Using nlp to analyze accident report
Firstly, I hope that the label is either a short summary or words of varying length, not just one word direction. Because moving cars involved in an accident may have multiple directions, or one car could be just parked like the example.
Secondly, given that you are planning to predict varying length label, and given the example text, I am pretty sure that bag of words will not work well. You need the context. And you dont have million sized training set to train a transformer deep neural net. So try to utilize  pre-trained embeddings like USE, GloVe etc. If you are using the embedding, it provides you awesome feature engineering done. Just train some low complexity model like random forest/ xgboost on (label, embeddings). You can also explore pretrained summary generators like bertseq2seq, however the code for this didn't work for me yet.