Cycling data as a change agent for sustainable mobility

13th ITS European Congress, Brainport, the Netherlands, 3-6 June 2019

Paper number ITS-XXXX Cycling data as way to enhance sustainability in smart cities R.J. Lindeman1*, W.J. de Kruiff2 1. Rijkswaterstaat, The Netherlands, rick.lindeman@rws.nl 2. Breda University of Applied Sciences, The Netherlands

Abstract The Netherlands is known for its high cycling shares and great cycling infrastructure. What many people less realize is the challenge to increase those shares even more to enhance cycling in the sustainability smart cities objectives. To push cycling to the next level a national collaboration has been set up to join forces in the field of cycling data collection, storage, visualisation and analyses.

Next, cycling knowledge sharing between a variety of stakeholders, ranging from academic to highly applied level, is essential. This paper not only covers an overview of challenges of the national organisation and the development of a cycling data platform but also shows how European award winning best practises add to the smart city objectives in the Netherlands. Combining mobile phone data, GPS/GNSS data, traffic light data, national survey data, traffic forecast model data and virtual and augmented reality results in a joint approach to smart cycling cities and ITS cycling developments.

These developments can lead to a greener mobility system, but if done wrongly eradicate the strengths of cycling in an autonomous-vehicle dominated city.

Keywords: Cycling, Traffic Management, Data visualisation

Cycling data as way to enhance sustainability in smart cities

Introduction Modern society faces various challenges with regard to sustainable mobility policies. Cities strive to stimulate a change in behaviour from current car-dependent lifestyles towards and simultaneously increase the economical accessibility, social cohesion and liveability and to decrease the negative environmental impact of current car-dependent lifestyles. The bicycle is often regarded as the sustainable alternative to meet the objectives, where the e-bike offers even more advantages where it mitigates negative effect of speed and effort related to the regular bicycle. Although the Netherlands is known for its high cycling shares in the total mobility patters, the sustainability challenges are not less than any other international modern city. In order to accelerate the cycling policy renewal in Dutch cities and regions in becoming smart cycling cities, Dutch government, academia and the industry join forces to uniform data collection, storage, visualisation and analyses. Next, cycling knowledge sharing between the wide variety of stakeholders is being tackled. All of these aspects are challenges in itself.

Therefore a taskforce Cycling Data and Knowledge sharing is being created, striving to accelerate to the whole chain of aspect from data collection to monitoring and evaluation. Over the last two years several milestones have been reached in the process. This paper reflects on the setup of national cycling knowledge collaboration, the development of a national cycling data platform and smart cycling city monitoring and evaluation dashboard.

Cycling has long been a world where the influx of ITS was relatively slow. The low-tech cheap way of moving, the limited geographic popularity of the mode and the anarchic image cycling contribute to this. This is changing rather rapidly, both in the recreational sector (Strava) and commutes more and more data is collected. This leads to both new insights in cycling behaviour as to a way to include cycling in smart traffic management solutions. Still there are many barriers within this traditional local / SME sector to provide a similar service compared to cars.

This paper describes the developments in the sector and discusses the challenges ahead based on the experiences in the Netherlands, the country with the highest cycling modal share in the world. These developments can lead to a greener mobility system, but if done wrongly eradicate the strengths of cycling in an autonomous-vehicle dominated city. We start with an overview of cycling in the Netherlands. Then we look into some developments on gathering more data. The next section is dedicated to the relation of bicycles and smart mobility (particularly ITS traffic management). Then we discuss some challenges we see arising on further development. We round up the paper with a number of conclusions.

Cycling in the Netherlands We owe much to our bikes. The bike keeps our inner cities accessible and liveable, brings many people to work and is indispensable in the countryside on the way to school, the grocery store or the

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Cycling data as way to enhance sustainability in smart cities

bus stop. And the bike supplies - more than we often realise - an important contribution to our health because it keeps us moving. In short, the bike produces many social benefits, for example in the areas of health, environment, economy, sustainability, accessibility, and so on. We have to cherish the bike.

Figure 1 – Proportion of Bicycle use as a percentage of total number of trips in several countries (Bueher and Puchler 2012 )

In the Netherlands, bicycles outnumber residents The Netherlands accommodates 17 million inhabitants and 23 million bicycles. Increasingly more Dutch residents own an e-bike; of the 23 million bicycles, 2 million are e-bikes. Half of all passenger car trips are shorter than 7.5 kilometres (=3.6 billion car trips), one-third are shorter than 5 kilometres (=2.5 billion car trips). Of all trips involving a distance up to 7.5 kilometres, one-third are made by car and one-third are made by bicycle. Of all trips involving a distance ranging from 7.5 to 15 kilometres, 70 per cent are made by car and 15 per cent are made by bicycle. For all trips the share is even 25% (All data in this section are from Harms and Kansen (2018) Recent developments The bicycle has been on the rise in much of Europe. Bike-sharing systems are popping up all over the world and when done well change the city. In the Netherlands, cycling in cities is on the rise as well.

