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Urban-rural integration is the critical process of urbanization, while during this process there are various corresponding problems generated, safety is the most important one, especially at urban-rural fringe areas due to mixed traffic flow and complicated land use. This study intended to investigate the injury severity interaction between urban area and urban-rural fringe area, and explore the correlation within injury severity levels and heterogeneity attributed to unobserved factors. To address the correlation and heterogeneity issues, a grouped random parameters seemingly unrelated bivariate (SUB) probit model was proposed, in which the SUB probit model addressed the correlation of residuals, while the random parameters model accommodated the heterogeneity due to unobserved factors. By comparing the pooled with random parameters models, the results showed that random parameters SUB probit model performed better than the pooled one, and the dataset collected from 2013 to 2017 in Chengdu, China was adopted to illustrate the proposed model. It is found that crash location, speed limit and age of person injured are significant for injury severity in urban and urban-rural fringe areas, but crash form plays a significant role in urban area while number of persons involved should be paid more attention due to injury severity in urban-rural fringe area. Some empirical suggestions are presented to improve the safety in urban and urban-rural fringe areas. [ABSTRACT FROM AUTHOR]

Dockless bike-sharing (DBS) has proliferated worldwide. Despite DBS's great potential to reduce air pollution, air pollution may also reduce the usage of DBS. However, not much research attention has been paid to the effects of air pollution on DBS usage. Existing attempts have mostly relied on traditional data sources and intended to establish associations, not causalities. To address this research gap, we compile a panel data set with more than 50 million DBS trip records and high-frequency air quality and weather monitoring readings over a 92-day period in Chengdu, China. We then estimate the causal effects of air pollution on DBS usage using an instrumental variable approach. We find that a 10 μg/m3 increase in PM 2.5 concentrations leads to a 2.5% reduction in DBS usage. Furthermore, such adverse effects are particularly pronounced among young DBS users, during non-peak hours, for long-distance trips, and in census tracts with low housing prices. [ABSTRACT FROM AUTHOR]