1. Autonomous Vehicle Simulations
Omsai Meka and Landon Powell

2. Motivation and Background
Tesla, BMW, Intel, and several other companies are currently in the process developing autonomous “self driving” cars.
In the production of these autonomous cars, there are several difficulties that have come about for developers.
One important thing about the development of autonomous cars is the fact that the car has to learn how to drive itself from a human.
This makes it difficult to teach the cars how to react in dangerous situations, since human drivers would not purposefully wreck a car while they were in it.
This difficulty has led to the more prominent use of simulators in the development of self driving cars.

3. State-of-Art and Challenges
Microsoft has released a simulator software called the Aerial Informatics and Robotics Platform which can be used with the Unity Game Engine to come up with simulation trials to allow the autonomous vehicles learn.
We will be able to generate different environments and conditions for the vehicle to perform in so that data can be gathered based on each situation.
This data will be used to give the autonomous vehicle more training and resources so that it will have a better idea of what to do.
Another possible platform we can use is Universe which allows users to interact directly with the AI in the autonomous vehicle in relation to different situations

4. Potential Simulations
One simulation that we could use is to have the car drive on a road with slick conditions and choose whether to crash into the sidewalk with people or into a ditch on the other side.
Another simulation can be about making the car learn what to do if the car is stopped and it see another car coming up too quickly from behind which will lead to an accident.
One other simulation could be what the car will have to do to avoid an obstacle in front of it while still making sure not to crash into other cars on its sides.