Cycle Competence Austria @Velocity2017

Take all relevant research institutions, planners and consulters, interest groups, authorities and manufacturers that are engaged in bicycling – voila, what you get is “Cycle Competence Austria” internet, an association of researcher and practitioners, who joined forces for the sake of further pushing the current bicycling boom and making knowledge available.

Klick on the picture to open a short Storify summary of the session.

The world’s biggest bicycling summit – Velo-city internet – takes place in Arnhem-Nijmegen, in the Dutch province of Gelderland these days. Today the Cycle Competence Austria had the nice opportunity to present bicycling knowledge “Made in Austria” to a broad audience.

Being a nation with still a lot of potential for a larger bicycle mode share, but quite exhaustive experiences and a growing body of knowledge, Austria can serve as front runner for so called climbing nations. In this session, six members of the Cycle Competence network presented their respective contribution to a prospering bicycling environment.

Martin Eder, the national bicycle advocate internet, started the series of presentations with an overview of national activities for bicycle promotion. He paid special attention to the second edition of the national masterplan internet, in which the official goal of 13% in the modal split by 2025 is published. In order to reach this, several national initiatives, such as the research funding program “Mobility of the Future” internet are launched and supported.

After Martin, Andrea Weninger from Rosinak & Partner internet shared here extensive experience in bicycle masterplan creation processes. She came up with a list of six points, which she regards to be essential for successful planning processes. Two of these success factors are to go for user-tailored masterplans (instead of copy-pasting elements from elsewhere), which are inspired by locals.

Andreas Friedwagner (Verracon internet) went on with a GIS-based analyses of accessibility and travel time analysis in the federal state of Vorarlberg. His beautiful maps clearly indicate which areas are well-served in terms of bicycle infrastructure and where improvements need to be made in order to motivate people to switch from car to active mobility. Interestingly, Andreas found in his studies that speed limits for cars (30 km/h within residential areas) have the most direct impact on overall bicycling safety.

Currently we are in an interesting transition phase from data scarcity in bicycle promotion to a data deluge (one of Andrea’s argument was that not everything that could be measured really contributes to a better understanding). However, the colleagues from BikeCitizens internet with their CEO Daniel Kofler do a great job in packing routing and navigation, promotion with gamification components and bicycle intelligence into a single app: the BikeCitizens app internet.

The session was completed by two contributions from research institutions. First I gave an overview of three current research project and argued that the spatial perspective facilitates joint efforts across domain boundaries:

After my presentation, Markus Straub from AIT internet presented two projects, each with a spatial optimization component: the EMILIA project internet seeks, among others, to optimize parcel deliveries in cities. In order to so the last miles from central distribution hubs to the consumer should be done by cargo-bikes. Markus and his colleagues have developed a route optimization algorithm for the delivery bicyclists. In the BBSS project internet a spatially explicit planning tool for optimizing the location of bike sharing stations was developed. This tool allows planners to estimate the potential demand for any location in a city.

Got interested in what happens in Austria in terms of bicycling research and promotion? Leave a comment here, visit the Cycle Competence Austria association booth at Velo-city or you can use Twitter internet or e-mail internet anytime.

Floating Bicycle Data

Our colleagues from Salzburg Research (SR) internet are very active in the field of floating car data generation, management and analysis. Among others, this real-time traffic status service internet is fed by their data.
In order to establish a community of researchers, authorities and companies around the topic of floating car data, SR hosts the annual “FCD Forum” in Salzburg. This year, I had the honor to contribute to the program internet. Since we have been working a lot with bicycling data over the last years, I was asked to evaluate the potentials of a conceptual transfer from FCD to “Floating Bicycle Data”. Well, a very fundamental finding in my research is that the term “Floating Bicycle Data” is not established yet in the scientific literature. Thus, the term is to be regarded as a word game derived from the forum’s agenda. However, I think it makes perfectly sense to invest some efforts in this context.

In my presentation internet, I started my argumentation from the fact that a) bicycle traffic is a relevant element of urban mobility, b) the modal share is likely to increase in the next years and c) a sound evidence base is required for future investments in bicycling infrastructure.
Currently, very little is known about the spatial and temporal distribution of bicycle traffic within cities. Comparably few permanent counting stations, sporadic, punctual counting campaigns and irregular mobility surveys do not provide sufficient and reliable data to support evidence-based policies on the local scale level. On the other hand, the popularization of the “humans as sensors” concept (Goodchild 2007 internet) has opened new possibilities to acquire data on bicyclists’ movements in urban networks. When talking about floating bicycle data, I used it as a catchy term, which summarizes all kind of geo-located movement data from bicyclists; they don’t need to be necessarily in real-time.

