03. DeepTraffic

Hi, I'm Cezanne Camacho, I have a Masters degree in electrical engineering from Stanford, which is where I first got into machine and deep learning. I love to think about how humans reason, and how we might replicate that reasoning in algorithms. I'm inspired by those with the curiosity and drive to learn something new! To stay up-to-date with my work, consider following me on Twitter.

DeepTraffic

Another great application of deep learning is in simulating traffic and making driving decisions. You can find the DeepTraffic simulator here. The network here is attempting to learn a driving strategy such that the car is moving as fast as possible using reinforcement learning. The network is rewarded when the car chooses actions that result in it moving fast. It's this feedback that allows the network to find a strategy of actions for optimal speed.

Note: At the time of writing, the DeepTraffic competition is over and MIT has taken down its simulator page. For the purpose of learning how to fine-tune deep reinforcement learning hyperparameters to pass the DeepTraffic challenge, you can view one of the many possible solutions on this YouTube video.