Research Article
Application of CNN-LSTM Model for Vehicle Acceleration Prediction Using Car-following Behavior Data
Table 3
The prediction results for four different groups.
| Group | Drivers | Model | Index | Experiments | Average | 1 | 2 | 3 | 4 | 5 |
| 1 | 8 drivers | LSTM | MSE | 0.0081 | 0.0081 | 0.0082 | 0.0080 | 0.0081 | 0.0081 | MAE | 0.0591 | 0.0592 | 0.0615 | 0.0595 | 0.0606 | 0.0600 | CNN-LSTM | MSE | 0.0076 | 0.0078 | 0.0076 | 0.0076 | 0.0076 | 0.0076 | MAE | 0.0572 | 0.0579 | 0.0574 | 0.0577 | 0.0575 | 0.0575 |
| 2 | 22 drivers | LSTM | MSE | 0.0193 | 0.0218 | 0.0175 | 0.0174 | 0.0170 | 0.0186 | MAE | 0.0891 | 0.1135 | 0.0947 | 0.0907 | 0.0891 | 0.0954 | CNN-LSTM | MSE | 0.0146 | 0.0146 | 0.0148 | 0.0145 | 0.0145 | 0.0146 | MAE | 0.0827 | 0.0822 | 0.0830 | 0.0819 | 0.0828 | 0.0825 |
| 3 | 30 drivers | LSTM | MSE | 0.0173 | 0.0180 | 0.0163 | 0.0173 | 0.0162 | 0.0170 | MAE | 0.0891 | 0.0952 | 0.0869 | 0.0924 | 0.0856 | 0.0898 | CNN-LSTM | MSE | 0.0125 | 0.0127 | 0.0124 | 0.0126 | 0.0128 | 0.0126 | MAE | 0.0746 | 0.0764 | 0.0741 | 0.0754 | 0.0757 | 0.0752 |
| 4 | 8 drivers (in random) | LSTM | MSE | 0.0219 | 0.0199 | 0.0247 | 0.0203 | 0.0202 | 0.0214 | MAE | 0.1097 | 0.1027 | 0.1191 | 0.1041 | 0.1041 | 0.1079 | CNN-LSTM | MSE | 0.0188 | 0.0188 | 0.0194 | 0.0189 | 0.0193 | 0.0190 | MAE | 0.1007 | 0.1001 | 01010 | 0.1005 | 0.1008 | 0.1006 |
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The bold results represent the outcomes of the model with the smallest prediction errors among the four driver groups.
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