As I’ve shown in my presentation, there a numerous application examples where floating bicycle data would make perfectly sense. However, there are several conceptual challenges, which need to be considered (most of them are also relevant for floating car data):

  1. When floating bicycle data are harvested through crowd-sourcing applications the data are not necessarily representative for the entire population. I referred to participation inequality or the 90-9-1 rule (see Nielsen 2006 internet) in this context. Additionally, different apps are used for different purposes. Thus, the data might be biased for example towards leisure trips (as it is the case with Strava internet data in Salzburg).
  2. Currently, there is no common data standard and the heterogeneity of bicycle mobility data is huge. Good news in this context were published earlier in this year by the European Commission (see this report internet from the COWI project).
  3. Since there is no obligation to register bicycles, the (spatial distribution of the) total population is unknown. Consequently, it is hard to estimate the total bicycle traffic volume from samples. In contrast to that, cars are registered and at least the car holders’ address is known.
  4. In order to further process movement data (GPS trajectories), a sound and very detailed reference graph is required for map matching. In most cases network graphs are not available at this level of detail (this holds true for authoritative data as well as for OSM). Consequently, GPS trajectories can only be matched to center lines at the moment.

Although this selection of challenges might be regarded as obstacle for a broader engagement (I prefer to interpret them as research opportunities), I expect the topic of floating bicycle data to emerge in the coming years for a simple reason: the market for floating bicycle data is definitely smaller than for floating car data. But, bicycle traffic is already a major element in urban traffic and its share will become even more substantial in the next years. As a consequence, cities need to invest in adequate infrastructure and these investments will hardly be made without a sound evidence base. Floating bicycle data could close a significant gap in this regard.


If you are already working with floating bicycle data (but haven’t used the term yet), have ideas on how to further push the topic or simply want to comment on the concept, please do not hesitate to contact me! I’m happy to learn from your expertise.
For those who are about to write a thesis in this or a related context, have a look at this proposal internet.

Topics for GIScience master theses

After several months of setting the stage and doing lots of preparatory work, we are currently entering the ‘core phase’ in two research projects at the GI Mobility Lab internet. In this context we provide the opportunity to Master’s students to participate in the projects and write their thesis in GIScience (or related fields).

Our part in the FamoS internet project is, among others, to develop an agent-based bicycle flow model for an entire city. In this context we offer two topics:

  1. Behavior to space (description internet)
  2. Exploring geoprocessing, geovisual analytical and mapping functionalities of GAMA (description internet)

Experts from sports medicine, GIScience and transport planning and management are collaborating in the GISMO internet research project in order to provide a sound evidence basis for the promotion of active commuting. Part of the research is a clinical study, in which we document the subject’s mobility by different means. For the analysis of this data we offer the following two topics:

  1. Analysis of movement data from fitness watches (description internet)
  2. Linking travel diaries and GPS trajectories (description internet)

The topics are primarily offered to local internet and UNIGIS internet students. However, I’m also open to any other form of supervision and collaboration, given we find a sound format for it.

Lecture series “Active Mobility”

Since the VeloCity internet conference took place in Vienna in 2013, the Institute of Transportation internet (Vienna University of Technology) hosts an annual lecture series on bicycling and active mobility in general.

This semester, 80-100 students from various planning domains (urban, transport, regional planning) are attending the weekly lecture on “Active Mobility” internet. Yesterday I had the privilege to present parts of my current research and provide an overview of potential contributions of spatial information to an enhanced bicycling safety situation (slides in German language):

Although some of the students have already worked with GIS, none of them employe GIS in the context of mobility or transport research (at least nobody raised his/her hand when I was asking). Thus, I was happy to serve an appetizer for introducing the spatial perspective to a rather “technical” planning community.

