Accident; analysis and prevention
-
Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. ⋯ The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data.
-
In an effort to improve traffic safety, there has been considerable interest in estimating crash prediction models and identifying factors contributing to crashes. To account for crash frequency variations among crash types and severities, crash prediction models have been estimated by type and severity. The univariate crash count models have been used by researchers to estimate crashes by crash type or severity, in which the crash counts by type or severity are assumed to be independent of one another and modelled separately. ⋯ The standard errors of covariates in the MVPLN model are slightly lower than the UPLN model when the covariates are statistically significant, and the crash counts by crash type and severity are significantly correlated. The model prediction comparisons illustrate that the MVPLN model outperforms the UPLN model in prediction accuracy. Therefore, when predicting crash counts by crash type and crash severity for rural two-lane highways, the MVPLN model should be considered to avoid estimation error and to account for the potential correlations among crash type counts and crash severity counts.
-
Fatigue is a significant contributor to motor-vehicle accidents and fatalities. Shift workers are particularly susceptible to fatigue-related risks as they are often sleep-restricted and required to commute around the clock. Simple assays of performance could provide useful indications of risk in fatigue management, but their effectiveness may be influenced by changes in their sensitivity to sleep loss across the day. ⋯ Tasks did not significantly predict driving performance during the control condition or around the acrophase during the SR condition. The PVT and self-assessed ability were the best predictors of simulated driving across circadian phases during SR. These results show that simple performance measures and self-monitoring explain a large proportion of the variance in driving when fatigue-risk is high.
-
This study compared the impact of split and consolidated sleep/wake schedules on subjective sleepiness during the biological day and biological night. This was achieved using a between-group design involving two forced desynchrony protocols: consolidated sleep/wake and split sleep/wake. Both protocols included 7×28-h days with 9.33h in bed and 18.67h of wake each day. ⋯ These findings were observed for wake periods that occurred during both the biological day and biological night. Previous data have shown that cognitive impairment at night is lower for split schedules than consolidated schedules, but the current data indicate that feelings of sleepiness are greater for split schedules than consolidated schedules for at least half of the time awake. Thus, it should be explained to people operating split sleep/wake schedules that although they may perform well, they are likely to feel sleepy.
-
To operate Navy ships 24h per day, watchstanding is needed around the clock, with watch periods reflecting a variety of rotating or fixed shift schedules. The 5/15 watch schedule cycles through watch periods with 5h on, 15h off watch, such that watches occur 4h earlier on the clock each day - that is, the watches rotate backward. The timing of sleep varies over 4-day cycles, and sleep is split on some days to accommodate nighttime watchstanding. ⋯ These laboratory-based findings suggest that Navy watch schedules are associated with cumulative sleep loss and a build-up of fatigue across days. The fixed watch periods of the 3/9 watch schedule appear to yield more stable performance than the backward rotating watch periods of the 5/15 watch schedule. Optimal performance may require longer and more consistent daily opportunities for sleep than are typically obtained in Navy operations.