社区步行通达性对独栋住宅房价的效益评估--美国德克萨斯州奥斯丁市空间特征分析

通过分析美国德克萨斯州奥斯丁市2010—2012年独栋住宅的销售价格,以街道智慧步行指数(Street Smart Walk Score)和人行道密度(Sidewalk Density)作为衡量指标,研究社区步行通达性对房价的影响。使用Cliff-Ord空间特征模型(即广义空间模型,General Spatial Model,或者SAC)控制空间自相关影响。结果表明：在依赖小汽车的社区通过增加设施可达性来提升步行通达性的举措并不能提高房价;增加人行道也只能最小限度地提高房价。投资社区便利设施和人行道对适宜步行社区的房价提升效果比依赖小汽车的社区显著。     

The market potential for plug-in hybrid and battery electric vehicles in Flanders: A choice-based conjoint analysis

This paper considers the market potential for battery electric and plug-in hybrid electric vehicles in Flanders, Belgium. Making use of a large-scale survey conducted in 2011 and applying a choice-based conjoint experiment, it is predicted that by 2020, battery electric vehicles could have a market share of about 5% of new vehicles, and plug-in hybrid electric vehicles could have a share of around 7%. By 2030, these figures could increase to 15% and 29%. The speed of up-take of electric vehicles, however, is sensitive to purchase costs.     

Recovery of inter- and intra-personal heterogeneity using mixed logit models

Most applications of discrete choice models in transportation now utilise a random coefficient specification, such as mixed logit, to represent taste heterogeneity. However, little is known about the ability of these models to capture the heterogeneity in finite samples (as opposed to asymptotically). Also, due to the computational intensity of the standard estimation procedures, several alternative, less demanding methods have been proposed, and yet the relative accuracy of these methods has not been investigated. This is especially true in the context of work looking at joint inter-respondent and intra-respondent variation. This paper presents an overview of the various different estimators, gives insights into some of the theoretical properties, and analyses their performance in a large scale study on simulated data. In particular, we specify 31 different forms of heterogeneity, with multiple versions of each dataset, and with results from over 16,000 mixed logit estimation runs. The findings suggest that variation in tastes over consumers is captured by all the methods, including the simpler versions, at least when sample size is sufficiently large. When tastes vary over choice situations for each consumer, as well as over consumers, the ability of the methods to capture and differentiate the two sources of heterogeneity becomes more tenuous. Only the most computationally intensive approach is able to capture adequately the two sources of variation, but at the cost of very high run times. Our results highlight the difficulty of retrieving taste heterogeneity with only cross-sectional data, providing further evidence of the benefits of repeated choice data. Our findings also suggest that the data requirements of random coefficients models may be more substantial than is commonly assumed, further reinforcing concerns about small sample issues.     

Energy policies for passenger motor vehicles

This paper assesses the costs and effectiveness of several energy policies for light-duty motor vehicles in the United States, using a version of the National Energy Modeling System. The policies addressed are higher fuel taxes, tighter vehicle efficiency standards, and financial subsidies and penalties for the purchase of high- and low-efficiency vehicles (feebates). I find that tightening fuel-efficiency standards beyond those currently mandated through 2016, or imposing feebates designed to accomplish similar changes, can achieve by 2030 reductions in energy use by all light-duty passenger vehicles of 7.1–8.4%. A stronger feebate policy has somewhat greater effects, but at a significantly higher unit cost. High fuel taxes, on the order of $2.00 per gallon (2007$), have somewhat greater effects, arguably more favorable cost-effectiveness ratios, and produce their effects much more quickly because they affect the usage rate of both new and used vehicles. Policy costs vary greatly with assumptions about the reason for the apparent myopia commonly observed in consumer demand for fuel efficiency, and with the inclusion or exclusion of ancillary costs of congestion, local air pollution, and accidents.     

