排序方式: 共有98条查询结果,搜索用时 281 毫秒
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基于岸线资源价值利用的研究 总被引:2,自引:0,他引:2
港口岸线具有"稀缺性"的天然禀赋,它是港口发展重要的物质基础。然而,大多数岸线的使用者仅把岸线当成无需成本的"免费"资源,造成了大量的浪费。介绍了国内外的对岸线资源价值利用的研究现状。阐述了岸线有偿使用的实例和港口岸线收费的依据,着重阐述了如何实施岸线有偿使用的价值实现,可供参考。 相似文献
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船舶网络信息采集系统的应用分析及优化 总被引:1,自引:0,他引:1
以“大洋一号”科学考察船网络信息集成系统建设项目为背景实例,介绍了基于该船网络的信息采集系统工作原理,利用数学模型分析网络信息采集的性能,针对分析结果重点开展有关系统实时性、可靠性优化方案的研究和探索。 相似文献
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通过对两种不同固化剂在不同剂量情况下稳定粉土的强度、刚度、水稳定性、冻融稳定性及干缩、温缩等性能的实验研究,分析了水泥基及石灰基的两种固化剂在相同配合比及同一种固化剂不同配合比或不同龄期情况下的路用性能的变化规律,得出了适当配合比的固化剂稳定粉土能够满足路面基层材料的要求,并结合使用性能提出了实际应用时应重点注意的问题,为工程应用做了一定的准备。 相似文献
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Erika Spissu Abdul Rawoof Pinjari Ram M. Pendyala Chandra R. Bhat 《Transportation》2009,36(4):403-422
In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles
drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete–continuous model system formulated in this study
explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e.,
self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive
distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components.
The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation
approaches for joint discrete–continuous model systems. The model system, when applied to simulate the impacts of a doubling
in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.
Erika Spissu is currently a Research Fellow at the University of Cagliari (Italy). She received her Ph.D. from the University of Palermo and University of Cagliari (Italy) in Transport techniques and economics. She spent the past 2 years at The University of Texas at Austin as a Research Scholar focusing primarily in activity-based travel behavior modeling, time use analysis, and travel demand forecasting. Abdul Pinjari is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of South Florida, Tampa. His research interests include time-use and travel-behavior analysis, and activity-based approaches to travel-demand forecasting. He has his Ph.D. from The University of Texas at Austin. Ram M. Pendyala is a Professor of Transportation Systems in the Department of Civil, Environmental, and Sustainable Engineering at Arizona State University. He teaches and conducts research in travel behavior analysis, travel demand modeling and forecasting, activity-based microsimulation approaches, and time use. He specializes in integrated land use-transport models, transport policy formulation, and public transit planning and design. He is currently the Vice-Chair of the International Association for Travel Behavior Research and is the immediate past chair of the Transportation Research Board Committee on Traveler Behavior and Values. He has his PhD from the University of California at Davis. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. 相似文献
Chandra R. Bhat (Corresponding author)Email: |
Erika Spissu is currently a Research Fellow at the University of Cagliari (Italy). She received her Ph.D. from the University of Palermo and University of Cagliari (Italy) in Transport techniques and economics. She spent the past 2 years at The University of Texas at Austin as a Research Scholar focusing primarily in activity-based travel behavior modeling, time use analysis, and travel demand forecasting. Abdul Pinjari is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of South Florida, Tampa. His research interests include time-use and travel-behavior analysis, and activity-based approaches to travel-demand forecasting. He has his Ph.D. from The University of Texas at Austin. Ram M. Pendyala is a Professor of Transportation Systems in the Department of Civil, Environmental, and Sustainable Engineering at Arizona State University. He teaches and conducts research in travel behavior analysis, travel demand modeling and forecasting, activity-based microsimulation approaches, and time use. He specializes in integrated land use-transport models, transport policy formulation, and public transit planning and design. He is currently the Vice-Chair of the International Association for Travel Behavior Research and is the immediate past chair of the Transportation Research Board Committee on Traveler Behavior and Values. He has his PhD from the University of California at Davis. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. 相似文献
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Lin HeWei Chen Guenter Conzelmann 《Transportation Research Part D: Transport and Environment》2012,17(3):208-214
We analyze the vehicle usage and consumer profile attributes extracted from both National Household Travel Survey and Vehicle Quality Survey data to understand the impact of vehicle usage upon consumers’ choices of hybrid electric vehicles in the US. In addition, the key characteristics of hybrid vehicle drivers are identified to determine the market segmentations of hybrid electric vehicles and the critical attributes to include in the choice model. After a compatibility test of two datasets, a pooled choice model combining both data sources illustrates the significant influences of vehicle usage upon consumers’ choices of hybrid electric vehicles. Even though the data-bases have in the past been used independently to study travel behavior and vehicle quality ratings, here we use them together. 相似文献
36.
Increasing CO2 emissions from the transport sector have raised substantial concerns among researchers and policy makers. This research examines the impact of the built environment on individual transport emissions through two mediate variables, vehicle usage and vehicle type choice, within a structural equation modelling (SEM) framework. We find that new-urbanism-type built environment characteristics, including high density, mixed land use, good connectivity, and easy access to public transport systems help reduce transport CO2 emissions. Such mitigating effect is achieved largely through the reduced vehicle miles travelled (VMT) and is enhanced slightly by the more efficient vehicles owned by individuals living in denser and more diverse neighborhoods, all else being equal. Our research findings provide some new evidence that supports land use policies as an effective strategy to reduce transport CO2 emissions. 相似文献
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汽车使用诸因素对燃油经济性的影响分析与试验研究 总被引:2,自引:0,他引:2
结合科技文献理论,从气象争件、道路状况、驾驶行为等各个方面详细分析了使用因素对汽车燃油经济性的影响,并且通过大量气象备件和道路状况试验,对汽车燃油经济性的影响进行了定量的研究。得出汽车使用诸因素中环境争件、道路状况和驾驶行为对汽车燃油经济性的影响不可低估。温度对汽车燃油经济性的影响并不是简单的比例关系,环境温度高于常温时。温度对于汽车的影响相对比较稳定。而高温与低温的油耗相比相差悬殊。环境温度为-10℃时和常温相比,其燃油消耗量增加竞高达45%,在不同道路类型中,汽车在省级公路上行驶最省油,不同的道路条件对燃油经济性的影响高达30%,不同的驾驶行为对燃油消耗量也能产生高达20%的影响。 相似文献
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结合北京市典型信号控制交叉口实际情况,现场调查高峰时段7个保护相位下专用双左转车道的车头时距、周期流量、大型车比例等数据,对双左转车道使用特性和调头车辆影响特性进行分析。结果表明,左转车辆的内、外侧车道利用率为50%,大型客车倾向于选择外侧左转车道行驶,给出双左转饱和流率的范围为1587~1818pcu/h/ln,平均值为1665pcu/h/ln,并且得到内、外侧左转饱和车头时距均值无显著性差异的结论。考虑到内侧车道特有的调头行为对左转车辆运行的影响,用数学方法确定了调头行为带来影响的范围,给出左转调头车辆相对于左转标准小型车的当量值为1.39。 相似文献
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