Inference on mode preferences,vehicle purchases,and the energy paradox using a Bayesian structural choice model

Discrete choice modeling is experiencing a reemergence of research interest in the inclusion of latent variables as explanatory variables of consumer behavior. There are several reasons that motivate the integration of latent attributes, including better-informed modeling of random consumer heterogeneity and treatment of endogeneity. However, current work still is at an early stage and multiple simplifying assumptions are usually imposed. For instance, most previous applications assume all of the following: independence of taste shocks and of latent attributes, exclusion restrictions, linearity of the effect of the latent attributes on the utility function, continuous manifest variables, and an a priori bound for the number of latent constructs. We derive and apply a structural choice model with a multinomial probit kernel and discrete effect indicators to analyze continuous latent segments of travel behavior, including inference on the energy paradox. Our estimator allows for interaction and simultaneity among the latent attributes, residual correlation, nonlinear effects on the utility function, flexible substitution patterns, and temporal correlation within responses of the same individual. Statistical properties of the Bayes estimator that we propose are exact and are not affected by the number of latent attributes.     

Investigating the impacts of weather variability on individual’s daily activity–travel patterns: A comparison between commuters and non-commuters in Sweden

Understanding travel behaviour change under various weather conditions can help analysts and policy makers incorporate the uniqueness of local weather and climate within their policy design, especially given the fact that future climate and weather will become more unpredictable and adverse. Using datasets from the Swedish National Travel Survey and the Swedish Meteorological and Hydrological Institute that spans a period of thirteen years, this study explores the impacts of weather variability on individual activity–travel patterns. In doing so, this study uses an alternative representation of weather from that of directly applying observed weather parameters. Furthermore, this study employs a holistic model structure. The model structure is able to analyse the simultaneous effects of weather on a wide range of interrelated travel behavioural aspects, which has not been investigated in previous weather studies. Structural equation models (SEM) are applied for this purpose. The models for commuters and non-commuters are constructed separately. The analysis results show that the effects of weather can be even more extreme when considering indirect effects from other travel behaviour indicators involved in the decision-making processes. Commuters are shown to be much less sensitive to weather changes than non-commuters. Variation of monthly average temperature is shown to play a more important role in influencing individual travel behaviour than variation of daily temperature relative to its monthly mean, whilst in the short term, individual activity–travel choices are shown to be more sensitive to the daily variation of the relative humidity and wind speed relative to the month mean. Poor visibility and heavy rain are shown to strongly discourage the intention to travel, leading to a reduction in non-work activity duration, travel time and the number of trips on the given day. These findings depict a more comprehensive picture of weather impact compared to previous studies and highlight the importance of considering interdependencies of activity travel indicators when evaluating weather impacts.     

Ship resistance when operating in floating ice floes: Derivation,validation, and application of an empirical equation

With the effects of global warming, the Arctic is presenting a new environment where numerous ice floes are floating on the open sea surface. Whilst this has improved Arctic shipping navigability in an unprecedented way, the interaction of such floes with ships is yet to be understood to aid the designing of ships and route planning for this region. To further explore this topic, the present work develops a procedure to derive an empirical equation that can predict the effects of such floes on ship resistance. Based on a validated computational approach, extensive data are extracted from simulations of three different ships with varying operational and environmental conditions. The ice-floe resistance is shown to strongly correlate with ship beam, ship buttock angle, ship waterline angle, ship speed, ice concentration, ice thickness and floe diameter, and the regression powers of each of the parameters on resistance are ascertained. This leads to a generic empirical equation that can swiftly predict ice-floe resistance for a given ship in a given condition. Subsequently, demonstrations are given on the incorporation of the derived equation into a set of real-time Arctic ship performance model and voyage planning tool, which can predict a ship's fuel consumption in ice-infested seas and dynamically suggest a route with the least safety concern and fuel consumption. Moreover, the equation is validated by providing ice resistance prediction for experimental and full-scale conditions from multiple sources, showing high accuracy. In conclusion, the empirical equation is shown to give valid and rapid estimates for ice-floe resistance, providing valuable insights into ship designs for the region, as well as facilitating practical applications for polar navigation.     