Road pricing — an outsider's view of American experiences

Abstract

Substantial changes in urban transport policy have taken place over the past decade. The concern with expanding infrastructure and the preoccupation with providing sufficient road capacity to meet the increasing demand of unrestricted car use, which characterized transport policy in the 1950s and 1960s, has gradually given way to the idea that there is a need to restrain motor traffic if urban society is to function efficiently. A variety of restrictive physical traffic management, land use planning and economic policies have, in consequence, been pursued. One option which has attracted considerable attention in the academic literature, but which has been received more cooly by policy‐makers, is the possibility of optimizing urban traffic congestion through the imposition of road pricing. The introduction and relative success of the area licensing scheme in Singapore has added fuel to the arguments of the advocates of such a policy. This review is not directly concerned with either the experiment with road pricing in Singapore nor the theoretical debates which have taken place concerning the potential merits and defects of such policies but rather looks at the applied work in the United States which has looked into the practical implications of road pricing for its cities. Further, it seeks to explore, again drawing on American experiences, just why there has been so much opposition to the employment of economic pricing principles in the urban road transport market. The author presents the results of an SSRC sponsored study into the practical problems of introducing road pricing to cities in the United States.     

Exploration of route choice behavior with advanced traveler information using neural network concepts

A model of driver's route choice behavior under advanced traveler information system (ATIS) is developed based on data collected from learning experiments using interactive computer simulation. The experiment subjected drivers to 32 simulated days in which they were to choose between the freeway or a side road. A neural network model is used as a convenient modeling technique in this initial phase of the analysis. The results indicated that most subjects made route choices based mainly on their recent experiences. It was also demonstrated that route choice behaviors are related to the personal characteristics as well as the characteristics of the respective routes. Travel experiences have less effect on the choice of the side road compared to the freeway and the results indicate that the prediction accuracy of the model, the acceptance rate of advice, and the quality of advice are closely correlated. The model developed here was for advice consistently provided at a level of 75 percent accuracy. The paper concludes with a discussion of experimental limitations and suggestions for future research.     

Who can recharge a plug-in electric vehicle at home?

We construct consumer-informed estimates of residential access to vehicle charging to guide understanding of plug-in electric vehicle demand, use, and energy impacts. Using a web-based survey, study 1 estimates that about half of new car-buying US households park at least one vehicle within 25 ft of a Level 1 (110/120 V) electrical outlet at home. Study 2 estimates that just under one-third of new car-buying households in San Diego County have access to Level 2 (220/240 V) charging. Further, 20% of the sample are both able and willing to install Level 2 PEV recharging infrastructure at the prices examined.     

Weaving marine food webs from end to end under global change

Marine food web dynamics are determined by interactions within and between species and between species and their environment. Global change directly affects abiotic conditions and living organisms, impinging on all trophic levels in food webs. Different groups of marine researchers traditionally study different aspects of these changes. However, over medium to long time scales perturbations affecting food webs need to be considered across the full range from nutrients to top predators. Studies of end-to-end marine food webs not only span organism sizes and trophic levels, but should also help align multidisciplinary research to common goals and perspectives. Topics are described that bridge disciplinary gaps and are needed to develop new understanding of the reciprocal impacts of global change on marine food webs and ocean biogeochemistry. These include (1) the effects of nutrients on biomass and production, (2) the effects of varying element ratios on food web structure and food quality, (3) bulk flows of energy and material in food webs and their efficiencies of transfer, (4) the ecological effects of species richness and the roles of microbial organisms, (5) the role of feeding behaviour in food web dynamics and trophic controls, (6) the spatial dynamics of communities and links between different food webs, (7) the combined effects of body size and behaviour in determining dynamics of food webs, and (8) the extent to which the ability of marine organisms (and communities) to adapt will influence food web dynamics. An overriding issue that influences all topics concerns the time and space scales of ecosystem variability. Threads link different nodes of information among various topics, emphasizing the importance of tackling food web studies with a variety of modelling approaches and through a combination of field and experimental studies with a strong comparative approach.     

Anticipating plug-in hybrid vehicle energy impacts in California: Constructing consumer-informed recharge profiles

Plug-in hybrid electric vehicles (PHEVs) can be powered by gasoline, grid electricity, or both. To explore potential PHEV energy impacts, a three-part survey instrument collected data from new vehicle buyers in California. We combine the available information to estimate the electricity and gasoline use under three recharging scenarios. Results suggest that the use of PHEV vehicles could halve gasoline use relative to conventional vehicles. Using three scenarios to represent plausible conditions on PHEV drivers’ recharge patterns (immediate and unconstrained, universal workplace access, and off-peak only), tradeoffs are described between the magnitude and timing of PHEV electricity use. PHEV electricity use could be increased through policies supporting non-home recharge opportunities, but this increase occurs during daytime hours and could contribute to peak electricity demand. Deferring all recharging to off-peak hours could eliminate all additions to daytime electricity demand from PHEVs, although less electricity is used and less gasoline displaced.