Traffic Flow Optimization on Melbourne Parking Probability 0.3 Real-world data
115.07Avg Time Loss (s)D-PA (Ours)
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| D-PA (Ours)Parking Probability=0.32025.12 | 115.07 | 39.7 | 2.71 | |
| D-PA (DQN)Parking Probability=0.3, Backbone=DQN2025.12 | 138.41 | 27.47 | 2 | |
| D-PA (A2C)Parking Probability=0.3, Backbone=A2C2025.12 | 144.22 | 24.43 | 2.13 | |
| D-PA (PPO)Parking Probability=0.3, Backbone=PPO2025.12 | 150.25 | 21.27 | 1.86 | |
| D-PA (Du-DQN)Parking Probability=0.3, Backbone=Dueling DQN2025.12 | 153.66 | 19.48 | 1.85 | |
| D-PA (D-DQN)Parking Probability=0.3, Backbone=Double DQN2025.12 | 155.19 | 18.68 | 1.83 | |
| C-PAParking Probability=0.32025.12 | 167.4 | 12.28 | 68.09 | |
| S-PAParking Probability=0.32025.12 | 169.59 | 11.14 | 1.71 | |
| No-PAParking Probability=0.32025.12 | 190.84 | — | 1.49 |