Spatial information and bicycling safety

Originally, this blog was intended to document the progress of my PhD research. Mhm, this goal has been successfully reached yesterday …

Successfully defending my doctoral research (pictures by R. Wendel)

I finished my doctoral studies with a thesis on Spatial Information and Bicycling Safety and yesterday’s defense. The thesis internet is based on five peer-reviewed, published papers and aims to strengthen the spatial perspective in bicycling safety research.
The thesis is motivated by the fact that bicycling safety research is dominated by non-spatial domain experts, e.g. with backgrounds in trauma medicine, psychology, bio-mechanics, sociology, epidemiology, engineering, planning, law and some more. Interestingly, the spatial perspective on bicycling safety is hardly ever considered in these domain-specific approaches. This holds especially true for bicycle crash analyses, where basic geographical concepts, such as nearness, spatial autocorrelation and topology, are hardly ever considered.
Neglecting location as a co-determining attribute of safety is remarkable for a very simple reason. Mobility of people – and thus bicycling – as such is spatial by its very nature. Consequently, bicycling safety (from the physical environment to crashes to individually experienced safety threats) has spatial facets, which can be modeled and analyzed accordingly in order to gain relevant information for safer bicycling.

The primary hypothesis of my doctoral thesis is that spatial models and analyses contribute to a better understanding of certain aspects of bicycling safety and provide relevant results, which support measures to mitigate safety risks for bicyclists. Specifically I argued that:

  • Geographical Information Systems (GIS) facilitate holistic approaches for improving the bicycling safety situation. The spatial perspective is relevant for virtually all stages of the implementation of bicycling safety strategies.
  • Model-based approaches have a great potential in safety assessment and can form the basis for a number of applications – from status-quo analysis to planning and route optimization.
  • The spatial analysis of bicycle crashes reveals significant and safety-relevant patterns and particularities, which remain hidden in common, non-spatial or highly aggregated approaches.
  • The spatial perspective is crucial for advanced (simulation) models, which are necessary for reliable risk estimations on the local scale. Furthermore, the spatial implications of risk mapping on the local scale must be made explicit.

The thesis is structured in three elements. The first paper demonstrates the contribution of GIScience to bicycling safety research and is intended to set the stage for the remaining papers. Two of them primarily deal with spatial models in the context of road space assessment and transport modeling, while the rest is about spatial analysis of bicycle crashes.

Structure of the thesis

Although the completion of my doctoral studies is a huge, personal milestone, there is still a lot of research work in this context to be done. Besides the further development of the spatial models, the applied statistical methods and analysis routines, I see research gaps in the context of data (from static to dynamic real-time data and data streams), information (e.g. what are the effects of information provision on decision process or on individual and collective behavior?) and cross-domain collaboration.
The amount of work that still lies ahead motivates me to further blog on some of our research activities and to connect with anyone who is interested in spatial information, bicycling safety, urban mobility etc. I’m looking forward to learning, reading and hearing from you in virtual internet and – even more preferably – in face-to-face communication!

OSMaxx: the easy access to OSM data

OpenStreetMap internet is much more than a free map of the world. It’s a huge geo-database, which is still growing and improving in quality. OpenStreetMap is a great project in many respects!
But because it is a community project, where basically everyone can contribute, it has some particularities, which are rather uncommon in authoritative data sets. There, data is generated according to a pre-fixed data standard. Thus, (in an ideal world) the data are consistent in terms of attribute structure and values. In contrast, attribute data in OpenStreetMap can exhibit a certain degree of (semantic) heterogeneity, misclassifications and errors. The OSM wiki internet helps a lot, but it is not binding.
datamodel_networkAnother particularity of OpenStreetMap is the data model. Coming from a GIS background I was taught to represent spatial networks internet as a (planar) graph with edges and nodes. In the case of transportation networks, junctions are commonly represented by nodes and the segments between as edges. OpenStreetMap is not designed this way. Without going into details, the effect of OSM’s data model internet is that nodes are not necessarily introduced at junctions. This doesn’t matter for mapping, but for network analysis, such as routing!

In 2014 I presented internet and published internet an approach that deals with attributive heterogeneity in OSM data. Later I joined forces with Stefan Keller internet from the University of Applied Sciences in Rapperswil, Switzerland and presented our work internet at the AAG annual meeting 2015 in Chicago.
Since then Stefan and his team have lifted our initial ideas of harmonized attribute data to an entire different level. They formalized data cleaning routines, introduced subordinate attribute categories and developed an OSM export service, which generates real network graphs from OSM data. The result is just brilliant!


Two maps with very different scale made from the same data set.

