Research Article
Prediction for Traffic Accident Severity: Comparing the Bayesian Network and Regression Models
Table 1
Variables and statistics based on survey data.
| Factors | Variables | Values | Percentage (%) |
| Accident severity | Number of fatalities: Nof | 0 : 1 | 89.59 | ≥1 : 2 | 10.41 | Number of injuries: Noi | 0 : 1 | 9.86 | 1, 3) : 2 | 85.89 | 3, 11) : 3 | 4.14 | ≥11 : 4 | 0.11 | Property damage (Yuan): Pd | <1000 : 1 | 61.18 | 1000, 30000) : 2 | 37.19 | ≥30000 : 3 | 1.63 |
| Accident characteristics | Time of day: Tod | day 6:00, 18:00) : 1 | 69.12 | night 18:00, 6:00) : 2 | 30.88 | Location-Motor vehicle lanes: L-Mvl | Yes: 1 | 71.68 | No: 2 | 28.32 | Location-Crosswalk: L-C | Yes: 1 | 3.42 | No: 2 | 96.58 | Location-Regular road section: L-Rrs | Yes: 1 | 60.01 | No: 2 | 39.99 | Location-Intersection: L-I | Yes: 1 | 38.90 | No: 2 | 61.10 |
| Vehicle characteristics | Motorcycle involved: Mi | Yes: 1 | 16.97 | No: 2 | 83.03 | Bus or truck involved: Bti | Yes: 1 | 95.30 | No: 2 | 4.70 | Vehicle condition: Vc | Good: 1 | 73.79 | Poor: 2 | 26.21 |
| Environmental factors | Weather condition: Wc | Sunny: 1 | 89.48 | Other: 2 | 10.52 | Visibility distance (meter): Vd | <50 : 1 | 8.90 | 50, 100) : 2 | 22.70 | 100, 200) : 3 | 19.86 | ≥200 : 4 | 48.54 |
| Roadway characteristics | Pavement condition: Pc | Asphalt or cement: 1 | 99.80 | Other: 2 | 0.20 | Roadway surface condition: Rsc | Dry: 1 | 85.16 | Other: 2 | 14.84 | Road geometrics: Rg | Flat and straight: 1 | 98.57 | Hill or bend: 2 | 1.43 | Traffic signal control: Tsc | Yes: 1 | 17.46 | No: 2 | 82.54 |
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