Modeling the behavioral determinants of travel behavior: An application of latent transition analysis

This paper applies the relatively new method of latent class transition analysis to explore the notion that qualitative differences in travel behavior patterns are substantively meaningful and therefore relevant from explanatory point of view. For example, because the bicycle may function as an important access and egress mode, a car user who also (occasionally) uses the bicycle may be more likely to switch to a public transit profile than someone who only uses the car. Data from the Dutch mobility panel are used to inductively reveal travel behavior patterns and model transitions in these patterns over time. Additionally, the effects of seven exogenous variables, including two important life events (i.e. moving house and changing jobs), on cluster membership and the transition probabilities are assessed. The results show that multiple-mode users compared to single-mode users are more likely to switch from one behavioral profile to another. In addition, age, the residential environment, moving house and changing jobs have strong influences on the transition probabilities between the revealed behavioral patterns over time.     

Using automated walking gait analysis for the identification of pedestrian attributes

Collecting microscopic pedestrian behavior and characteristics data is important for optimizing the design of pedestrian facilities for safety, efficiency, and comfortability. This paper provides a framework for the automated classification of pedestrian attributes such as age and gender based on information extracted from their walking gait behavior. The framework extends earlier work on the automated analysis of gait parameters to include analysis of the gait acceleration data which can enable the quantification of the variability, rhythmic pattern and stability of pedestrian’s gait. In this framework, computer vision techniques are used for the automatic detection and tracking of pedestrians in an open environment resulting in pedestrian trajectories and the speed and acceleration dynamic profiles. A collection of gait features are then derived from those dynamic profiles and used for the classification of pedestrian attributes. The gait features include conventional gait parameters such as gait length and frequency and dynamic parameters related to gait variations and stability measures. Two different techniques are used for the classification: a supervised k-Nearest Neighbors (k-NN) algorithm and a newly developed semi-supervised spectral clustering. The classification framework is demonstrated with two case studies from Vancouver, British Columbia and Oakland, California. The results show the superiority of features sets including gait variations and stability measures over features relying only on conventional gait parameters. For gender, correct classification rates (CCR) of 80% and 94% were achieved for the Vancouver and Oakland case studies, respectively. The classification accuracy for gender was higher in the Oakland case which only considered pedestrians walking alone. Pedestrian age classification resulted in a CCR of 90% for the Oakland case study.     

Incorporating human-factors in car-following models: A review of recent developments and research needs

Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams.It is necessary to consider human-factors in CF modeling for a more realistic representation of CF behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of CF models available in the literature, none of these specifically focuses on the human factors in these models.This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area.     

民办高校系部教学督导工作的探究与实践

教学督导工作要想为人才培养导航护航，适应新时期对人才质量的要求，就必须自我调整，完善，升华。督导体制的建立也是教学督导工作研究的一个方面。很多民办高校形成了由院（一级督导）、系部（二级督导）、学生（三级督导）构成的三级督导体制，并以二级督导和三级督导作为督导工作的主体，充分发挥教师和学生的主观能动性，强调全员参与，建立良好的督导氛围。文中主要针对民办高校系部教学督导的工作方式进行研究和探讨。     

基于NASTRAN的汽车转向节有限元分析

阐述了有限元方法在汽车应用的必要性。对某款车型前悬架在二三种工况下的受力情况进行了分析，并利用PATRAN和NASTRAN有限元分析软件对该车型的转向节进行了强度和变形的分析计算．找出了该结构设计的薄弱环节．为改进设计提供了依据。     

新型GFRP组合梁翼缘有效分布宽度分析

利用能量变分法推导出均布线荷载作用下新型GFRP组合梁翼缘有效分布宽度的理论公式,通过有限元数值模拟验证理论公式可靠性。并借鉴传统钢-混凝土组合梁分析方法,对新型GFRP组合梁翼缘有效分布宽度各种影响因素进行了参数分析。     

32 m超低高度混凝土T梁动力性能试验与分析

为了研究开行120km/h货车后既有铁路32m超低高度混凝土T梁的运营状况、安全性和加固对策,选取1孔32m超低高度混凝土T梁进行自振频率、挠度、振幅等主要动力性能测试。结果发现跨中横向振幅超过限值,不能满足120km/h货车运行,需要提高该梁的竖向和横向刚度。     

某飞鸟式拱桥拱座开裂加固后静动载试验与分析

针对某飞鸟式拱桥拱座加固后结构性能进行静动载试验。分析了静载试验中控制位置变形、应变,吊杆轴力等控制指标,观测了拱座裂缝变化情况。并采用模态分析法比较动载试验所确定桥面前两阶振型及频率,对实测加速度及动挠度变化规律与理论结果进行比较,计算确定冲击系数。试验结果分析表明,该桥检测指标均能满足要求,行车性能较好。表明该桥拱座加固效果良好,使用性能比较理想,可适应设计荷载等级的要求。     

桩-土-结构相互作用对大跨度连续刚架钢桁拱桥地震响应影响研究

以广州新光大桥为例,研究软弱分层土、较软分层土、较硬分层土和岩石地基与群桩相互作用下大跨度连续刚架钢桁拱桥动力特性以及地震响应。研究表明在各种地震时程激励下,不同地基土对大跨度连续刚架钢桁拱桥拱肋以及V形刚架的内力和位移影响很大。随着地基土刚度的增加,在横桥向、顺桥向和竖向地震激励下,主拱肋和边拱肋上弦杆、V形刚架靠边跨斜腿轴力基本呈递减趋势,而V形刚架面内和面外弯矩随地基土刚度变化的规律性不强。     

汽车电动助力转向系统

对目前汽车配置的助力转向系统做了简要比较,指出了机械液压和电子液压助力的缺点,介绍了电动助力转向系统的构成、工作原理、以及主要设计参数和控制特性。此系统的优点是节约能源,提高操作稳定性,是将来动力转向的发展趋势。