Mainstream consumers driving plug-in battery-electric and plug-in hybrid electric cars: A qualitative analysis of responses and evaluations

Plug-in electric vehicles can potentially emit substantially lower CO₂ emissions than internal combustion engine vehicles, and so have the potential to reduce transport emissions without curtailing personal car use. Assessing the potential uptake of these new categories of vehicles requires an understanding of likely consumer responses. Previous in-depth explorations of appraisals and evaluations of electric vehicles have tended to focus on ‘early adopters’, who may not represent mainstream consumers. This paper reports a qualitative analysis of responses to electric cars, based on semi-structured interviews conducted with 40 UK non-commercial drivers (20 males, 20 females; age 24-70 years) at the end of a seven-day period of using a battery electric car (20 participants) or a plug-in hybrid car (20 participants). Six core categories of response were identified: (1) cost minimisation; (2) vehicle confidence; (3) vehicle adaptation demands; (4) environmental beliefs; (5) impression management; and, underpinning all other categories, (6) the perception of electric cars generally as ‘work in progress’ products. Results highlight potential barriers to the uptake of current-generation (2010) plug-in electric cars by mainstream consumers. These include the prioritization of personal mobility needs over environmental benefits, concerns over the social desirability of electric vehicle use, and the expectation that rapid technological and infrastructural developments will make current models obsolete. Implications for the potential uptake of future electric vehicles are discussed.     

A discrete choice framework for modeling and forecasting the adoption and diffusion of new transportation services

Major technological and infrastructural changes over the next decades, such as the introduction of autonomous vehicles, implementation of mileage-based fees, carsharing and ridesharing are expected to have a profound impact on lifestyles and travel behavior. Current travel demand models are unable to predict long-range trends in travel behavior as they do not entail a mechanism that projects membership and market share of new modes of transport (Uber, Lyft, etc.). We propose integrating discrete choice and technology adoption models to address the aforementioned issue. In order to do so, we build on the formulation of discrete mixture models and specifically Latent Class Choice Models (LCCMs), which were integrated with a network effect model. The network effect model quantifies the impact of the spatial/network effect of the new technology on the utility of adoption. We adopted a confirmatory approach to estimating our dynamic LCCM based on findings from the technology diffusion literature that focus on defining two distinct types of adopters: innovator/early adopters and imitators. LCCMs allow for heterogeneity in the utility of adoption for the various market segments i.e. innovators/early adopters, imitators and non-adopters. We make use of revealed preference (RP) time series data from a one-way carsharing system in a major city in the United States to estimate model parameters. The data entails a complete set of member enrollment for the carsharing service for a time period of 2.5 years after being launched. Consistent with the technology diffusion literature, our model identifies three latent classes whose utility of adoption have a well-defined set of preferences that are significant and behaviorally consistent. The technology adoption model predicts the probability that a certain individual will adopt the service at a certain time period, and is explained by social influences, network effect, socio-demographics and level-of-service attributes. Finally, the model was calibrated and then used to forecast adoption of the carsharing system for potential investment strategy scenarios. A couple of takeaways from the adoption forecasts were: (1) placing a new station/pod for the carsharing system outside a major technology firm induces the highest expected increase in the monthly number of adopters; and (2) no significant difference in the expected number of monthly adopters for the downtown region will exist between having a station or on-street parking.     

LCI型路缘石自动成型机

LCI型路缘石自动成型机是一种利用沥青混合料修筑道路路缘的专用设备。本文主要介绍了该机工作原理、技术参数、结构设计、沥青混合料的配制及施工工艺。     

乳化沥青的生产,使用与效益分析

介绍了福建泉州公路局乳化沥青站乳化沥青的生产工艺、设备安装及使用情况,对乳化沥青的经济效益进行了分析,认为阳离子乳化沥青对湿矿料具有较强的吸附作用,在多雨的福建省尤为值得推广使用.     

减少水泥砂砾基层开裂的工艺措施

在高等级公路施工中，广泛采用水泥砂砾基层，为防止基层开裂，应该采用合理的施工工艺本文从原材料进场、拌和、运输、摊铺、碾压、初期养护等多方面详细分析了施工中影响砂砾基层开裂的主要因素，提出了合理的施工工艺。     

高速公路柔性路面平整度的控制

指出了高等级公路路基、底基层、基层和联结层施工质量的控制是影响面层平整度的直接因素，重点介绍了国产平地机加装自动找平控制系统的工作概况以及摊铺机全自动找平装置和浮动基准梁的应用，并从实践出发，分析了其他因素对平整度的影响及相应的处理措施。     

雪峰山特长隧道沟槽盖板塑钢模具施工技术

结合雪峰山特长隧道沟槽盖板施工,介绍采用塑钢模具生产沟槽盖板的工艺流程、技术要点和质量控制措施。运用塑钢模具进行沟槽盖板生产效果较好,可在当前及未来预制混凝土构件施工中进一步推广运用。     

铁路信号动态检测数据管理系统

在铁路信号动态检测系统、列控设备动态监测系统和应答器数据管理系统运用的基础上,重点对信号检测项目、数据处理、设备管理等相关技术标准,数据转储设备,地面数据管理系统等进行研究。     

船电产品设计与开发中的电磁兼容问题浅析

本文根据笔者在船舶电气电子产品设计与开发中碰到的电磁兼容问题，分析了其产生原因，介绍了解决电磁干扰问题的多种解决措施。     

浅谈改性沥青路面现场热再生技术的应用

改性沥青路面现场热再生技术是一项应用于改性沥青混凝土路面的维修技术,对该项技术施工工艺及施工中应注意的问题进行了介绍。