A growing number of international studies have highlighted that ambient air pollution exposures are related to different health outcomes. To do so, researchers need to estimate exposure levels to air pollution through...A growing number of international studies have highlighted that ambient air pollution exposures are related to different health outcomes. To do so, researchers need to estimate exposure levels to air pollution throughout everyday life. In the literature, the most commonly used estimate is based on home address only or taking into account, in addition, the work address. However, several studies have shown the importance of daily mobility in the estimate of exposure to air pollutants. In this context, we developed an R procedure that estimates individual exposures combining home addresses, several important places, and itineraries of the principal mobility during a week. It supplies researchers a useful tool to calculate individual daily exposition to air pollutants weighting by the time spent at each of the most frequented locations (work, shopping, residential address, etc.) and while commuting. This task requires the efficient calculation of travel time matrices or the examination of multimodal transport routes. This procedure is freely available from the Equit’Area project website: (https://www.equitarea.org). This procedure is structured in three parts: the first part is to create a network, the second allows to estimate main itineraries of the daily mobility and the last one tries to reconstitute the level of air pollution exposure. One main advantage of the tool is that the procedure can be used with different spatial scales and for any air pollutant.展开更多
With the development of motorization, road traffic crashes have become the leading cause of death in many countries. Among roadway traffic crashes, almost 90% of accidents are related to driver behaviors, wherein driv...With the development of motorization, road traffic crashes have become the leading cause of death in many countries. Among roadway traffic crashes, almost 90% of accidents are related to driver behaviors, wherein driving anger is one of the most leading causes to vehicle crash-related conditions. To some extent, angry driving is considered more dangerous than typical driving distraction due to emotion agitation. Aggressive driving behaviors create many kinds of roadway traffic safety hazards. Mitigating potential risk caused by road rage is essential to increase the overall level of traffic safety. This paper puts forward an integrated computer vision model composed of convolutional neural network in feature extraction and Bayesian Gaussian process in classification to recognize driver anger and distinguish angry driving from natural driving status. Histogram of gradients (HOG) was applied to extract facial features. Convolutional neural network extracted features on eye, eyebrow, and mouth, which are considered most related to anger emotion. Extracted features with its probability were sent to Bayesian Gaussian process classier as input. Integral analysis on three extracted features was conducted by Gaussian process classifier and output returned the likelihood of being anger from the overall study of all extracted features. An overall accuracy rate of 86.2% was achieved in this study. Tongji University 8-Degree-of-Freedom driving simulator was used to collect data from 30 recruited drivers and build test scenario.展开更多
在高质量发展国土空间布局背景下,科学评价和分析道路的生态影响对协调生态环境和经济社会可持续发展具有重大意义。选取成渝城市群为研究对象,基于2020年土地利用和交通数据,结合MSPA法、景观连通性指数和MCR模型构建生态网络,通过道...在高质量发展国土空间布局背景下,科学评价和分析道路的生态影响对协调生态环境和经济社会可持续发展具有重大意义。选取成渝城市群为研究对象,基于2020年土地利用和交通数据,结合MSPA法、景观连通性指数和MCR模型构建生态网络,通过道路网络模型量化道路综合影响值,再运用景观格局指数、图论法和核密度分析法,点线面结合对比分析。结果显示:(1)研究区生态源地占总面积的51.37%,斑块间连通性良好,但在道路网络影响下生态源地数量增加56.00%,总面积减少了14640.21 km ^(2);(2)生态网络布局发生变化,重要廊道的长度降幅高达45.80%,α、β、γ指数分别下降76.67%、38.86%和40.54%;生态关键点的数量减少了17.80%,生态干扰点的高密度分布区呈现以成都和重庆为中心的“双核”发展趋势。研究表明,道路出现导致研究区约51.41%的生境丧失,其中道路沿线景观和优势景观的景观连接度受到严重影响,整体呈现生态格局破碎化、景观分布均衡化的趋势;生态源地的连接水平与网络连通率降低使得生态网络中的环路数量偏少,重要廊道长度减少了1890.43 km,生态关键点数量减少、距离拉远削减了生态源地间的物种交流,导致生态网络的生态效能降低,生态安全格局稳定性减弱。最后从源地保护和道路选线方面提出建议:在优先保护生态核心源地的同时,采用将交通量引导至已建高等级道路,低等级道路集中紧凑发展的策略,减少路网拓展对生态斑块的分割,以期为成渝地区生态空间保护提供参考。展开更多
