1.3 million deaths globally per year (Lee et al. 2012 internet). Physical inactivity accounts for an estimated economic loss of 1-3% of GDP (WHO 2018 internet). For adults, the World Health Organization recommends a minimum of 150 minutes of physical activity with moderate intensity per week (WHO 2010 internet). This sounds not too much. However, worldwide, one out of three does not meet this recommendation and the share is worse for high income western countries. Here, 42.3% of the total population is insufficiently active (Guthold et al. 2018 internet)!

In the recently finished research project GISMO (see a previous post internet  or consult the project website internet in German language for further details), we hypothesized that the daily commute to and from work is a very efficient opportunity for increasing the amount of physical activity. In order to unlock this potential, a behaviour change from passive to active mobility is required. This could be a very hard process, because mode choices are not made on a rational basis (Innocenti et al. 2013 internet).
In order to overcome this barrier, it is necessary to create positve experiences and to provide incentives for more walking and cycling. Companies are key players in this transition process. Through institutional health promotion programs and travel plans, they have the necessary means to influence employees’ commuting mobility. Moreover, companies are social settings, where a pro-activity spin can be created and cultivated (Millonig et al. 2016 internet). Conversely, companies need a sound evidence base on which they could decide on adequate measures. Any decision maker in this context wants to know how much he or she needs to invest and which return can be expected.

A corner stone of GISMO was a clinical intervention study, in which we investigated the health effects of promotion activities that encouraged employees from car to active commuting. In order to come up with a dose-effect relation, accurate data on the subjects’ commute were required. These data also indicate to which degree subjects were willing to follow the instructions and change their mobility behaviour.
We used travel diaries and fitness watches with a GPS and a heart rate sensor for tracking commuting mobility. A methodological paper on travel mode detection was published last year (Stutz u Westermeier 2018 internet). Another paper on how to merge self-reported with technically sensed mobility data is going to be submitted very soon together with a series of papers on the health effects – I will add the reference as soon as the papers are published.

For our GISMO study, 76 subjects, who primarily travelled to work by car, were initially recruited (73 finally participated). Subjects were randomized into an intervention and a control group in a 2:1 strata (Niederseer et al. 2018 internet). Depending on personal preferences, the intervention group was divided into two subgroups. One, in which subjects were asked to switch to cycling and another one, in which subjects were encouraged to walk and use public transport. The baseline characteristics in terms of health and mobility behaviour were comparable across all groups.
First results of an analysis of the collected data were striking in terms of mobility behaviour change:

Besides the loyality of subjects to the recommended transport mode, the low modal share of the car in the intervention groups, compared to the control group, becomes evident. Given the fact that the modal split of all participants was similar prior to the intervention, one can conclude that a vast majority of car trips were successfully substituted in the control group.
The financial investment that was necessary to achieve this astonishing mode switch was comparable low (max. 700 € per subject for a one year intervention period). From a qualitative survey among participants who finished the study, we know that two motivators were particular outstanding. First, the experience was decisive for behaviour change (see this feedback internet in German language by a subject). Second, the medical investigations at the beginning and end of the intervention period were very positively perceived.

According to the latest available mobility survey internet, 44% of all trips of the working population are commuting trips from and to work. Considering this high amount of work-related traffic, the high share of the car in the commuting modal split and the comparatively short distances bear huge potentials for healthy, active commuting. Changing established mobility behaviour patterns is a challenge, but as we could show in the GISMO study, it is possible to unlock the potential of active mobility for health promotion.



Bicycle flow model on OpenABM and GitHub

During the past 2 years, we have been intensely working on an agent-based simulation model, which allows for estimating cycling traffic at the highest possible spatial and temporal resolution. Results were presented among others at the last ICSC in Barcelona. The slides of my presentation and further details on the simulation model can be found on this blog internet.
The context of this research was the collaborative project FamoS, lead by TU Graz and funded by the Austrian Ministry of Transport, Innovation and Technology.

