Objective: This study aimed to explore the relationship between crash types and different freeway segments and identify the factors contributing to crashes on different freeway segments. Unlike most of the previous studies on freeway segments, this study separately investigates basic freeway segments, single ramp influence segments, and multiple ramp influence segments.
Methods: Nonlinear canonical correlation analysis (NLCCA) and proportionality test were used to identify the relationship between crash types and different freeway segments. The data sets for the different freeway segments accumulated for this study consist of 9,867 crash samples with complete information on all 22 chosen variables. A multinomial logit model (MNL) was used to estimate the influence of crash factors on different freeway segments.
Results: The results show that weaving and diverge overlap influence segments (WD) are more likely to have injury or fatal crashes; diverge and diverge overlap influence segments (DD) are more likely to have property damage–only (PDO) crashes; merge and merge overlap influence segments (MM) are more likely to have sideswipe crashes; and WD have non-sideswipe crashes; WD and weaving overlap influence segments (MW) are more likely to have rear end crashes; and MM segments are less likely to have hit object crashes. The contributing factors are identified by MNL and the results show that different traffic variables, environmental variables, vehicle variables, driver variables, and geometric variables significantly affected the likelihood of crashes on different freeway segments.
Conclusions: Investigation of crash types and factors contributing to crashes on different freeway segments is based on multiple ramp influence segments, which can promote a better understanding of the safety performance of various freeway segments. 相似文献
Coastal and ocean planning comprises a broad field of practice. The goals, political processes, and approaches applied to planning initiatives may vary widely. However, all planning processes ultimately require adequate information on both the biophysical and social attributes of a planning region. In coastal and ocean planning practice, there are well‐established methods to assess biophysical attributes; however, less is understood about the role and assessment of social data. We conducted the first global assessment of the incorporation of social data in coastal and ocean planning. We drew on a comprehensive review of planning initiatives and a survey of coastal and ocean practitioners. There was significantly more incorporation of social data in multiuse versus conservation‐oriented planning. Practitioners engaged a wide range of social data, including governance, economic, and cultural attributes of planning regions and human impacts data. Less attention was given to ecosystem services and social–ecological linkages, both of which could improve coastal and ocean planning practice. Although practitioners recognize the value of social data, little funding is devoted to its collection and incorporation in plans. Increased capacity and sophistication in acquiring critical social and ecological data for planning is necessary to develop plans for more resilient coastal and ocean ecosystems and communities. We suggest that improving social data monitoring, and in particular spatial social data, to complement biophysical data, is necessary for providing holistic information for decision‐support tools and other methods. Moving beyond people as impacts to people as beneficiaries, through ecosystem services assessments, holds much potential to better incorporate the tenets of ecosystem‐based management into coastal and ocean planning by providing targets for linked biodiversity conservation and human welfare outcomes. La Práctica Actual y los Prospectos Futuros para los Datos Sociales en la Planeación Costera y Oceánica 相似文献
Culturomic tools enable the exploration of trends in human–nature interactions, although they entail inherent biases and necessitate careful validation. Furthermore, people may engage with nature across different culturomic data sets differently. We evaluated people's digital interest and engagement with plant species based on Wikipedia and Google data and explored the conservation implications of these temporal interest patterns. As a case study, we explored the digital footprints of the most popular plant species in Israel. We analyzed 4 years of daily page views from Hebrew Wikipedia and 10 years of daily Google search volume in Israel. We modeled popularity of plant species in these 2 data sets based on a suite of plant attributes. We further explored the seasonal trends of people's interest in each species. We found differences in how people interacted digitally with plants in Wikipedia and Google. Overall, in Google, searches for species that have utility to humans were more common, whereas in Wikipedia, plants that serve as cultural emblems received more attention. Furthermore, in Google, popular species attracted more attention over time, opposite to the trend in Wikipedia. In Google, interest in species with short bloom duration exhibited more pronounced seasonal patterns, whereas in Wikipedia, seasonality of interest increased as bloom duration increased. Together, our results suggest that people's digital interactions with nature may be inherently different depending on the sources explored, which may affect use of this information for conservation. Although culturomics holds much promise, better understanding of its underpinnings is important when translating insights into conservation actions. 相似文献
Eco-labelling is the practice of eco information provision that most directly addresses consumer behaviour. Nowadays, consumers are facing difficulties in perceiving and understanding existing eco labels. In previous work, we proposed the conceptual framework of eco information individualisation which tailors eco labels according to the specific needs of individual users using contextual technologies. This paper extends the conceptual framework by introducing a more structured way of considering the personal data and product data requirements, and reports the development of a design toolkit that aims to support designers in the designing of individualised eco information. A design workshop was carried out to introduce the concept to designers, and evaluate the usability and usefulness of the toolkit. Positive responses were received. The design outputs generated from the workshop were considered largely feasible and have the potential to be developed into digital prototypes. These indicate that it is possible for designers to learn to design eco information individualisation in a short time. This paper is a step towards a greater understanding of designing individualised eco information. 相似文献
水环境污染是长江流域突出的环境问题之一,预测污染物排放特征可为流域水污染防治提供科学基础.本研究综合采用灰色理论预测模型、Conversion of land use and its effects at small region extent(CLUE-S)模型以及 Integrated valuation of ecosystem services and tradeoffs(InVEST)模型,预测2025年长江流域非点源以及点源总氮排放趋势.结果表明:①非点源总氮排放呈减少趋势,2015~2025年区域非点源总氮排放量减少23.96%,中下游农业区总氮排放骤减,而上游局部地区呈增加趋势;②点源总氮排放总体呈现增加趋势,2015~2025年区域点源总氮排放量增加1.79%,主要是由于城镇废水排放的增加以及中下游沿江城市群生活污水排放显著增加,而中下游丘陵地区点源总氮排放呈现减少趋势;③长江流域总氮排放量呈现减少趋势,2015~2025年减少2.67%,但仍有37.64%区域呈现总氮排放增加的趋势.长江流域未来应加强对上游面源污染治理以及中下游工业、城镇废水排放的管控.采用多模型结合的手段可以精细揭示了长江流域总氮排放空间格局及未来趋势,可为明确流域总氮排放控制目标提供科学基础,也可为实现高效的水环境治理提供科学依据. 相似文献