城市公交线网差异化计程票价多目标优化

为获取更加接近实际城市公交线网的票价策略，将出行者的社会互动行为与后悔心理引入广义费用，提出线路客流OD矩阵均衡算法；分别以交通管理部门利润最大化及出行者效用最大化为目标，以公交计程票价、发车频率、私家车停车费为变量，建立固定需求下公交线网差异化计程票价多目标优化模型.引入集群智能多目标优化算法求解，并应用于Mandl 标准公交线网.研究发现：以线路里程为标准，差异化计程票制可以有效降低出行成本；依据帕累托最优解调节票价，可以促进出行者选择行为向优势均衡转移.     

感应充电路面技术研究现状与展望

以感应充电技术(Inductive Power Transfer,IPT)为主要特征的充电路面(Electrified Road,e-Road)近年来发展迅速，其可为行进中的电动汽车进行动态无线充电，有效解决电动汽车充电时间过长、续航里程不足等问题，是支撑未来公路交通电气化发展的重要储备技术。详细介绍了IPT系统的工作原理和性能特点，并总结了已有e-Road试验段的充电性能参数和技术就绪度水平。在此基础上，进一步从基础设施角度剖析了e-Road目前存在的主要工程问题及相关研究进展，内容包括：①深入分析了IPT系统工作时因高频磁场通过介电性路面材料所引起的电磁损耗对IPT系统充电效率的影响，并提出了可能的解决方法；②针对充电模块与普通沥青路面存在的力学兼容性问题，从结构受力原理、材料损伤特性等方面总结了e-Road复合结构产生力学损伤加剧效应的原因，并提出了耐久性优化措施；③针对e-Road环境可持续方面存在的不确定性，评估并对比了e-Road与传统道路的全生命周期环境效益，指出了e-Road环境性能研究对电动汽车全生命周期综合效益估算的重要性。此外，还从政策支持、安全性、价格因素等角度对e-Road进行了综合可行性评估，并对充电路面基础设施的未来发展进行了智能化展望，提出了e-Road与其他新型智能道路技术进行有机融合的可能途径。     

Toward using social media to support ridesharing services: challenges and opportunities

Ridesharing has been attracting increasing attention from both academia and industry. One of the challenges posed by the study of ridesharing is to identify the most valuable information for improving the ridesharing decisions taken by participants. Another challenge is to use harvesting techniques to extract specific types of travel-related information. Many methods have been developed by the community in order to solve these issues. However, due to a lack of information sharing between different transit authorities and the difficulty of identifying subjective perceptions of the experience of ridesharing, understanding and evaluating how social media data might support or obstruct goals for mobility, safety and environmental sustainability in ridesharing is a difficult task. In this survey, we first analyze the literature on ridesharing with a focus on the properties and model of service, and introduce a framework to describe the major components required for a ridesharing service. Then, we illustrate the potential value of information extracted from social media and present the rationale for harvesting travel-related data. Finally, we detail some possible directions and different approaches for using social media data, and highlight their assets and drawbacks.     

论宪法作为非确断性的社会评价系统在"新启蒙运动"中的意义

在当前的意识形态领域里，学术界对“新蒙昧主义思潮”的泛起和蔓延给予了很大的关注。相应地国际国内一大批社会人文主义科学家倡导要在全世界范围内开展一场大规模的“新启蒙运动”。“新蒙昧主义思潮”中的“宗教政治蒙昧主义”对宪法政教分离的原则与宪政已经和正在造成重大冲击并产生了消极性影响。对此，宪法学术界应当予以严肃的对待。本文从宪法作为非确断性的社会评价系统的职能角度，作了初步的探讨。     

沪杭磁浮线的社会经济效益分析

沪杭磁浮线对长江三角洲的经济将会带来巨大影响,同时其投入资金巨大.从可量化效益(节约乘客出行时间、提高安全性、提高乘客的劳动生产率、节约城市土地、降低污染、带动沿线不动产的增值、节约能源)和不可量化效益(改善交通促进城市发展、改善居民生活质量)这两大方面对沪杭磁浮线的社会经济效益进行分析.     

渝长高速公路可持续发展能力分析

随着高速公路的大规模建设,2005年我国高速公路通车里程突破4万km,其在社会经济发展中作用日益凸显,如何保证高速公路持续、稳定的运营,以满足不断增长的交通运输需求就显得尤为重要.应用目标持续性评价的理论方法对渝长高速公路的可持续发展能力进行了分析,有助于确保项目在运营期内提高质量的运输服务.     

紧扣民需民意 推进三社联动 探索基层治理新模式

党的十九大对国家治理体系和治理能力现代化提出了新任务、新要求,突出社会化、法治化、智能化、专业化。以湖南省株洲市荷塘区为例,通过深入实施三社联动,不断创新基层治理,推进社会治理体系和治理能力现代化。     

实现城市防洪经济、社会、环境效益三统一

本文从分析防洪经济效益、社会效益、环境效益三者关系入手 ,明确了在生态失衡、灾害频繁、环境问题已经成为危及人类生存与发展的今天 ,实现三者统一协调、整体推进的重要性 ,并提出了工作思路与对策     

可持续交通——各方观点和长期挑战

从交通研究者和实践者的角度出发,以可持续交通这一概念为中心展开讨论。可持续交通宽泛地反映了可持续发展在交通领域的原则。随着可持续性这一概念的外延逐渐扩大,在它的定义、应用和价值取向上出现了不同观点。着重讨论可持续交通,以及如何理解和运用可持续交通,包括:1)将可持续性或者可持续发展作为一个整体的概念,包括关于可持续性的不同方法和定义之间的冲突;2)对可持续交通以及交通领域对其理解的探索;3)使用指标来实现可持续性的应用。然后识别了通往可持续交通之路的若干挑战,包括缺乏清晰定义、可持续性的固有冲突、可持续发展的跨领域本质、各种工作框架和指标体系、可持续发展的政治因素和交通领域实践中的不同观点。基于在该课题上的研究积累,总结解决这些问题的工作框架,提出因地制宜、注重结果、整体的方法来解决可持续交通中的挑战。     

Identifying tourists and analyzing spatial patterns of their destinations from location-based social media data

Reliable travel behavior data is a prerequisite for transportation planning process. In large tourism dependent cities, tourists are the most dynamic population group whose size and travel choices remain unknown to planners. Traditional travel surveys generally observe resident travel behavior and rarely target tourists. Ubiquitous uses of social media platforms in smartphones have created a tremendous opportunity to gather digital traces of tourists at a large scale. In this paper, we present a framework on how to use location-based data from social media to gather and analyze travel behavior of tourists. We have collected data of about 67,000 users from Twitter using its search interface for Florida. We first propose several filtering steps to create a reliable sample from the collected Twitter data. An ensemble classification technique is proposed to classify tourists and residents from user coordinates. The accuracy of the proposed classifier has been compared against the state-of-the-art classification methods. Finally, different clustering methods have been used to find the spatial patterns of destination choices of tourists. Promising results have been found from the output clusters as they reveal most popular tourist spots as well as some of the emerging tourist attractions in Florida. Performance of the proposed clustering techniques has been assessed using internal clustering validation indices. We have analyzed temporal patterns of tourist and resident activities to validate the classification of the users in two separate groups of tourists and residents. Proposed filtering, identification, and clustering techniques will be significantly useful for building individual-level tourist travel demand models from social media data.