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100% right focus on traffic decision zero-emissionzones

With the climate agreement, there are also municipal climate targets in which zero-emission zones play an important role. Zones where there is no more room for trucks and certain vans. Not always a fun reality. Writing a traffic decree for zero-emission zones can be a tricky undertaking. It goes against existing traffic orders and, because of the new subject matter, there is sometimes not enough expertise within the organisation. Jaap Tjebbes explains how he helps municipalities with his approach, which innovatively combines AI with human insights.

Traffic decisions an sich are not exactly new, they have long been an important part of municipal decision-making. However, for new types of remediation like the zero-emission decision, new thresholds soon appear. Jaap Tjebbes was able to combine these two data to speed up and qualitatively deepen the process in decision-making. “I came to the conclusion that there are many standards in traffic decisions. So I started to explore whether, with the history of already public decisions (and added data), a basic decision could be quickly created for zero-emission zones via smart use of AI. Of course, different municipalities also have their own templates, but with smart use of technology, I can write a good traffic decision base in a few days.

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Creating more time to focus on the in-depth parts of the decision

That may sound a bit facile and unspecific, but the end justifies the means here, as it turns out. “There is sometimes the stigma as if you use AI to get everything done, but I actually just guessed through a huge library of traffic decisions. This allowed me to arrive at a basic decision faster than usual, which in turn could be used as a good underpinning for further enrichment. Indeed, the great advantage of this is that by saving time, I can pay more attention to more complex issues within the decision.” A complexity that in turn bypasses artificial intelligence.

“Once the first traffic decision was in place, I was able to quickly engage with other stakeholders and so frictions with existing remediation were quickly revealed. Besides the zero-emission zone, there is also the logistics zone, the environmental zone, the car-free area. With the basic decision as a foundation, I was able to seek integral solutions together with the various departments.” And that turned out to involve major interventions down to details that required knowledge from the field. “By superimposing the blueprint of this decision over the others, you immediately see the bottlenecks and avoid adding all kinds of problems during implementation. Think of signs that contradict each other, zones that overlap or not and how the arguments coincide to justify these interventions in the city. Issues that AI just can’t solve.”

Which goes to the heart of the approach: “With the right use of AI, we ensure that human knowledge (from practice) can be applied to the complex issues of parking decision making in a targeted and qualitative way. We prioritise the essential issues and also do so efficiently.” In this way, The Future Mobility Network managed to assist Delft in making the process around the traffic decision for zero-emission zones run smoothly. You can read more about how Delft municipality itself liked it here. Jaap is eager to apply his working methods and insights elsewhere. Also interested in a friendly co-pilot that helps your municipality to quickly reach a sound traffic decision? Then comment below!

Jaap Tjebbes vond een handige aanpak voor de zero-emmissiezones

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