The simulation model was implemented in a OpenSource software environment called GAMA internet. A major advantage of this software is its GIS capabilities. GAMA is not specifically designed for agent-based transport modeling and a lot of features had to be programmed from scretch.

We have now shared the entire model with an extensive documentation and a sample experiment on OpenABM platform internet. You are invited to test the model, improve it or contribute additional features. The code is available on GitHub internet.

GIS and sustainable mobility

The transport sector accounts for a substantial portion of greenhouse gas emissions and fine particulates. Besides these environmental implications, the current transport system heavily relies on motorized individual transport, which leads to negative economic, social and health effects. Consequently, legislators on all levels are aiming for transforming today’s mobility. Numerous strategies and roadmaps towards decarbonization, sufficiency and efficiency and sustainability reflect this political goal.

At the coming GI Forum conference internet in Salzburg, I’m going to organize a special session, which is dedicated to sustainable mobility. The session “Spatial Perspectives on Sustainable Mobility” is the fifth in a series on GIS and mobility research. The idea of this series is to highlight the potential of spatial approachs in mobility research. Numerous factors influence mobility behavior and transport systems. The spatial perspective can help to link domain-specific knowledge on the basis of a common spatial reference and derive novel, integrative approaches.
Over the past years, this special session series has become a well attended element of the annual GI Forum conference. Besides original research that is presented in this session, it is a perfect opportunity for networking with fellow GIScientists and experts from other domains.

For the next edition of this series, we invite researchers from any domain backround, who are working at the intersection of GIScience and mobility research, to contribute to this special session. Today, the call for contributions internet got published on the website of the conference. Original research can be submitted until Februrary 1st 2019.
Consider this call as an opportunity for your publication strategy and for project dissemination. Accepted full papers and extended abstracts are going to be published in the Open Acccess GI Forum journal internet.

I’m looking forward very much to welcoming you in Salzburg next july!

Is cycling dangerous?

Studying a map with geo-located bicycle crashes might leave you with the impression that cycling must be terribly dangerous. A little bit of rudimentary statistics definitely helps at this stage. Whether something is regarded as dangerous or not ultimately depends on the underlying statistical population. This is a common concept for example in medicine. In a drug’s package insert, the risk for suffering from adverse effects is always related to a population. This helps the consumer (or the medical doctor) to draw informed conclusions. The risk, or incident rate, expresses the probability for a drug to become dangerous. Something similar is still missing for cycling. At least at the local scale level.

Geo-located, reported bicycle crashes between 2002 and 2011. Data source: City of Salzburg. Details are published in Loidl et al. (2016 internet).

Alberto Castro internet and colleagues published an extensive study on exposure-adjusted road fatality rates of pedestrians and cyclists just recently. Compiling data from most OECD countries, this is the first systematic study of this kind and a huge step forward. However, the calculated fatality rates are based on very highly aggregated statistics. In the authors’ own words, ‘exposure data was found to be generally poorer than for fatality data, as travel distances of active modes are not systematically collected in all countries’ (Castro et al. 2018 internet, p. 8). Now, if the availability of exposure data is poor on at national level, how to interpret local crash data or so called crash blackspots – a challenge planners and authorities are facing in cities on a daily basis?

In fact, the problem is that we do not know where, when, how many and which types of cyclists are on the road in most cases. Consequently, we are lacking required exposure data. Moreover, we can only roughly estimate the demand for infrastructure and the respective capacity, and finally, the effect of interventions remains opaque. Regarding the interpretation of crash data, the map below perfectly illustrates the problem. The message of the mapped bicycle crashes seems to be pretty obvious: on the road along the river, crashes are recorded every few meters (crash data were collected over a 10-year period). It looks like this road was quite dangerous for cyclists. In contrast, on the parallel road no crashes are recorded at all. Is this the safe alternative? Well, a quick look at the attached street views answers the question instantaneously. The road along the river is a highly frequented cycle way, whereas the parallel road is exclusively dedicated to motorized traffic (plus a narrow sidewalk). Because hardly any cyclist is riding there, no crashes occur. The probability of being involved in a crash is, at least in part, a function of traffic volume.

