"Algorithms should not take over urban planning"

We talked to Thuy Chinh Duong about how we can use data to develop our cities and urban mobility.

Thuy Chinh Duong is working on solutions for sustainable mobility. She is mainly responsible for product development at MotionTag, a Potsdam-based startup for electronic ticketing solutions and data analytics in public transport. Prior to that, she worked for several years as a strategy consultant in the public sector and as a design thinking coach at the D-School and the HPI Academy, among others.


Ms. Duong, you are working on data analytics solutions for public transport. It seems to make sense to use Big Data when planning or optimizing traffic. Who is involved in such data-driven projects?

When planning and optimising transport, these are primarily cities and transport operators, i.e. public transport companies, but also transport associations, and of course also private providers. They produce a great deal of data from completely different sources, e.g. static data on road and line networks or vehicle data. This data only becomes interesting when combined with dynamic real-time data, i.e. data on capacity utilization or usage.


It is said that data is the capital of tomorrow. But this capital is worth nothing if the inventive spirit in dealing with this data is lacking. It takes the right questions to ask the data. What are your current questions?

We ask ourselves the fundamental question, for whom these data are interesting. We not only consider a means of transport in isolation, but also ask where, for example, the customer acquisition potential for public transport as a whole exists. Who can we get to switch from private cars to other forms of mobility? For this it is necessary to get data from as many areas as possible. In order to get meaningful results, the data must be handled wisely and intelligently combined.


Data suggests objectivity. However, urban development and transport planning are political issues. How does that fit together?

Data in itself is objective in the first place. A problem is often the incomplete data situation, or that data is not meaningful. There are shortcomings with many data, e.g. in the up-to-dateness. However, there are also problems with the exchange or accessibility of data. Moreover, despite their objectivity, data are often not comparable. For example, it is very difficult to compare the use of private cars with that of public transport, given the different costs and prices. It often gets political when it comes to evaluating the actually objective data. There are actors who do not want data to be collected because it is feared that this will expose that unnecessary means of transport are offered on some routes. This would mean that cuts could be made at these points and thus part of the funding.

In the 1950s, 60s and 70s, the concept of a car-friendly city prevailed. How do you see future topics for traffic in the city?

I believe that the new buzzword is the traffic turnaround. This includes several points, including decarbonisation by switching to alternative, climate-friendly drives such as electricity. But the issues of safety and the declared goal of zero road deaths are also included. All in all, there is a consensus that we are moving away from the car. An open question is still whether a turnaround away from the private car with an internal combustion engine is sufficient or whether the car generally needs to be pushed out of the public space even further. There are many who want to work even harder towards sustainable mobility and design cities worth living in, also with a view to greater use of public transport and cycling.


If you combine this with the trend of urbanization - that is, that cities continue to grow - the question arises how data analytics projects can help with urban development and the planning of main traffic and commuter routes?

If one assumes a growing city, one must naturally expect that the demand for transport will increase. Data helps to say very quickly and very precisely where this demand is increasing. These results can be incorporated into the planning of new transport services, which also helps new private transport providers to assess where offers will pay off economically in the future. If demand for private offers is too low in terms of time or space, cities can take the lead, find solutions and develop other, publicly controlled mobility offers.


Does this not entail the risk that urban development will mainly take place on feeder routes and existing local transport routes, because demand is concentrated there?

No, this danger does not exist, since urban planning does not only blindly follow demand, but also has the task of providing services of general interest. Demand is measured, you can see where people are moving during the survey and then you can initiate control. When collecting data, you can see not only where there is a lot of traffic, but also where there are supply gaps. It is possible to change these currents.


Cities also have their charm because they are wild and disordered. Where do Data Analytics reach its limits? Will our cities be sterile in the future?

The limits are the human capacities, e.g. in the classic "information overload". It will come to the point where more information no longer helps because it is not processed at all. Data can underpin decisions, but the moment of decision remains human. Human experience and creativity are required in the management and design of cities. I do not want to live in a city where algorithms take over the entire city planning. The keyword sterile data does not apply here because it needs the design aspect.


What does optimal cooperation between public transport and private mobility providers look like?

I believe that an open data approach is important as a basis for close cooperation. This would make data that should actually belong to the general public accessible and usable for machines. Then private actors could also look at the data and consider which cooperations could be of interest to them and where they could actually create added value for end customers with the data. Then there are also company cooperations in the sense of mobility stations. This involves identifying different points in the city where different offers come together. Then there is Mobility-as-a-service, an area where different actors need to come together to create an attractive product.


Will we have just one app to manage all our mobility in the future?

That is the wish of the perfect allrounder. Of course it would be very convenient to have something like this and I can also imagine that in the future there will be a market consolidation and certain apps will prevail, but I still believe that there will not be the one app that can do everything. Ideally, we will have many apps that are interoperable and integrated into the various offerings. If we have many apps, competition for the better UX and the customer interface can also arise. In Berlin there are the BVG and the VBB app, which are quite widespread, so the market there is already quite well penetrated. If you take the view that public transport has to be the backbone in a growing city, so that the city remains livable and not everything is fully parked with cars, then you have to use and strengthen the market penetration of these apps, and e.g. integrate more functionalities into these apps. It would be nice if I could use these Berlin apps in Munich and vice versa.


Will mobility as a service offers or the integrated mobility of tomorrow make mobility a white label product that is all about getting from A to B quickly and cheaply?

Mobility is always a means to an end: I want to get somewhere as quickly and cheaply as possible. The emotional charge is always only an additional factor, but not the determining factor, not even in car use. Four factors are decisive: price, time, safety and comfort. With Mobility-as-a-Service, too, the user experience and user interfaces can be designed so that they are emotionally charged and have a positive image. Finally, perhaps a thought-provoking impulse: when we talk about mobility in cities, mobility to and fro and data to and fro, we are always ultimately confronted with urban concerns and we must not forget to look at what mobility and transport planning actually do to cities. If I need five more minutes to get to work but have a city where children can actually play safely on the street and there are no accidents, then maybe it is worth more than the small loss of time. I think you always have to bear that in mind when you think about future mobility concepts, this subordination to the topic of urban design as a whole.


Thank you very much for the interview.