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This paper evaluates the impacts on energy consumption and carbon dioxide (CO2) emissions from the introduction of electric vehicles into a smart grid, as a case study. The AVL Cruise software was used to simulate two vehicles, one electric and the other engine-powered, both operating under the New European Driving Cycle (NEDC), in order to calculate carbon dioxide (CO2) emissions, fuel consumption and energy efficiency. Available carbon dioxide data from electric power generation in Brazil were used for comparison with the simulated results. In addition, scenarios of gradual introduction of electric vehicles in a taxi fleet operating with a smart grid system in Sete Lagoas city, MG, Brazil, were made to evaluate their impacts. The results demonstrate that CO2 emissions from the electric vehicle fleet can be from 10 to 26 times lower than that of the engine-powered vehicle fleet. In addition, the scenarios indicate that even with high factors of CO2 emissions from energy generation, significant reductions of annual emissions are obtained with the introduction of electric vehicles in the fleet. 相似文献
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In recent years, there has been increased interest in using completely anonymized data from smart card collection systems to better understand the behavioural habits of public transport passengers. Such an understanding can benefit urban transport planners as well as urban modelling by providing simulation models with realistic mobility patterns of transit networks. In particular, the study of temporal activities has elicited substantial interest. In this regard, a number of methods have been developed in the literature for this type of analysis, most using clustering approaches. This paper presents a two-level generative model that applies the Gaussian mixture model to regroup passengers based on their temporal habits in their public transportation usage. The strength of the proposed methodology is that it can model a continuous representation of time instead of having to employ discrete time bins. For each cluster, the approach provides typical temporal patterns that enable easy interpretation. The experiments are performed on five years of data collected by the Société de transport de l’Outaouais. The results demonstrate the efficiency of the proposed approach in identifying a reduced set of passenger clusters linked to their fare types. A five-year longitudinal analysis also shows the relative stability of public transport usage. 相似文献
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The existing studies concerning the influence of weather on public transport have mainly focused on the impacts of average weather conditions on the aggregate ridership of public transit. Not much research has examined these impacts at disaggregate levels. This study aims to fill this gap by accounting for intra-day variations in weather as well as public transport ridership and investigating the effect of weather on the travel behavior of individual public transit users. We have collected smart card data for public transit and meteorological records from Shenzhen, China for the entire month of September 2014. The data allow us to establish association between the system-wide public transit ridership and weather condition on not only daily, but also hourly basis and for each metro station. In addition, with the detailed trip records of individual card holders, the travel pattern by public transit are constructed for card holders and this pattern is linked to the weather conditions he/she has experienced. Multivariate modeling approach is applied to analyze the influence of weather on public transit ridership and the travel behavior of regular transit users. Results show that some weather elements have more influence than others on public transportation. Metro stations located in urban areas are more vulnerable to outdoor weather in regard to ridership. Regular transit users are found to be rather resilient to changes in weather conditions. Findings contribute to a more in-depth understanding of the relationship between everyday weather and public transit travels and also provide valuable information for short-term scheduling in transit management. 相似文献
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Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach 总被引:5,自引:2,他引:3
Suburban sprawl has been widely criticized for its contribution to auto dependence. Numerous studies have found that residents
in suburban neighborhoods drive more and walk less than their counterparts in traditional environments. However, most studies
confirm only an association between the built environment and travel behavior, and have yet to establish the predominant underlying
causal link: whether neighborhood design independently influences travel behavior or whether preferences for travel options
affect residential choice. That is, residential self-selection may be at work. A few studies have recently addressed the influence
of self-selection. However, our understanding of the causality issue is still immature. To address this issue, this study
took into account individuals’ self-selection by employing a quasi-longitudinal design and by controlling for residential
preferences and travel attitudes. In particular, using data collected from 547 movers currently living in four traditional
neighborhoods and four suburban neighborhoods in Northern California, we developed a structural equations model to investigate
the relationships among changes in the built environment, changes in auto ownership, and changes in travel behavior. The results
provide some encouragement that land-use policies designed to put residents closer to destinations and provide them with alternative
transportation options will actually lead to less driving and more walking.
Xinyu (Jason) Cao is a research fellow in the Upper Great Plains Transportation Institute at North Dakota State University. His research interests include the influences of land use on travel and physical activity, and transportation planning. Patricia L. Mokhtarian is a professor of Civil and Environmental Engineering, Chair of the interdisciplinary Transportation Technology and Policy graduate program, and Associate Director for Education of the Institute of Transportation Studies at the University of California, Davis. She specializes in the study of travel behavior. Susan L. Handy is a professor in the Department of Environmental Science and Policy and Director of the Sustainable Transportation Center at the University of California, Davis. Her research interests center around the relationships between transportation and land use, particularly the impact of neighborhood design on travel behavior. 相似文献
Susan L. HandyEmail: |
Xinyu (Jason) Cao is a research fellow in the Upper Great Plains Transportation Institute at North Dakota State University. His research interests include the influences of land use on travel and physical activity, and transportation planning. Patricia L. Mokhtarian is a professor of Civil and Environmental Engineering, Chair of the interdisciplinary Transportation Technology and Policy graduate program, and Associate Director for Education of the Institute of Transportation Studies at the University of California, Davis. She specializes in the study of travel behavior. Susan L. Handy is a professor in the Department of Environmental Science and Policy and Director of the Sustainable Transportation Center at the University of California, Davis. Her research interests center around the relationships between transportation and land use, particularly the impact of neighborhood design on travel behavior. 相似文献
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李胜永 《南通航运职业技术学院学报》2010,9(3):77-80
文章分析了当前港口机械监控系统组建遇到的问题,提出了解决问题的方法,并举例说明了如何利用OPC服务器实现监控系统的组建。 相似文献
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本文是在研究校园一卡通平台的基础上,分析现有离校流程中存在的问题,提出基于一卡通平台的离校注销系统的设计与实现方案,使得每个用户拥有符合自己情况的离校流程,用户仅需持一卡通到他所需办理的部门办理手续,取代了原有的每个用户都要跑一遍的离校转单,简化离校手续办理流程,且减少了各部门的工作量,同时为学校各个部门提供统一准确的人员离校信息及统计结果,为建立全校统一人员数据中心提供强有力的保障,有效促进数字化校园的建设. 相似文献
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