## 5 Sub-Areas of Traffic Prediction Applications Using RNNs
### Traffic Accidents and Congestion Prediction
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Application** & **Reference** & **Techniques** & **Temporal** & **Spatial** \\ \hline \multirow{8}{*}{Traffic Flow Prediction} & [29; 32; 66] & LSTM & \(\surd\) & \(\times\) \\  & [30; 65; 83] & GRU & \(\surd\) & \(\times\) \\  & [31; 73; 74] & LSTM + CNN & \(\surd\) & \(\surd\) \\  & [36; 37; 38] & TCN & \(\surd\) & \(\times\) \\  & [51; 53; 54; 64] & RNN & \(\surd\) & \(\times\) \\  & [75; 76] & LSTM + CNN & \(\surd\) & \(\surd\) \\  & [77; 78; 82; 89] & LSTM + Attention & \(\surd\) & \(\surd\) \\  & [84] & RNN + GNN & \(\surd\) & \(\surd\) \\  & [85] & RNN + Attention & \(\surd\) & \(\surd\) \\  & [90] & GRU + CNN + Attention & \(\surd\) & \(\surd\) \\ \hline \multirow{4}{*}{Passenger Flow Prediction} & [91; 92; 93; 94] & LSTM & \(\surd\) & \(\times\) \\  & [95; 96] & LSTM + CNN & \(\surd\) & \(\surd\) \\  & [97] & RNN + GCN & \(\surd\) & \(\surd\) \\  & [98] & LSTM + GCN + Attention & \(\surd\) & \(\surd\) \\ \hline \multirow{4}{*}{OD Demand Prediction} & [56; 57; 58] & LSTM+CNN & \(\surd\) & \(\surd\) \\  & [99; 100] & LSTM & \(\surd\) & \(\times\) \\  & [101] & RNN, LSTM, GRU & \(\surd\) & \(\times\) \\  & [102] & GCN & \(\times\) & \(\surd\) \\  & [103] & GCN & \(\surd\) & \(\surd\) \\  & [104] & LSTM + Attention + Conv & \(\surd\) & \(\surd\) \\ \hline \multirow{4}{*}{Traffic Speed Prediction} & [28] & LSTM & \(\surd\) & \(\times\) \\  & [33; 34] & CNN & \(\surd\) & \(\times\) \\  & [52] & RNN & \(\surd\) & \(\times\) \\  & [59] & RNN + GNN & \(\surd\) & \(\surd\) \\  & [60] & LSTM + GNN & \(\surd\) & \(\surd\) \\  & [81] & GRU + GCN + Attention & \(\surd\) & \(\surd\) \\  & [105; 106] & RNN, LSTM & \(\surd\) & \(\times\) \\  & [107] & RNN + CNN & \(\surd\) & \(\surd\) \\  & [108] & GRU + CNN & \(\surd\) & \(\surd\) \\  & [109] & LSTM + CNN & \(\surd\) & \(\surd\) \\  & [110] & LSTM + CNN + Attention & \(\surd\) & \(\surd\) \\  & [111] & RNN + GNN + Attention & \(\surd\) & \(\surd\) \\ \hline \multirow{4}{*}{Traffic Accident Prediction} & [112; 113] & RNN, LSTM & \(\surd\) & \(\times\) \\  & [114; 119] & LSTM + Attention & \(\surd\) & \(\surd\) \\ \cline{1-1}  & [115] & LSTM + Conv & \(\surd\) & \(\surd\) \\ \cline{1-1}  & [117] & LSTM + GCN & \(\surd\) & \(\surd\) \\ \cline{1-1}  & [118] & LSTM + CNN & \(\surd\) & \(\surd\) \\ \hline \multirow{4}{*}{Traffic Congestion Prediction} & [121; 122] & RNN & \(\surd\) & \(\times\) \\ \cline{1-1}  & [123] & RNN, LSTM, GRU & \(\surd\) & \(\times\) \\ \cline{1-1}  & [124] & LSTM + Attention & \(\surd\) & \(\times\) \\ \cline{1-1}  & [125] & TCN + GCN & \(\surd\) & \(\surd\) \\ \hline \multirow{4}{*}{Traffic Congestion Prediction} & [127] & LSTM & \(\surd\) & \(\times\) \\ \cline{1-1}  & [128] & LSTM + CNN & \(\surd\) & \(\surd\) \\ \cline{1-1}  & [129] & Transformer + GCN & \(\surd\) & \(\surd\) \\ \hline \multirow{4}{*}{Occupancy Prediction} & [130; 131] & LSTM & \(\surd\) & \(\times\) \\ \cline{1-1}  & [132] & GRU & \(\surd\) & \(\times\) \\ \cline{1-1}  & [133] & LSTM + MLP & \(\surd\) & \(\times\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of traffic prediction methods in different fields of application. accidents and congestion prediction and provides a solid foundation for further research in this domain.