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Cycling data as way to enhance sustainability in smart cities

Furthermore, due to the e-bike, more and more inter-city trips are becoming viable.

This is accompanied by a rediscovery of the bike as a policy measure by the different government layers. This resulted in the National cycling agenda by the Tour de Force (2016)3, which sets a route to the next level in cycling. This included new facilities like cycling, but also an impulse for IT and data by the afore-mentioned task force.

Cycle policy renewal by open cycling data In order to renew and innovate mobility policies cities develop Sustainable Urban Mobility Plans (SUMPS). With these plans cities set up a framework to increase its sustainability city print over time.

In order to measure effectiveness of sustainability measures many data driven solutions have been developed over time. These data driven solutions gather more and more data using smart data sensing.

With the technical evolution more and different forms of data are being generated and stored. Many projects nowadays are focused around the topic of data, varying from enhancing data collection techniques, resolving data privacy issues and storage to data fusion and the translation of data into policy relevant information. The objective to develop an online open cycling data platform is yet the starting point for cities with regard to the transition into more sustainable daily urban mobility patterns, where the behavioural change is key. In order to maximize the benefits of these new forms of data, policy profits the most if standard agreements can be made with the industry about data availability and accessibility. The first challenge therefore was to set up a process to create open cycling data. By creating on overview of the many different forms of cycling data was the first step, followed by the substantive detailing of algorithms to actually create open cycling data. For both components different specialists are required which were brought together creating an national open cycling data platform with uniform rules, standards and guidelines.

Figure 3 – Combined efforts of Dutch agencies for cycling data

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Cycling data as way to enhance sustainability in smart cities

To date, a framework lacked how these new data can add to the SUMP cycle. Related to this question, the individual privacy has to be guaranteed at all times. To date, only local explorative attempts had been made to develop protocols to anonymize data for storage and open data sharing in different mobility fields like PT and cycling, but a comprehensive framework lacked. Optimization and uniformity of the process has been conducted in dialog with data suppliers. Next, an effective data-sharing partnership scheme has been developed that underpins and ensures adequate spatial and urban planning, funding of future transportation services, commercial business models of the private parties, and guarantees citizen privacy and data security. Establishing and clearly communicating the potential benefits resulting from the data partnership to public and private-sector stakeholders is crucial. Partners and citizens should also be assured that the data being collected is used for the purposes for which it is intended and will not be used in any way that harms the operations of the partners. Consideration also needs to be given to concerns around reputational impacts or that sharing data may breach privacy, security and competition laws.

This national platform will be released in the Dutch context early 2019, but can also be easily translated into the international context. This is already a first breakthrough regarding cycling data, where in many smart city related issues cycling data lacked and was ignored or regarded in a more qualitative manner.

When the Tour de Force taskforce was created in 2017 it was discovered that cycling data meant different things to different people. Furthermore, most initiatives were small and not easily scalable to a national level. In the last 2 years we have managed to join forces and develop new scalable business models.

Transforming open cycling data into information Having dealt with all data issues, the question that is just as important to raise is what knowledge and insights should be generated, incorporating various information demands from policy makers, local stakeholders and citizens. Targeting sustainable changes in daily urban mobility behaviour parts of the SUMP process are already enriched by several forms of tracking mobility and fusion of available and newly collected “Big Mobility Data� (BMD). Over the years several dashboards have been developed to translate this BMD into policy relevant insights. Translating these insights into decision support information allows to better deploy the urban mobility offer in response to existing and changing demands, while respecting citizens’ individual privacy. This last step of empowering the SUMP-cycle with the data - insights - information needs optimization for cities to fully benefit from emerging technologies and computer science, First, Policy Renewal and Innovation is partly brought about by presenting information in an effective manner, providing ex ante scenarios and showing sound ex post evaluation of SUMP measures.

