Traffic Flow Optimization on Melbourne Parking Probability 0.4 Real-world data
121.22Avg Time Loss (s)D-PA (Ours)
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| D-PA (Ours)Parking Probability=0.42025.12 | 121.22 | 47.79 | 3.52 | |
| D-PA (DQN)Parking Probability=0.4, Backbone=DQN2025.12 | 155.71 | 32.93 | 2.72 | |
| D-PA (A2C)Parking Probability=0.4, Backbone=A2C2025.12 | 167.22 | 27.98 | 2.86 | |
| D-PA (PPO)Parking Probability=0.4, Backbone=PPO2025.12 | 169.9 | 26.82 | 2.56 | |
| D-PA (Du-DQN)Parking Probability=0.4, Backbone=Dueling DQN2025.12 | 170.06 | 26.75 | 2.58 | |
| D-PA (D-DQN)Parking Probability=0.4, Backbone=Double DQN2025.12 | 176.65 | 23.91 | 2.54 | |
| C-PAParking Probability=0.42025.12 | 198.55 | 14.48 | 70.7 | |
| S-PAParking Probability=0.42025.12 | 200.21 | 13.77 | 2.47 | |
| No-PAParking Probability=0.42025.12 | 232.17 | — | 2.12 |