TY  - JOUR
PY  - 2022//
TI  - Mixed logit model based diagnostic analysis of bicycle-vehicle crashes at daytime and nighttime
JO  - International journal of transportation science and technology
A1  - Liu, Shaojie
A1  - Li, Yang
A1  - Fan, Wei (David)
SP  - 738
EP  - 751
VL  - 11
IS  - 4
N2  - Cycling provides an important alternative to environmental-friendly transportation modes in urban areas. However, cyclists are vulnerable road users and often suffer severe injuries once crashes occur, which has impeded the growth of bicycle uses. Identification of factors that influence injury severities of crashes involving cyclists can help policy-makers form efficient strategies to mitigate crashes. Moreover, crashes involving cyclists at daytime and nighttime are very likely to present different patterns. Hence, the objective of this study is to explore the underlying factors to injury severity in crashes involving cyclists in the daytime and nighttime separately. Mixed logit model approach is employed due to its advantage of accounting for heterogeneity in observations and four factors are found to have random effects in the mixed logit model for daytime. The differences of crash mechanisms at daytime and nighttime are discussed, and the results of this research would help to develop effective policies that aim to mitigate the injury severities of cyclists while promoting the use of bicycles.<p />  <p>Language: en</p>
LA  - en
SN  - 2046-0430
UR  - http://dx.doi.org/10.1016/j.ijtst.2021.10.001
ID  - ref1
ER  -