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Cycling data as way to enhance sustainability in smart cities

Second, the variations brought about by the social, cultural, natural and spatial context have to be taken into account. As homogeneity or heterogeneity have a large impact on urban mobility patterns, the availability of different data forms should be taken into account. Third, taking all context related variables and area type into account the SUMP process can be linked to important location specific stakeholders (e.g. large employers, visitors and tourist attractions) and inhabitants providing them with tailor-made mobility information from BMD accelerating a shift in the daily urban mobility demand.

Finally, the use of open data will lead to the development of new forms of mobility services and infrastructure, a transformation in the use of vehicles and more efficient and lower impact city logistics mitigating the negative effects of transport effectively. With regard to the whole process, several parts need specific attention in order to accelerate the existing SUMP process empowered by data.

In order to accelerate the usage and translation of open cycling data into policy relevant insights various parties are working on new visualisation and analysis techniques using not only regular cycle count data, traffic forecast data, national survey data but also GPS/GNSS data and (intelligent) Traffic Light data. By merging these different forms of cycling and combing them with for example weather data new insights are created and explored. In this process close collaboration with scientific partners is key.

Obvious opportunities of big-data relate to increasing data accuracy, the opportunity to collect data over longer time periods, larger areas and the ability to track individuals’ route choices. While this allows for more disaggregate analyses, each type of data has its own biases, limitations and levels of openness. The technical development together with the rapid global penetration rate of the smartphone caters for new location based data. This location based data (e.g. floating car data) can encompass thousands of people and multiple time periods.

Early 2019, Breda University of Applied sciences will present their first results to the Dutch frontier cycling cities in order to balance between applied scientific curiosity and practical applicability. The main objective of the work is not only addressing cycling policy related topics but also optimizing the open data platform development agenda. By putting the open cycling data into practice by integrating these in visualisation and analysis toolkits creating new insights opens a new array of possible cycling solutions. Because the cycling data reflects the actual cycling in the city and region a policy shift can be obtained from a mainly infrastructure and supply driven towards a customer oriented city design.

Putting information into practice The provinces of Noord-Brabant and Gelderland joined forces in achieving their shared objective: becoming the best cycling region of the Netherlands. The development of an extensive network of Cycle Highways is regarded as one of the key measures to reach the objective of 35% cycling share in

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Cycling data as way to enhance sustainability in smart cities

2030. Because Cycle Highway development is a major investment, the demand for a sound quantitative substantiation is requested.

An increasing array of data sources is available for monitoring cycling behaviour including cycle counts, GPS/GNSS-data, cell phone data and large-scale surveys. Both regions monitor cycling on existing and still to be constructed Cycle Highways. Together with Breda University of Applied Sciences a state-of-the-art Cycling Intelligence monitoring and evaluation dashboard was developed within the EU project CHIPS to evaluate the effect of cycle policies, measures and impact of Cycle Highways5.

Based on multiple already obtained data sources, indicators have been developed where from interesting conclusions can be drawn about the actual cycling behaviour. Next to fluctuations in volume, also origin/destination, route choice, speeds and delays. These indicators and their changes over time are visualized and evaluated. The total process was developed with an easy entry approach where smart regions without having the full range of data available can take up monitoring. This approach is gaining international interest where more regions want to take cycle monitoring up to the next level.

Next to an explanation about the techniques, our contribution will be focused on sharing our conclusions about the impact of our cycle highway development. It is interesting to be able to display a massive increase in bicycle kilometres travelled on cycle highways causing a decrease in environmental impact. With all the new insights Dutch governments opt for a more customer based cycling policy in order to take the next step in increasing regional cycling.

Intermezzo: from policy to marketing and back again Working on the platform for cycle data we came across the potential benefits of cooperation with service providers. In order to help their clients on a bike to find the best route, to see how healthy they have become or to lead them to bike parking places, industry is generating data and is keen on sharing data order to provide better services. MaaS will be the next stage in this movement that will be more and more relevant for the bike and the use of the bike. MaaS is relevant because when people will make choices based on information provided by MaaS-systems, a modality which isn’t compliant with Maas-requirements, won’t be chosen.

As government agencies setting up the data platform we aim to profit from this willingness to share data as long as we can give something of value back. In the end this will lower the maintenance costs of the platform and will stimulate directly (by means of of the commercial services) and indirectly (by means of better policies) the use of the bike. Talking Bikes is an example of how this philosophy will work in practice.

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Cycling data as way to enhance sustainability in smart cities

From Talking Traffic to Talking bikes?

Huge volumes of data are available about speed, driving behaviour and location. By being continuously ‘connected’ we are in a position to share that data. In the Partnership Talking Traffic, public and private parties are working together to access knowledge and data which can subsequently be made available in real time, for individual road users, via tailor-made applications. These innovative services enable road users to see beyond their windscreen4.

