TY  - JOUR
PY  - 2022//
TI  - A random-parameter negative binomial model for assessing freeway crash frequency by injury severity: daytime versus nighttime
JO  - Sustainability (Basel)
A1  - Zhang, Ping
A1  - Wang, Chenzhu
A1  - Chen, Fei
A1  - Cui, Suping
A1  - Cheng, Jianchuan
A1  - Bo, Wu
SP  - e9061
EP  - e9061
VL  - 14
IS  - 15
N2  - This study explored the effects of contributing factors on crash frequency, by injury severity of all, daytime, and nighttime crashes that occurred on freeways. With three injury severity outcomes classified as light injury, minor injury, and severe injury, the effects of the explanatory variables affecting the crash frequency were examined in terms of the crash, traffic, speed, geometric, and sight characteristics. Regarding the model estimations, the lowest AIC and BIC values (2263.87 and 2379.22, respectively) showed the superiority of the random-parameter multivariate negative binomial (RPMNB) model in terms of the goodness-of-fit measure. Additionally, the RPMNB model indicated the highest R2 (0.25) and predictive accuracy, along with a significantly positive α parameter. Moreover, transferability tests were conducted to confirm the rationality of separating the daytime and nighttime crashes. Based on the RPMNB models, several explanatory variables were observed to exhibit relatively stable effects whereas other variables presented obvious variations. This study can be of certain value in guiding highway design and policies and developing effective safety countermeasures.<p />  <p>Language: en</p>
LA  - en
SN  - 2071-1050
UR  - http://dx.doi.org/10.3390/su14159061
ID  - ref1
ER  -