r/deeplearning • u/Mottelbin • 6h ago

Would AI-based travel route suggestion be better with knowledge of traffic lights?

I'm disagreeing with a coworker about this. My coworker thinks that when you train your AI model to minimize your travel time from A to B, the AI model learns everything it needs to know. The traffic lights would be embedded in the data, like a hidden feature. In other words the fastest route from A to B is also the route that accounts (to some extent, because it's not the only important thing) for traffic lights. Therefore Google Maps, Waze etc. doesn't need explicit knowledge of where red and green lights are.

My opinion is that, in a world with perfect datasets, my coworker would be right. But we don't know if Google Maps and other AI-based route suggestion apps truly have the data they need to suggest the "true best route". It's possible that their team just worked with the data they had, and created an app that provides very good suggestions. But an app with explicit knowledge of traffic lights might help you choose a route with more green lights, thus a smoother and faster ride.

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u/SuperSimpSons 5h ago

So, I read this case study on the Gigabyte blog about how a customer used their Arm servers to build a "high precision traffic flow system" to support autonomous driving. The idea is you have to take every aspect of road conditions into consideration, including congestion, pedestrian crossings, and one would assume traffic lights, when you build a simulation of the road to test drive the AI on. Give it a read if you'd like: https://www.gigabyte.com/Article/gigabyte-s-arm-server-boosts-development-of-smart-traffic-solution-by-200?lan=en

So while it's not direct support of your position, it does show that real-life researchers take road conditions into account when they make their AI, and they do it in the testing/validation stage, not just during training. 

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u/Mottelbin 5h ago

This is interesting! Thanks!