fix typo

README.md

@@ -40,7 +40,7 @@ python eval.py --model_path ./models/tinyphysics.onnx --data_path ./data --num_s
 You can also use the notebook at [`experiment.ipynb`](https://github.com/commaai/controls_challenge/blob/master/experiment.ipynb) for exploration.
 
 ## TinyPhysics
-This is a "simulated car" that has been trained to mimic a very simple physics model (bicycle model) based simulator, given realistic driving noise. It is an autoregressive model similar to [ML Controls Sim](https://blog.comma.ai/096release/#ml-controls-sim) in architecture. It's inputs are the car velocity (`v_ego`), forward acceleration (`a_ego`), lateral acceleration due to road roll (`road_lataccel`), current car lateral acceleration (`current_lataccel`) and a steer input (`steer_action`) and predicts the resultant lateral acceleration of the car.
+This is a "simulated car" that has been trained to mimic a very simple physics model (bicycle model) based simulator, given realistic driving noise. It is an autoregressive model similar to [ML Controls Sim](https://blog.comma.ai/096release/#ml-controls-sim) in architecture. Its inputs are the car velocity (`v_ego`), forward acceleration (`a_ego`), lateral acceleration due to road roll (`road_lataccel`), current car lateral acceleration (`current_lataccel`), and a steer input (`steer_action`), then it predicts the resultant lateral acceleration of the car.
 
 
 ## Controllers
@@ -56,7 +56,7 @@ Each rollout will result in 2 costs:
 It is important to minimize both costs. `total_cost`: $(lataccel\\_cost * 50) + jerk\\_cost$
 
 ## Submission
-Run the following command, and submit `report.html` and your code to [this form](https://forms.gle/US88Hg7UR6bBuW3BA).
+Run the following command, then submit `report.html` and your code to [this form](https://forms.gle/US88Hg7UR6bBuW3BA).
 
 ```
 python eval.py --model_path ./models/tinyphysics.onnx --data_path ./data --num_segs 5000 --test_controller <insert your controller name> --baseline_controller pid