Research Article
Analysis and Prediction of Overloaded Extra-Heavy Vehicles for Highway Safety Using Machine Learning
Table 7
Summary of the laws of clustering results of the national and provincial highways when k = 4.
| Year | Quarter | Most overloaded vehicles | Vehicles with high overload rate | Entry time | Gross weight of vehicle and goods | Axle number | Entry time | Gross weight of vehicle and goods | Axle number |
| 2018 | 1 | 0:00–8:00 | Over 49 t | 6 | 2:00–3:00 | Over 49 t | 6 | 2 | 0:00–8:00 | Over 49 t | 6 | 21:00–23:00 | Over 49 t | 6 | 3 | 0:00–8:00 | Over 49 t | 6 | 21:00–23:00 | Over 49 t | 6 | 4 | 0:00–8:00 | Over 49 t | 6 | 23:00 | Over 49 t | 6 | 2019 | 1 | 4:00–13:00 | Over 49 t | 6 | 0:00–3:00 | Over 49 t | 6 | 2 | 0:00–15:00 | Over 49 t | 6 | 0:00–3:00 | Over 49 t | 6 | 3 | 4:00–5:00 | Over 49 t | 6 | 2:00–3:00 | Over 49 t | 6 | 4 | 8:00–15:00 | Over 49 t | 6 | 0:00–4:00 | Over 49 t | 6 |
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