Image: Thomas Kunz
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The benefits and pitfalls of AI in traffic

Kevin Hofer
27.8.2019
Translation: Patrik Stainbrook

Our transport network is increasingly reaching its limits. According to many, the solution isn't just more roads and trains, but artificial intelligence, aka AI. But how can computers and their algorithms protect us from traffic collapse?

It's just after five on a Friday afternoon. I'm sitting in my car trying to get out of town. Unfortunately, the traffic lamp I've been stuck at for what feels like twenty minutes only lets three cars through per green light. Why is that? Can't this be optimised? Do the drivers across from me suffer from the same problem?

I always ask myself these and similar questions when I'm on the road. Traffic light systems are constantly being optimised. But we're just starting to get AI involved.

AI can help make all modes of transport safer, more ecological, smarter and more convenient. It can be implemented in vehicles and infrastructure and thereby change how means of transport and their users interact. AI also helps evaluate trends, identify risks, alleviate traffic chaos, make transport more economical and manage it.

All the advantages of artificial intelligence come with challenges. These include ethical, social, economic and legal issues. Questions relevant to safety also arise.

How is AI used in road traffic today and what problems does this raise?

AI in traffic

There's a lot going on with AI in road traffic at the moment. Manufacturers are experimenting with self-driving vehicles for public and private transport. These vehicles are equipped with sensors and actuators as well as control units and software.

Uber (in German) is also testing self-driving vehicles. However, the company doesn't only rely on AI in that sector. Uber uses AI in all aspects of its services. From matching drivers to route optimisation.

But AI can also help in road transport. In truck platooning, for example. Several trucks drive one behind the other at a minimum distance. Only the front vehicle contains a human driver. The other trucks follow the leader using AI. This already works very well on the motorway, but in complex traffic situations, such as traffic lights, these technologies still have their problems.

Traffic management also benefits from AI. It analyses traffic patterns, traffic volume and other factors. On the one hand, this can help in planning a road system and reduce congestion. Traffic light systems can also be improved with AI.

All these technologies, in addition to making road traffic more comfortable, would also protect the environment. With liquid traffic, less congestion and optimized transportation, vehicles pump less exhaust fumes into the air.

Risks

Despite its many advantages, AI also carries risks in road traffic. Self-propelled cars give drivers free time; they no longer have to worry about driving. This circumstance could tempt many people to switch from public transport to self-propelled cars. This would destroy the progress made with ecology in transport.

Data protection also raises important questions. AI for self-propelled cars requires an enormous amount of data. They may be protected, but there is still the possibility that third parties could access the data.

AI in transport also raises many ethical questions. How should AI react in an emergency? My colleague Philipp Rüegg will deal with this in another article for our theme week.

In the event of accidents, the question of liability arises. Who is responsible for an accident in any specific case? Liability must be defined according to the level of automation of vehicles. In the case of fully autonomous cars, is only the manufacturer liable?

AI in transport will change jobs, create new ones and also destroy jobs. Some professions such as taxi, bus or truck drivers will probably disappear in the future.

Header image: Image: Thomas Kunz

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From big data to big brother, Cyborgs to Sci-Fi. All aspects of technology and society fascinate me.


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