Objective: Considering the high annual number of fatal driving accidents in Iran, any approach for reducing the number or severity of driving accidents is a positive step toward decreasing accident-related losses. Accidents can often be avoided by a timely reaction of the driver. One of the steps before reacting to a hazard is perception. Some driver characteristics may affect road hazard perception. In this research, it was assumed that various driver characteristics, including demographic characteristics and cognitive characteristics, have an impact on driver perception.
Methods: The driving simulator used in this research provides various scenarios; for example, passing a pedestrian or animal across the road or placing fixed objects in a 2-lane separated rural road for 2 groups of experienced and inexperienced drivers under day and night lighting conditions. The go/no-go test was carried out in order to assess drivers’ attention to driving tasks and inhibitory control. A structural equation model (SEM) was used to estimate the relation between driver characteristics and sensitivity to road hazard perception. A new hazard perception index was proposed based on the time intervals in the hazard vulnerability.
Results: The results show that the most effective variables in the analysis of sensitivity to hazard perception are driving experience (in kilometers) during the last 3 years and road lighting conditions. Moreover, hazard perception sensitivity was improved by better inhibitory control, selective attention, and decision making, more carefulness, the average amount of daily sleep, and marital status.
Conclusion: The results of this research may be useful in educating and advertising programs. It also could enhance sensitivity to perception of hazards such as pedestrians, animals, and fixed obstacles among young and novice drivers. 相似文献
Species, habitats, and ecosystems are increasingly exposed to multiple anthropogenic stressors, fueling a rapidly expanding research program to understand the cumulative impacts of these environmental modifications. Since the 1970s, a growing set of methods has been developed through two parallel, sometimes connected, streams of research within the applied and academic realms to assess cumulative effects. Past reviews of cumulative effects assessment (CEA) methods focused on approaches used by practitioners. Academic research has developed several distinct and novel approaches to conducting CEA. Understanding the suite of methods that exist will help practitioners and academics better address various ecological foci (physiological responses, population impacts, ecosystem impacts) and ecological complexities (synergistic effects, impacts across space and time). We reviewed 6 categories of methods (experimental, meta-analysis, single-species modeling, mapping, qualitative modeling, and multispecies modeling) and examined the ability of those methods to address different levels of complexity. We focused on research gaps and emerging priorities. We found that no single method assessed impacts across the 4 ecological foci and 6 ecological complexities considered. We propose that methods can be used in combination to improve understanding such that multimodel inference can provide a suite of comparable outputs, mapping methods can help prioritize localized models or experimental gaps, and future experiments can be paired from the outset with models they will inform. 相似文献
Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R2 ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use. 相似文献
• In situ preparation of FeNi nanoparticles on the sand via green synthesis approach.• Removal of tetracycline using GS-FeNi in batch and column study.• Both reductive degradation and sorption played crucial role the process.• Reusability of GS-FeNi showed about 77.39±4.3% removal on 4th cycle.• TC by-products after interaction showed less toxic as compared with TC. In this study, FeNi nanoparticles were green synthesized using Punica granatum (pomegranate) peel extract, and these nanoparticles were also formed in situ over quartz sand (GS-FeNi) for removal of tetracycline (TC). Under the optimized operating conditions, (GS-FeNi concentration: 1.5% w/v; concentration of TC: 20 mg/L; interaction period: 180 min), 99±0.2% TC removal was achieved in the batch reactor. The removal capacity was 181±1 mg/g. A detailed characterization of the sorbent and the solution before and after the interaction revealed that the removal mechanism(s) involved both the sorption and degradation of TC. The reusability of reactant was assessed for four cycles of operation, and 77±4% of TC removal was obtained in the cycle. To judge the environmental sustainability of the process, residual toxicity assay of the interacted TC solution was performed with indicator bacteria (Bacillus and Pseudomonas) and algae (Chlorella sp.), which confirmed a substantial decrease in the toxicity. The continuous column studies were undertaken in the packed bed reactors using GS-FeNi. Employing the optimized conditions, quite high removal efficiency (978±5 mg/g) was obtained in the columns. The application of GS-FeNi for antibiotic removal was further evaluated in lake water, tap water, and ground water spiked with TC, and the removal capacity achieved was found to be 781±5, 712±5, and 687±3 mg/g, respectively. This work can pave the way for treatment of antibiotics and other pollutants in the reactors using novel green composites prepared from fruit wastes. 相似文献