The service can be accessed via internet. There, a login with an OSM account is required. Users can then choose whether they go with an existing excerpt or define an individual area of interest. In the latter case the area can be clipped on a map and the export format (from Shapefiles to GeoPackage to SQLite DB) and spatial reference system can be chosen. The excerpt is then processed and published on a download server. At this stage I came across the only shortcoming of the service: you don’t get any information that the processing of the excerpt takes up to hours (see here internet).
However, the rest of the service is just perfect. After “Hollywood has called” the processed data set can be downloaded from a web server.

OSMaxx interface.

OSMaxx interface.

osmaxx-downloadThe downloaded *.zip file contains three folders: data, static and symbology. The first contains the data in the chosen format. In the static folder all licence files and metadata can be found. The latter is especially valuable, because it contains the entire OSMaxx schema documentation. This excellent piece of work, which is the “brain” of the service is also available on GitHub internet. Those who are interested in data models and attribute structure should definitely have a look at this!
The symbology folder contains three QGIS map documents and a folder packed full with SVG map symbols. The QGIS map documents are optimized for three different scale levels. They can be used for the visualization of the data. I’ve tried them for a rather small dataset (500 MB ESRI File Geodatabase), but QGIS (2.16.3) always crashed. However, I think there is hardly any application context where the entire content of an OSM dataset needs to be visualized at once.

Of course, OSMaxx is not the first OSM export service. But besides the ease of use and the rich functionality (export format, coordinate system and level of detail), the attribute data cleaning and clustering are real assets. With this it is easy, for example, to map all shops in a town or all roads where motorized vehicles are banned. Using the native OSM data can make such a job quite cumbersome.
I have also tried to use the data as input for network analysis. Although the original OSM road data are transformed into a network dataset (ways are split into segments at junctions), the topology (connectivity) is invalid at several locations in the network. Before the data are used for routing etc., I would recommend a thoroughly data validation. For the detection of topological errors in a network see this post internet. Maybe a topology validation and correction routine can be implemented in a future version of OSMaxx.

In the current version the OSMaxx service is especially valuable for the design of maps that go beyond standard OSM renderings. But the pre-processed data are also suitable for all kinds of spatial analyses, as long as (network) topology doesn’t play a central role. Again, mapping and spatial analysis on the basis of OSM data was possible long before OSMaxx, but with this service it isn’t necessary to be an OSM expert and thus, I see a big potential (from mapping to teaching internet) for this “intelligent” export service.

VeloCittà bikesharing & POLIS conference

We contribute spatial information to the design and optimization of a city-wide BBS.

We contribute spatial information to the design and optimization of a city-wide BBS.

150 participants from 23 countries gathered on November 30th in Rotterdam to attend the VeloCittà internet bikesharing conference, which was held in conjunction with the annual POLIS internet conference (450 participants, according to the organizers). While the VeloCittà conference was exclusively dedicated to bikesharing, the POLIS conference offered a broader perspective on sustainable transport. I was in Rotterdam primarily for the POLIS conference because I had a presentation, but it was also a great opportunity to get an impressive update of recent bikesharing practice and research. Lot’s of what I’ve learned can be directly linked to our current involvement in the planning of a bikesharing system in Salzburg, Austria.
All presentations of both conferences can be found on the respective websites. Thus, I will focus only on two topics I’ve found especially relevant for our research and project work.


Willemijn Lambert (@WM_Lamber internet) captured the essence of the VeloCittà bikesharing conference.

Success factors for bikesharing systems

polis2016aIn a very interesting session at the POLIS conference on sharing systems, Sebastian Schlebusch from Nextbike internet gave some insights into the company’s history. Several years they were treated quite harshly by public transit operators who feared for their business. However the break through of bikesharing systems (BSS) came. In accordance with Sebastian’s talk the following success factors occurred in various presentations at both conferences:

Cologne's bike sharing system (KVB Rad) is integrated in the city's public transit service.

Cologne’s bikesharing system (KVB Rad) is integrated in the city’s public transit service.

