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Juan de Dios Ortuzar: “We need data to make good decisions in Transport Planning”

Juan de Dios Ortuzar: “We need data to make good decisions in Transport Planning”
Juan de Dios Ortuzar: “We need data to make good decisions in Transport Planning”

Juan de Dios Ortuzar was in MSC to give us two lectures about Transport and Mobility. Full time professor at the Academic College of Engineering, PUC, since 1972, he is a pioneer in the development of discrete choice models and its applications to assess willingness to pay to reduce externalities (accidents, noise and pollution).

Juan de Dios Ortuzar was in MSC to give us two lectures about Transport and Mobility. Full time professor at the Academic College of Engineering, PUC, since 1972, he is a pioneer in the development of discrete choice models and its applications to assess willingness to pay to reduce externalities (accidents, noise and pollution).

We had the opportunity to talk with him about the content of his class, the importance of performing good surveys of transportation and the different models of collecting data. Here is the interview.

Why data collection is so important for Transport Planning?
Data collection is a much extended subject. It is not just about Big Data, using smart cards for transportation or mobility, which allows planners to understand where citizens are. 

Data needs a model. In my class, I want to relate how people travel and how they are. We need explanations on the citizens’ behaviour. For instance, you can collect data from some person that in the morning goes to work, or to study, at noon goes for lunch, and then comes back to home. Of course, you have certain information about this person: age, gender, incomes… Depending of these attributes, methods of travelling will be vey different, but now, in recent times, there have been developments and we can have more information about people perceptions.

For instance, if you are a green person you would use the bike more often, but if you don’t mind ecology, you will use cars more than bikes. These attitudes and perceptions need to be collected as well, and they are crucial for Transport Planning.

Which are the current best examples (companies, public administrations…) of Transport Planning in the world?
The best examples are located in Australia and Germany. They take very seriously the job of collecting data. They do it in a regular basis and they use the most advanced methods. In other cities, like Madrid, they have very good data to use, with lots of potential.

Why Smart Cities need professionals able to understand data and Transport models?
Transportation is essential for the life of the cities. We need to be capable of understanding it and, if we do not have data, we are going to make bad decisions. Data is something essential. And then, certainly, we have to be able to understand a complex system and summarize it in a simpler model to analyse it.

And this is how models can help us, because with models you simplify reality, and you are able to better understand which things will work and which will not.

One of the mistakes that politicians make is that they don’t believe in models. They think they can just imagine how things should be done. But it is such a complex system that, actually, they can not imagine it and, so, they make mistakes. This is something that is happening all around the world just right now.

I have the feeling that politicians consider technics opinion. But we, as transportation planners, have to be able to explain people what we do. Our objective is explaining the data we give them, so they can make better decisions. 

And there is another very difficult issue: Implementation. You can imagine solutions, but implementing them is very difficult.  Details are crucial, and only engineering solutions can solve them, things like stations design or roads, or streets… number of details is very big.

How will Smart Cities be in 30 years?
Your question is incredible difficult. In 30 years everything can happen. Actually, we do not know what is going to happen. There may be some inventions, disruptions, which can change everything. For example, cars without drivers, roads where cars are separated just by millimetres at a very high speed. 

For example, ten years ago nobody could expect the success of the system of rental bikes in Spain. It is amazing… and really difficult to imagine. But I am sure of something: we would need more data to achieve our goals.

And what might be these disruptive solutions that can change the future?
Collaborative economy, Uber, electric bikes… any invention can trigger substantial changes. If they work, they can have an impact. But the impact is very difficult to size. And, of course, they need to work…

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