Research Article

Analysis of Factors Affecting the Severity of Injuries in Electric Two-Wheeled Vehicle Crashes with or without Violation: A Random Parametric Logit Model considering Heterogeneity of Means and Variances

Table 5

Estimating the severity of injuries in electric two wheeled vehicle accidents using a random parameter logit model considering the heterogeneity of mean and variance.

VariableNo violationExistence of violation
MISFMISF
MeanS.DMeanS.DMeanS.DMeanS.D

Rider factor
Male−1.1880.240−0.9580.873
18–32−0.2360.154
46–600.7960.655
>600.1510.1780.3470.2120.7860.9752.0171.316

Road factor
Pavement damage−2.2410.2310.1480.247
Dusk/dawn−0.4930.347
Street lights at night−1.1450.1750.2580.455
No street lamp at night0.7670.1590.8380.2330.4260.725
Nonmotorized lane−0.2880.105−0.5540.143
Mixed lane1.3230.1351.1710.1970.7230.5350.5710.397
Sidewalk−0.5520.155

Collision factor
Other angles−1.1560.237−1.6680.537−1.3250.736

Environmental factor
Uncontrolled−0.2360.135−0.4560.1420.3200.294
Marking control0.5320.322
Autumn0.3670.155
Severe weather1.1490.2110.8041.103
<200 m0.4850.1810.2490.645

Random parameter
Severe weather0.8040.2121.1491.853
<200 m0.2600.7380.4861.163

Heterogeneity in the means of random parameters
Severe weather: No street lamp at nigh0.3010.217
Severe weather: >600.4330.212
Severe weather: Uncontrolled−0.5321.123
<200 m: Mixed lane−0.3220.6710.5250.278

Heterogeneity in the variances of random parameters
Severe weather: >601.5880.205
Severe weather: No street lamp at nigh1.2370.512
<200 m: Mixed lane1.3071.062