Traffic flow, cost savings, sustainable Traffic and transport are becoming increasingly intelligent. Information technology is already able to improve the use of road capacity. By approaching mobility issues ever more smartly, journey times can be further shortened and traffic flows will be improved, resulting in lower government spending.

Fewer wasted kilometres, less unnecessary braking and acceleration, no more delays with red traffic lights when no other road users are nearby, more cars driving ‘through green lights’; in addition to these advantages, savings can be made in costs and fine particulates and CO2 emissions can be reduced.

Agreements have been reached with all partners to ensure that Talking Traffic services make the maximum possible contribution to reducing the number and improving anticipation of unsafe traffic situations. Specific demands have also been imposed on all partners to ensure that road users are able to make safe use of these services while in the car or on the bicycle. In every case, the underlying principle is: the driver (cyclist) must at all times be able to focus fully on the road.

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Cycling data as way to enhance sustainability in smart cities

Figure 3 – Talking bikes integrating to the Talking Traffic ecosystem

Talking bikes It has been a challenge to include bicycles as part of the talking traffic ecosystem. Cycling data companies are often small companies with a relative small innovation budget. To accelerate the development of cycling ITS. The Dutch government will now make an effort to ensure cycling can be a part of this ecosystem. The result will (hopefully) be that bicycles will be seen by and can interact with a smart traffic management system. This is essential for the system – especially in the Netherlands – since otherwise the traffic management system won’t be able to consider all modes when it decides about the optimal safe traffic flow. Furthermore, this allows cycling data service providers to develop new services for cyclist like information about green traffic lights and allow pelotons of cyclists to pass at once.

Challenges When looking at the combination of cycling and data, there are three types of challenges: challenges

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Cycling data as way to enhance sustainability in smart cities

about the collection of representative data, challenges on the organisation and challenges regarding the nature of cycling and cyclists.

All apps we have seen until now are only registering certain types of cyclists: either sportive, commuters or bike-enthusiasts. High school children, one of the largest groups of cyclists are underrepresented. Furthermore, all these apps have relied on voluntary participation, which means only a small part of cyclists register. This leads us to look at other forms of data (e.g. phone data, traffic light data) Until recently there was no organisational model to collect data. This meant lots of municipalities developed (or were seduced to buy) their own apps. With the efforts of both the Task force of Tour de Force and Talking Traffic there is now a standard for cycling data, and are we working on the next steps.

Cyclists are not used to have technology on their bicycles. Often bikes used in Dutch city centres are old and in sad condition. This is because of the risk of theft. Slowly this is changing. Because of the building of many new safe storage facilities, the rise of shared and leased bikes (which have tags) and with the omnipresence of smart phones there are now many more potential sources. Still, many cyclists prefer the privacy and the freedom bikes offer (there are no license plates). This could be a risk in connected smart cities, when infrastructure is built on connected vehicles. In the most negative scenario this could lead to the demise of Dutch cycling culture.

Conclusion The use of data and ITS is a rapidly developing field. There are many different outcomes possible, but the experiences in the Netherlands suggest that the added value to transport policy and dynamic traffic management can be huge. The cycling industry is slowly preparing for this future by implementing GNSS-tags and developing new services. Hopefully, together with the experiences in Denmark and other like-minded countries this can lead to a truly data-driven transport system, without sacrificing the benefits of the freedom of cycling. In Dutch we call desire lines Elephant-paths (Olifantenpaadjes).

They’ve come to symbolise the way cyclists choose their own path, and thus creating their own mobility system. Let’s hope a future mobility system will facilitate this, and not walk like an elephant (or bull) in a china shop.

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Cycling data as way to enhance sustainability in smart cities

References 1. Harms, L, and Kansen M.. (2018), Cycling Facts, KIM, Netherlands Institute for Travel Policy Analyses The Hague, Netherlands.

2. Pucher, J. and Buehler, R. (2012), City Cycling. MIT Press. ISBN 9780262517812’. Transport Reviews, 33 (2). pp. 239-240. ISSN 0144-1647 Available from: http://eprints.uwe.ac.uk/21831 3. Tour de Force (2016), National Bicycle Agenda, available from Tourdeforce2020.nl 4. Talking Traffic (2018), New Intelligent Traffic Solutions, from talking-traffic.com 5. Ruebens, C. (2017), European Cyclist Federation, Introduction to Chips, available from http://www.nweurope.eu/media/4577/chips-general-introduction.pdf

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