Research Article
Traffic Status Prediction of Arterial Roads Based on the Deep Recurrent Q-Learning
Table 4
Experimental result table.
| Group | Highest loss index | Lowest loss index | Maximum volatility | Training time (s) | Prediction time (s) | Total time (s) |
| 1 | 0.240 | 0.082 | 0.0400 | 1080 | 100 | 1180 | 2 | 0.230 | 0.066 | 0.0385 | 1088 | 102 | 1190 | 3 | 0.195 | 0.070 | 0.0375 | 950 | 92 | 1042 | 4 | 0.970 | 0.096 | 0.4350 | 1086 | 101 | 1187 | 5 | 0.154 | 0.070 | 0.0435 | 1096 | 102 | 1198 | 6 | 0.250 | 0.080 | 0.0600 | 1139 | 105 | 1244 | 7 | 0.186 | 0.062 | 0.0510 | 1000 | 93 | 1093 | 8 | 0.195 | 0.080 | 0.0400 | 1033 | 96 | 1129 | 9 | 0.157 | 0.065 | 0.0440 | 1046 | 99 | 1145 | 10 | 0.238 | 0.070 | 0.0400 | 1013 | 94 | 1107 | 11 | 0.235 | 0.081 | 0.0440 | 1024 | 96 | 1120 |
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