An investigation of tour generation models combining two waves of household travel surveys through pooled models

This paper presents a study that examines two waves of travel survey data through a pooled model structure. The pooled model structure provides a means to take advantage of multiple data sources which will lead to a better estimate and understanding of travel behavior. In particular, it accounts for the difference in data variance and therefore allows for the comparison of the true impacts of the model parameters on travelers’ tour-making behavior. Larger variance is found in the 1998 data than in the 2010 data. Comparison between model parameters reveals significant behavioral changes among several socio-economic and demographic groups. In terms of common variables, the magnitude of the coefficient values has generally decreased, which conforms to the overall decreasing trend in traveling. Overall, the model equality tests indicate that the models developed based on the two data sources do not have equal taste parameters, thus the transferability hypothesis is rejected. The results of this study are expected to have implications for the application of models based on cross-sectional data, especially over long time periods.     

Incorporating online shopping into travel demand modelling: challenges,progress, and opportunities

There is a large body of literature, spanning multiple disciplines, concerned with the relationship between traditional (physical) shopping and associated travel behaviour. However, despite the recent rapid growth of digital retailing and online shopping, the impact on travel behaviour remain poorly understood. Although the issue of the substitution and complementarity between conventional and virtual retail channels has been extensively explored, few attempts have been made to extend this work so as to incorporate virtual retail channels into modelling frameworks that can link shopping and mobility decisions. Here, we review the existing literature base with a focus on most relevant dimensions for personal mobility. How online activity can be incorporated into operational transport demand models and benefits of such effort are discussed. Existing frameworks of shopping demand are flexible and can, in principle, be extended to incorporate virtual shopping and the associated additional complexities. However, there are significant challenges associated with lack of standard ontologies for crucial concepts and insufficiencies in traditional data collection methods. Also, supply-side questions facing businesses and policy-makers are changing as retailing goes through a digital transformation. Opportunities and priorities need to be defined for future research directions for an assessment of existing tools and frameworks.     

规则波中船舶波浪增阻理论和经验法预报分析与比较

针对规则波中迎浪下有航速集装箱船船型阻力增加预报,采用一种改进的三维移动脉动源面元法求解船舶运动,进而通过理论方法求解辐射和绕射增阻.速度势求解引入了格林函数空间线段积分和面元积分方法,辐射增阻采用三维辐射能量法计算,绕射增阻通过二阶波浪力中绕射速度势获得.通过与试验数据对比证明了该理论预报模型在精度和效率方面有明显优势.在此预报结果基础上对经验预报模型提出了改进公式,计算结果表明了改进模型对工程设计具有较好的适用性.     

多种多学科设计优化方法的比较研究

多学科设计优化(Multidisciplinary Design Optimization,MDO)是一种通过充分探索和利用系统间的相互作用的协同机制来设计复杂系统工程和子系统的方法论.随着多学科设计优化方法在船舶与海洋工程中的广泛应用,多学科设计优化方法越来越受到重视,目前已经发展出了多种不同的具体算法.该文的主要目的就是对这些现有的算法开展比较研究,为后续的应用选择奠定基础.论文首先介绍了MDO算法的分类和发展,对各种MDO算法的优缺点进行了比较分析,最后再通过具体算例来显示这些方法的差别.     

Estimating heterogeneity of car travelers on mode shifting behavior based on discrete choice models

In order to understand the mode shift behavior of car travelers and relieve traffic congestion, a Stated Preference survey has been conducted in the city of Ji'nan in China to analyze bus choice behavior and the heterogeneity of car travelers. Several discrete choice models, including multinomial logit, mixed logit and latent class model (LCM) are developed based on these survey data. A comparative analysis indicates that the LCM has the highest precision and is more suitable to analyze the heterogeneity of car travelers. The LCM divides car travelers into three classes. Different classes have different sets of influencing factors in the model. Policy recommendations are also proposed for those classes to promote bus shift from car travelers based on the model results. Finally, sensitivity analysis on parking fees and fuel cost is carried out on the LCMs under different bus service levels. Car travelers have different sensitivities to the influencing factors. The conclusions indicate that the LCM can reflect the heterogeneity and preferences of car travelers and can be used to understand how to shift the behavior of car travelers and make more effective traffic policy.     

国外大比例潜艇模型试验研究

采用大比例潜艇模型进行试验测试可有效评估、预测潜艇战技性能,从而推进潜艇研制工作.与实艇试验相比,大比例潜艇模型试验具有低成本、无人员安全风险等突出优点.本文将研究国外大比例潜艇模型试验情况,分析未来潜艇大比例模型试验发展趋势.     

果蝇算法在基于LSSVM智能水下机器人操纵运动模型辨识中的应用

基于水下机器人的Z型仿真试验,应用支持向量机对水下机器人的操纵运动模型进行辨识,从核函数结构中得到水动力系数,并建立水下机器人的预报模型,引入果蝇算法对惩罚因子C进行寻优,以减少基于经验而选择的参数对辨识精度产生的影响。通过预报与仿真比较,验证了该方法的有效性。     

小水线面双体船下潜体局部强度分析研究

本文针对小水线面双体船特有的下潜体结构,运用MSC.Patran软件建立下潜体有限元模型,参考英国劳氏船级社特种船规范中的设计载荷,对下潜体典型部位三舱段模型进行计算分析,并考虑了破损工况下的下潜体局部强度问题。计算结果表明,下潜体各舱室破损状态下的应力比健康状态下大,且下潜体船艏和艉部目标舱的应力比舯部略大,各目标舱中强扶强材、纵桁、横框架和横舱壁是应力较大的结构,在设计和建造时应重点考虑。     

Truck trip generation in small- and medium-sized urban areas

This paper describes procedures to develop truck trip generation (TTG) rates for small- and medium-sized urban areas and its implications. Ordinary least squares models are used to develop separate truck production and attraction equations with the number of employees as the independent variable for three industrial groups – retail, transportation and warehousing, and manufacturing. Results from this research indicate that number of employees is a statistically significant predictor, and has significant explanatory power in predicting the number of truck trips produced and attracted. The rates developed in this study are also found to be significantly different from rates developed in other studies with the implication that caution needs to be taken when transferring TTG rates. The rates are applied in a travel demand model as the initial step of incorporating truck traffic into the modeling process.     

基于AQPSO算法的圆碟形水下滑翔机路径规划

为解决复杂海洋环境影响下圆碟形水下滑翔机的路径规划问题,采用多黏性Lamb涡叠加方法模拟洋流环境模型。以最小能量消耗为优化目标,结合B-spline方法生成光滑的曲线路径,采用自适应性基于量子行为的粒子群优化算法对圆碟形水下滑翔机的路径选择进行优化求解。将该算法与粒子群优化算法和基于量子行为的粒子群优化算法相对比,仿真结果验证了各算法在求解航行路径问题方面的有效性。此外,基于能耗最优原则分析各算法的适用性。