Random Forest regression validation and improvement of the model

I am working with vehicle occupancy prediction and I am very much new to this, I have used random forest regression to predict the occupancy values.

Jupyter notebook_Random forest

I have around 48 M rows and I have used all the data to predict the occupancy, As the population and occupancy were normalized due to the higher numbers and I have predicted. I am sure the model is not good, how can I interpret the results from the RMSE and MAE. Also, the plot shows that it is not predicted well, Am I doing it in a correct way to predict the occupancy of the vehicles.

Kindly help me with the following,

1. Is Random forest regression is a good method to approach this problem?
2. How can I improve the model results?
3. How to interpret the results from the outcome.

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