Commuter-cyclist, Leisure-cyclist, Hazard, Duration, Covariate effect,

Pavement deterioration models provide useful predictions of distress initiation, for purposes of pavement design and management. A common problem in modeling the initiation is the inappropriate treatment of data censoring. If the censoring is not accounted for properly, the model may suffer from statistical biases.In this paper, an analysis of pavement crack initiation data based on the duration modeling techniques is presented. Duration models enable the stochastic nature of pavement crack initiation to be represented as well as censored data to be incorporated in the statistical estimation of the model parameters. The results show that the model predictions are more accurate than those obtained with the original AASHO model.

No abstract

No abstract

This study aims to study the impact of weather conditions and locational characteristics of bike stations on the usage of public bike sharing system for efficient deployment and operation of public bike systems. Linear regression analysis is used to estimate the usage of public bikes of Goyang city. The statistical analysis shows that the usage rate increases with average temperature and decreases under high wind (over 7m/s) or high temperature (over 29°) condition. The usage rate of public bike sharing system can be differentiated by locational characteristics of bike station such as residential area, commercial area, park, school, and metro station. The usage rate increases in park and commercial areas from 10 AM to 3 PM, while it increases in school areas from 3 PM to 5 PM. Public bikes are highly used near the metro station from 5 PM to 8 PM. The stations in parks are highly used in late night, and the usage rate in CBD area increases after the midnight.