Research Article
Predicting Free Flow Speed and Crash Risk of Bicycle Traffic Flow Using Artificial Neural Network Models
Table 1
Descriptive statistics of model parameters.
| Parameters types | Designation | Max | Min | Mean | SD |
| Cycleway features | Cycleway width (m) | CW | 4.60 | 2.27 | 3.46 | 0.74 |
| Traffic flow parameters | Bicycle flow (bicycles/h/m) | FB | 1364 | 72 | 590 | 302 |
| Bicycle types | % of BSEB | PBS | 42.31% | 3.75% | 16.78% | 5.79% | % of SSEB | PSS | 79.59% | 29.61% | 53.11% | 10.56% |
| Characteristics of cyclists | % of male cyclists | PMC | 92.75% | 43.54% | 65.64% | 8.48% | % of young cyclists | PYC | 92.02% | 22.50% | 64.14% | 14.13% | % of middle-aged cyclists | PMAC | 62.38% | 4.80% | 28.10% | 11.82% | % of loaded cyclists | PLC | 30.00% | 1.32% | 11.19% | 5.67% |
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