In order to overcome the limitation of missing exposure data, we have been working on an agent-based bicycle flow model with a very high spatial and temporal resolution in the collaborative research project FamoS internet. This week, I’m going to present results from this research at the International Cycling Safety Congress internet in Barcelona.


The building blocks of our agent-based simulation model are single trips. We expect flow patterns to emerge from individual mobility behavior, which is determined by multiple parameters. With this approach, it is possible to anticipate the heterogeneity of cyclists. Different to motorized mobility, where the machine levels out different capabilities (elderly people are able to drive at the same speed as youngsters), the variety of behavioral variables and riding styles is huge among cyclists. A 4-year old girl on a bicycle has little in common with a bike courier, just to give an example.

In our model, we can control for different socio-demographic variables, such as age, education or employment status. Additionally, we differentiate between different trip purposes, trip length and accessibility of destinations. After initialization, we simulate agent’s activities, schedules, destinations, mode choice and route choice. Of course, such a model requires many data. In the case of a model we developed for the Salzburg central region, we used:

  • Topological correct road graph with a rich set of attributes
  • Census data with a spatial resolution of 100 and 250 meters from Statistik Austria
  • Central facilities and POIs from OGD portals
  • Raw data from mobility surveys
  • Time use statistics from representative surveys

The bicycle flow model was developed from scratch by Dana internet. She did an excellent job by translating the conceptual model into code. The simulation model runs on GAMA platform and will be freely available at OpenABM internet soon. Through a very efficient code structure, we are able to initialize and run the simulation model for a 24-hours day, with 150,000 agents, a temporal increment of one second and a spatial resolution of one meter within only five hours. This very fast runtime makes the model perfectly suitable for sensitivity analysis and simulation of various interventions, such as additional connections or changing behavior of travelers.

Comparison of simulated bicycle trips (left) and recorded data from the Bike Citizens app (right).

The model was calibrated with data from six stationary counters. For model validation, we used tracking data from Bike Citizens internet. In total, we achieved very accurate results. The temporal distribution of bike rides perfectly matches the double peak signature in reference data. The simulated spatial pattern of bicycle flows has a little bias towards the left side of the Salzach river. Reasons for this are expected to be associated with known biases in the input data. In the validation, we also compared the characteristics of simulated and recorded trips. Whereas the mean travel time is much higher for Bike Citizens data (mainly due to a few outliers, generated by long distance leisure cyclists), the average distance and speed distribution resembles perfectly.

To the best of my knowledge, this is the first bicycle flow model at the local scale level with a regional coverage. We use the results for multiple purposes. For example, we could simulate the expected effect of planned bicycle corridors in the city of Salzburg. In the context of safety, the model is well suited to generate exposure data for risk analysis. Referring to the example above, the simulated bicycle flows can be nicely used to calculate incidence rates and subsequently assess the safety of areas and road segments (we published a paper in Safety internet on this topic). In the particular case presented above, it becomes evident that the road along the river is definitely not dangerous. The recorded crashes can be expected from the number of cyclists. However, it is beyond any discussion that every bicycle crash is one too much. Providing adequate infrastructure is crucially important for attracting cyclists and ensure safe rides. Here again, the simulation model helps to estimate the demand and derive required capacities for dedicated infrastructure.

With the agent-based simulation model, we have made a step forward in providing sound evidence to decision makers and bicycle advocates. Nevertheless, it is still a model and thus, it does not mirror reality, but a generalized representation. In order to further refining the model we are currently improving the input data basis In the research project Bicycle Observatory internet, we combine quantitative and qualitative data from different sources for getting an integrated perspective on bicycle mobility. This will help us to include even more parameters in the model and hence, provide a more accurate representation in the spatial, temporal and behavioral dimension.