文摘A growing number of international studies have highlighted that ambient air pollution exposures are related to different health outcomes. To do so, researchers need to estimate exposure levels to air pollution throughout everyday life. In the literature, the most commonly used estimate is based on home address only or taking into account, in addition, the work address. However, several studies have shown the importance of daily mobility in the estimate of exposure to air pollutants. In this context, we developed an R procedure that estimates individual exposures combining home addresses, several important places, and itineraries of the principal mobility during a week. It supplies researchers a useful tool to calculate individual daily exposition to air pollutants weighting by the time spent at each of the most frequented locations (work, shopping, residential address, etc.) and while commuting. This task requires the efficient calculation of travel time matrices or the examination of multimodal transport routes. This procedure is freely available from the Equit’Area project website: (https://www.equitarea.org). This procedure is structured in three parts: the first part is to create a network, the second allows to estimate main itineraries of the daily mobility and the last one tries to reconstitute the level of air pollution exposure. One main advantage of the tool is that the procedure can be used with different spatial scales and for any air pollutant.
文摘With the development of motorization, road traffic crashes have become the leading cause of death in many countries. Among roadway traffic crashes, almost 90% of accidents are related to driver behaviors, wherein driving anger is one of the most leading causes to vehicle crash-related conditions. To some extent, angry driving is considered more dangerous than typical driving distraction due to emotion agitation. Aggressive driving behaviors create many kinds of roadway traffic safety hazards. Mitigating potential risk caused by road rage is essential to increase the overall level of traffic safety. This paper puts forward an integrated computer vision model composed of convolutional neural network in feature extraction and Bayesian Gaussian process in classification to recognize driver anger and distinguish angry driving from natural driving status. Histogram of gradients (HOG) was applied to extract facial features. Convolutional neural network extracted features on eye, eyebrow, and mouth, which are considered most related to anger emotion. Extracted features with its probability were sent to Bayesian Gaussian process classier as input. Integral analysis on three extracted features was conducted by Gaussian process classifier and output returned the likelihood of being anger from the overall study of all extracted features. An overall accuracy rate of 86.2% was achieved in this study. Tongji University 8-Degree-of-Freedom driving simulator was used to collect data from 30 recruited drivers and build test scenario.
文摘在高质量发展国土空间布局背景下,科学评价和分析道路的生态影响对协调生态环境和经济社会可持续发展具有重大意义。选取成渝城市群为研究对象,基于2020年土地利用和交通数据,结合MSPA法、景观连通性指数和MCR模型构建生态网络,通过道路网络模型量化道路综合影响值,再运用景观格局指数、图论法和核密度分析法,点线面结合对比分析。结果显示:(1)研究区生态源地占总面积的51.37%,斑块间连通性良好,但在道路网络影响下生态源地数量增加56.00%,总面积减少了14640.21 km ^(2);(2)生态网络布局发生变化,重要廊道的长度降幅高达45.80%,α、β、γ指数分别下降76.67%、38.86%和40.54%;生态关键点的数量减少了17.80%,生态干扰点的高密度分布区呈现以成都和重庆为中心的“双核”发展趋势。研究表明,道路出现导致研究区约51.41%的生境丧失,其中道路沿线景观和优势景观的景观连接度受到严重影响,整体呈现生态格局破碎化、景观分布均衡化的趋势;生态源地的连接水平与网络连通率降低使得生态网络中的环路数量偏少,重要廊道长度减少了1890.43 km,生态关键点数量减少、距离拉远削减了生态源地间的物种交流,导致生态网络的生态效能降低,生态安全格局稳定性减弱。最后从源地保护和道路选线方面提出建议:在优先保护生态核心源地的同时,采用将交通量引导至已建高等级道路,低等级道路集中紧凑发展的策略,减少路网拓展对生态斑块的分割,以期为成渝地区生态空间保护提供参考。
