Journal of Advanced Transportation / 2019 / Article / Tab 1

Research Article

Identifying High-Risk Intersections for Walking and Bicycling Using Multiple Data Sources in the City of San Diego

Table 1

Negative binomial regression model for pedestrians.

VariableEstimatest-statSig.

(Intercept)4.86523.240.000
Transit stop density (0.5 miles)8.7823.810.000
Percentage of regular transit rider, pedestrian, or bicyclist population (0.25 miles)3.7171.950.051
Employment density (0.25 miles)0.0512.410.016
Maximum speed limit within the intersection less than 40 mph1.1355.370.000
Percentage of vacant housing units (0.5 miles)−3.517−2.990.003
Total commercial or mixed-use land area (0.1 mile)0.1905.010.000
If the area contains a higher crime count than the average crime counts among the buffers (0.25 miles)−0.292−1.650.098

N45
R-squared0.70
RMSE1633.24
MAE1147.41