Research Article
Identifying Recurring Bottlenecks on Urban Expressway Using a Fusion Method Based on Loop Detector Data
Table 1
Bottleneck identification results.
| Station ID no. | Occurrence time | O-UP (km) | O-DOWN (km) | Length of bottleneck (km) | Duration time (min) | Delay (hour) |
| 1208944 () | 07:55 | 4.88 | 2.39 | 2.49 | 15 | 2.05 | 08:20 | 4.74 | 2.84 | 1.9 | 5 | 5.29 | 08:50 | 4.87 | 2.76 | 2.11 | 5 | 1.91 | 09:30 | 4.67 | 3.72 | 0.95 | 5 | 0.98 | 09:40 | 4.86 | 3.72 | 1.14 | 15 | 0.75 | 10:55 | 4.75 | 2.88 | 1.87 | 5 | 0.59 | 13:15 | 4.83 | 3.72 | 1.11 | 5 | 1.05 | 13:50 | 4.73 | 2.04 | 2.69 | 5 | 0.91 |
| 1210679 () | 06:45 | 19.73 | 17.86 | 1.87 | 20 | 0.87 | 07:20 | 19.37 | 16.18 | 3.19 | 15 | 2.52 | 11:10 | 19.32 | 16.74 | 2.58 | 10 | 0.68 | 12:00 | 19.28 | 16.74 | 2.54 | 20 | 1.17 | 12:40 | 19.26 | 17.86 | 1.40 | 15 | 0.52 | 15:10 | 19.30 | 17.27 | 2.03 | 15 | 1.26 | 15:50 | 19.37 | 16.74 | 2.63 | 10 | 0.73 | 16:50 | 19.36 | 17.02 | 2.34 | 10 | 1.75 | 17:20 | 19.31 | 17.86 | 1.45 | 10 | 0.97 | 18:00 | 19.22 | 16.18 | 3.03 | 15 | 1.13 | 19:05 | 19.26 | 17.86 | 1.40 | 5 | 0.38 | 19:15 | 19.35 | 17.38 | 1.97 | 5 | 0.57 |
| 1210474 () | 08:25 | 23.06 | 21.64 | 1.42 | 5 | 7.27 |
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