就地冷再生技术在高速公路养护工程中的应用研究

就地冷再生技术具有施工便捷、污染小、旧料回收利用率高、节约成本等优势,在公路养护中得到了利用.以S49新扬高速为例,从适用条件、混合料设计、路用性能验证以及社会经济效益等方面,对就地冷再生技术进行系统研究,结果表明就地冷再生技术在高速公路养护工程中应用效果理想,可进行推广运用.     

地铁车辆定修工艺设计探讨

通过分析地铁车辆定修工艺设计现状及发展趋势,研究适用于定修向定检转化后的主要工艺流程和检修内容,提出定修工艺设计中房屋面积优化和设备配备的方法。工程实例表明,采用本方法可在满足车辆段功能需求的前提下,减小定修房屋面积与设备配备数量,降低工程投资。为地铁车辆段的定修工艺设计提供参考。     

半刚性基层沥青路面结构优化设计

文章在对沥青路面早期损坏原因进行分析的基础上，探讨了解决路面早期损坏的途径，提出了采用组合式基层的优化设计思路，并对组合式基层沥青路面结构进行了设计分析，认为组合式基层沥青路面是一种比较适合于重载交通的路面结构。     

昆山市东城大道快速化改造工程总体设计

东城大道是昆山“双环-四联-八射”快速路系统外环中东环的重要组成部分,对其进行快速化改造须开展总体方案设计研究.以功能需求分析为依托、交通量分析为支撑,梳理了沿线重要节点及控制物,特别针对两处现状隧道控制条件,提出了两个总体设计方案,并对方案进行了论证与比选.最后综合考虑现状隧道、沿线高压铁塔及重要出行节点等控制因素,确定了总体方案和出入口布置,效果良好.     

地铁车辆段综合管线设计研究

研究目的:综合管线设计是地铁车辆段设计的一大难点,也是地铁车辆设计成功与否的关键点之一。通常综合管线是在各专业完成施工图后才能正式开展工作,因此每次综合管线设计的工期都非常短。目前传统的综合管线设计思路及方法已不能满足设计需要,为了较好地解决综合管线设计周期短、质量要求高的难题,推出新的综合管线设计方法尤为迫切。研究结论:通过地面车辆段、双层车辆段综合管线设计的归纳总结,提出采用反推法设计综合管线。采用反推法设计综合管线,将缩短地铁车辆段综合管线设计周期50%,提高了设计质量的同时还提高了设计人员的综合素质。     

Incorporating Driver Behaviors in Network Design Problems: Challenges and Opportunities

The goal of a network design problem (NDP) is to make optimal decisions to achieve a certain objective such as minimizing total travel time or maximizing tolls collected in the network. A critical component to NDP is how travelers make their route choices. Researchers in transportation have adopted human decision theories to describe more accurate route choice behaviors. In this paper, we review the NDP with various route choice models: the random utility model (RUM), random regret-minimization (RRM) model, bounded rationality (BR), cumulative prospect theory (CPT), the fuzzy logic model (FLM) and dynamic learning models. Moreover, we identify challenges in applying behavioral route choice models to NDP and opportunities for future research.     

A mixed logit model for predicting exit choice during building evacuations

Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns is the escape route. The choice of a route may involve local decisions on alternative exits from an enclosed environment. This study investigates the effect of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1503 participants is obtained and a mixed logit model is calibrated using these data. The model shows that the presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model indicates that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main aim of this study is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.     

基于BIM的三维铁路路基建模应用研究

为推进铁路工程建设信息化发展,铁路设计行业大力推进BIM技术研究。通过对现阶段铁路站前专业BIM技术应用实例和路基二维辅助设计方法的广泛调研,提出一种基于运用自主研发的三维铁路路基辅助设计软件的建模方法,结合川藏线拉林段路基区间,完成建模流程和设计成果的展示。实践表明,三维设计有助于设计人员更为全面直观了解实际工程结构,新增可视化效果,提高设计精确性,为铁路路基设计行业带来新的设计理念和运用基础。     

关于城市桥梁在8度强震区的抗震设计讨论

为了研究一般跨径城市桥梁在8度地震区的抗震设计方法,文章以具体工程为例,采用规范推荐的参数和公式,拟合出场地在E1和E2作用下水平地震动反应谱;通过有限元建模分析,对规范推荐的延性抗震体系和减隔震体系做了详细的计算和分析,研究结果标明:两种抗震体系均能满足相关规范的设计要求;但是减隔震体系在设计阶段造价更低,震后修复费用也较小,在经济性方面有较大的优势。     

Daily activity pattern recognition by using support vector machines with multiple classes

The focus of this paper is to learn the daily activity engagement patterns of travelers using Support Vector Machines (SVMs), a modeling approach that is widely used in Artificial intelligence and Machine Learning. It is postulated that an individual’s choice of activities depends not only on socio-demographic characteristics but also on previous activities of individual on the same day. In the paper, Markov Chain models are used to study the sequential choice of activities. The dependencies among activity type, activity sequence and socio-demographic data are captured by employing hidden Markov models. In order to learn model parameters, we use sequential multinomial logit models (MNL) and multiclass Support Vector Machines (K-SVM) with two different dependency structures. In the first dependency structure, it is assumed that type of activity at time ‘t’ depends on the last previous activity and socio-demographic data, whereas in the second structure we assume that activity selection at time ‘t’ depends on all of the individual’s previous activity types on the same day and socio-demographic characteristics. The models are applied to data drawn from a set of California households and a comparison of the accuracy of estimation of activity types and their sequence in the agenda, indicates the superiority of K-SVM models over MNL. Additionally, we show that accuracy in estimating activity patterns increases using different sets of explanatory variables or tuning parameters of the kernel function in K-SVM.