  • Political support. Obviously this seems to be the most decisive factor for successful BSSs in any country.
  • Integrated systems. An increasing number of cities regard bikesharing systems as an element of public transit services. This is reflected in the planning of the network, pricing and promotion. Cologne’s BSS internet is a good example for a large, integrated system.
  • Robust business models. This factor becomes important when initial subsidies fade out. Alberto Castro internet, one of the keynote speakers at VeloCittà, demonstrated how fast BSSs without sound financial (and operational) basis disappear internet.
  • Appropriate planning. Nicole Freedman, keynote speaker at VeloCittà, made a compelling case for the importance of realistic projections and tailored BSS design. Cities are comparable only to a certain degree and thus, BSSs cannot be simply transferred. Specific (mobility) characteristics of cities, from PT service level to topography, need to be taken into account.
  • User-tailored, easy solutions. The needs and expectations of users must be addressed in every aspect: from intuitive interfaces for initial registration to the ease of handling the hardware.
    To know and consider people’s reasons for not using BSSs is especially valueable when systems should be improved. In many cases the barriers for BSS usage can be lowered or removed with small adaptions.
  • Visibility in public space. In order to raise awareness for bikesharing it is necessary that the system is visible in public space. This visibility can be achieved by an appropriate station design, but also with art in public space.
  • Make it beautiful. Directly associated to the latter point Nicole Freedman strongly argued for aesthetically pleasing, beautiful bikes and infrastructure. Way too often BSSs are shaped by technicians and technology. With a good design of hard- and software people can be made curious; once they are attracted to the system, the possibility is high for turning prospective into active users.

polis2016cAt both conferences lots of case studies were presented. At least two of them were really remarkable:
Krakow (~ 760,000 inhabitants) initially launched a system with 30 stations and 300 bikes, which turned out to be not that successful. Thus, the city relaunched the entire system under a new name (Wavelo internet) and with 1,500 bikes at 150 stations, which is above the average bikes per people ratio in Europe (ref. OBIS internet handbook)!
A much smaller, but very successful BSS can be found in Pisa (CICLOPI internet). Marco Bertini presented the city’s strategy to make people in Pisa love their bikesharing system: “Bikesharing is note a service for citizens, but part of the community.” With this approach Pisa achieved impressive key figures: 5-8 rides per bike and day, virtually no vandalism and not a single bike stolen in 4 years.

Road Safety

polis2016dMore people are killed in road crashes than by malaria or tuberculosis, according to a recent OECD report internet that calls for a paradigm shift in road safety. Before this background and with a special focus on the role of large cities the International Transport Forum (ITF internet) launched the Safer City Streets internet project, which was presented by Alexandre Santacreu. The aim of this project is to provide an environment for exchange of data, experience and knowledge. What I regard as an asset of this project is the drive to publish data as OGD.
Alex pointed to the difficulty of comparing data from various sources, especially when crashes of vulnerable road users are investigated (different reporting procedures, classification, under-reporting etc.). Of course, this is nothing new, but my impression is that the limited comparability of data is mostly neglected in analyses of global data (I’ve demonstrated an aspect of this in this post internet).

While the Safer City Streets project operates on the global scale, the Netherlands have launched a national project where cities can learn from each other with respect to crash prevention and safety measures. Charlotte Bax from SWOV internet presented this benchmarking project that is built upon the three elements comparing – learning – improving. Two aspects caught my attention: (1) None of the data are made public because the involved city administrations fear the pressure that might be put on them after publishing crash details. (2) Even in the Netherlands’ city administrations struggle to make use of their data; Charlotte referred to cases where responsible departments were not able to tell how many kilometers of bicycle infrastructure they had.

Benchmarking on the very local level was at the core of Eric de Kievit’s internet presentation on the development of a compound road safety assessment. For this, two approaches were combined. Firstly, a network safety index, which consists of an enormously detailed description of the road space (every 25 meters the road profile was investigated based on street view photos). And secondly, a safety performance indicator that focuses on road user’s behavior. Both perspectives are then used as basis for targeted infrastructure measures, law enforcement, education and communication campaigns.

My own contribution to the session on road safety was about spatial analysis of bicycle crashes on the local scale level. The presentation was a synthesis of two of my latest journal papers (JTRG internet and Safety internet):


In both conferences it became evident that there are lots of innovative and creative solutions for promoting sustainable mobility in urban environments. However, there is no philosopher’s stone that solves all problems immediately, but cities all over Europe have to work hard to make progress.
I have the strong impression that the discussion and collaboration across domains and institutions is a key for sustainable solutions for cities. Urban environments are complex and thus require multifaceted strategies. In any way, we are ready to contribute spatial expertise for the good of our cities and their citizens.