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This study aims to evaluate the effect of ultra-low emission zone (ULEZ) on the demand of public bike sharing in London (also known as London Cycle Hire Scheme (LCH)). Bike usage data from 699 bicycle docking stations between May 2019 and October 2019 are used. Treatment and control groups for effectiveness evaluation of ULEZ are established using the propensity score matching approach, with which the confounding effects by factors including population density, socio-demographics, land use, and transport facilities are considered. Results indicate that bicycle demand increases significantly (27.9%) after the introduction of ULEZ. In addition, increases in bicycle demand are more profound for short (with 15 minutes, 25.3%) and intermediate (15 to 30 minutes, 28.8%) trips. Furthermore, increase in bicycle trip with origin (borrowing) and destination (return) both within ULEZ is considerable (44.8%). However, there is no significant change for overall bicycle trip duration after the introduction of ULEZ. [ABSTRACT FROM AUTHOR]

To study the time-of-day variations and temporal stabilities of factors influencing single-vehicle crashes on rural highways, random parameters logit models with heterogeneity in means and variances under different time periods of the day and from year to year were estimated to identify significant factors. The potential crash-influencing factors in drivers, vehicles, roads, and the environment were analyzed to dissect the correlation and variability between the influencing factors and crash injury severity. Likelihood ratio tests were conducted to assess the transferability of model estimation results from different times of the day and from year to year. The results showed that the effect of factors that determine injury severity varied significantly across time-of-day/time-period combinations. Overall temporal instability was observed in the study. However, several explanatory variables showed temporally stable effects in terms of their impact on resulting injury severities. Such as male, driver age (<30), truck, non-dry road surface, and visibility (100–200 m). [ABSTRACT FROM AUTHOR]

The severity of crashes on national/provincial roads, urban roads, and rural roads was analyzed. Random parameters logit models with heterogeneity in means and variances under different time periods of the day and roadway classifications were employed. Analysis of factors influencing injury severity of single-vehicle crashes in the driver, vehicle, road, and environment to explore correlation and difference between influencing factors and crash severity. The results showed that the effect of factors that determine injury severity varied significantly across different roadway classifications. Specifically, driver age (<30) and summer were only significantly associated with single-vehicle crashes on urban roads. Dawn/dusk was only significant in single-vehicle crashes on rural roads. Meanwhile, overall spatiotemporal instability was observed in the study. While several indicators were also reported to show relative spatial or temporal stability such as male, driver age (>55), motorcycle, traffic control, and visibility (<100 m). [ABSTRACT FROM AUTHOR]