Research Article
An Improved Deep Learning Model for Traffic Crash Prediction
Table 1
Summary statistics of analyzed continuous variables.
| Variable | Mean | Std. Dev. | Min. | Max. |
| Independent variable | | | | | The number of major injury crashes per year per roadway segment | 0.04 | 0.32 | 0 | 3 | The number of minor injury crashes per year per roadway segment | 0.41 | 0.54 | 0 | 9 | The number of no injury crashes per year per roadway segment | 1.23 | 1.74 | 0 | 22 | Traffic factors | | | | | The logarithm of AADT per lane | 3.53 | 3.74 | 2.93 | 4.51 | Truck traffic percentage | 6.71 | 4.98 | 1 | 33 | Posted speed limits | 38.65 | 6.69 | 30 | 70 | Geometric design features | | | | | Segment length (miles) | 0.81 | 1.03 | 0.02 | 12.31 | Degree of horizontal curvature | 1.51 | 3.23 | 0 | 14.00 | Median widths | 1.12 | 2.02 | 0 | 12 | Outside shoulder widths | 3.06 | 1.88 | 3.52 | 8 | Pavement factors | | | | | International roughness index | 65.85 | 27.75 | 25.45 | 182.58 | Rut depth (in.) | 0.13 | 0.05 | 0.06 | 0.41 |
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