Perceived service quality of paratransit in developing countries: A structural equation approach

This paper develops empirical models for evaluating the service quality (SQ) of paratransit. Specifically, several models are developed based on structural equation modeling (SEM) using twenty-four SQ variables. To calibrate those models, a data set of 2008 paratransit users of Dhaka City are utilized, who were interviewed with a structured questionnaire to know their experience, level of satisfaction and opinion about the existing service as well as their expectations. SEM reveals the observed and latent SQ variables and their relationship with the overall SQ of paratransit. Among the different models developed, the best one is selected using statistical parameters and resemblance with real life expectations. Out of twenty-four SQ variables, ‘Punctuality and Reliability’ and ‘Service Features’ are respectively found to be the observed and latent variables having the greatest influence on the paratransit SQ. Moreover, the effect of heterogeneity among users on the performance of the best model is investigated. All the study findings support the data collected from the paratransit users. The research outcomes can be utilized by the city transportation officials of developing countries to improve the overall paratransit performance to attract new users as well as retain the current ones.     

Consumer purchase intentions for electric vehicles: Is green more important than price and range?

In view of global warming and climate change, a transition from combustion to electric vehicles (EVs) can help to reduce greenhouse gas emissions and improve air quality. However, high acquisition costs and short driving ranges are considered to be main factors which impede the diffusion of EVs. Since electricity needs to be produced from renewable energy sources for EVs to be a true green alternative, the environmental performance of EVs is also presumed to be an important factor. This paper investigates the role of environmental performance compared to price value and range confidence regarding consumer purchase intentions for EVs. To develop our hypothesis, we interview 40 end-user subjects about their beliefs toward EVs. Then, we perform 167 test drives with a plug-in battery EV and conduct a survey with the participants to test the hypothesis. Results of a structural equation modeling support the hypothesis that the environmental performance of EVs is a stronger predictor of attitude and thus purchase intention than price value and range confidence.     

组合式堵漏箱堵漏过程中的水压作用机理

利用动量定理推导了组合式堵漏箱不同结构形式处于不同工况时的动量方程，探讨了堵漏板垂直堵漏、堵漏板斜置堵漏、堵漏箱垂直堵漏、堵漏箱斜置堵漏等四种工况下堵漏作业过程中的水压作用机理，最后通过堵漏试验对理论分析结果进行了验证。结果表明，理论分析结果与试验现象基本吻合，可以用于组合式堵漏箱的水压计算和测试依据。     

非均质条件下铁路危险货物运输应急响应模型

在无风、没有障碍物的条件下,点源气体均匀稳定地向四周扩散,因此,在均质条件下,铁路应急救援指挥中心能够及时实施救援的区域范围,并用扩散现象描述。在实际应用中,扩散现象受到外界因素的影响,并不是均匀稳定的扩散。用非均质随机扩散方程确定非均质条件下点源气体的扩散过程,通过模拟气体的扩散范围,同时引入阻尼方程,并且把该过程应用于铁路应急救援,进而确定非均质条件下铁路应急指挥中心能够及时做出响应区域范围。     

深水对高桩承台桥墩地震反应的影响*

介绍了 Morison方程考虑动水压力的方法,并计算出了桥墩各部位的动水附加质量。分析了高桩承台桥墩在不同水深和不同地震作用下动水压力对其地震反应的影响,以某黄河大桥的一个高桩承台桥墩为工程实例,利用纤维模型对其进行非线性时程反应分析。结果表明水的存在对高桩承台桥墩动力特性和地震反应的影响较大,因此在进行桥梁抗震设计时动水压力的影响不可忽略。     

基于改进三弯矩法在某物探船可调桨推进轴系校中计算的应用

为使轴系校中计算模型更接近实船轴系运转工况,确保采用可调桨推进系统的船舶安全运行,在考虑螺旋桨水动力影响下,采用改进三弯矩法对轴系校中数值计算模型进行改进。并以某物探船为例,对其可调桨推进系统进行动态轴系校中计算。数值计算结果显示：考虑螺旋桨水动力等动态因素影响的动态轴系校中计算确保了采用调距桨推进轴系船舶在各种工况下的安全运转。     

舰艇特殊进水过程的流量差值迭代算法研究

目前,在进行静水情况下的破损舰艇进水过程中的姿态计算时,通常使用流量差值迭代算法。然而,该算法的使用有一定的局限性。对于存在进满水舱室的特殊进水过程,破口流线的伯努利方程将发生改变,这导致了不能使用目前的迭代公式进行计算。因此,本文以该特殊的进水过程为对象,在对流线伯努利方程修正的基础上,利用隐函数求导模型和克莱姆法则,对此时的流量差值迭代算法进行了建模,并对该算法进行了船模实验验证。最后,针对某船的进水过程进行了仿真计算,横倾角时域变化曲线上的不连续点直观地表明了流量差值迭代算法的改变对进水过程仿真计算的影响。