长途跨线高速列车直达与中转选择问题

我国快速客运网基本形成,长途跨线列车直达与中转选择对于高速列车开行方案设计至关重要。为提升长途跨线高速列车开行效益和服务品质,按长途跨线列车直达与中转方式对比的思路,以旅客出行需求、基础设施能力、移动设备能力等多方面因素对长途跨线列车开行方式的影响为约束条件,研究长途跨线列车直达与中转选择模型及求解方法。选取2025年15个长途跨线起讫点为对象进行案例研究,提出D站—E站、F站—D站等9个起迄点之间开行长途跨线直达列车的建议方案,研究表明直达与中转换乘选择模型能够解决长途跨线列车开行方案编制问题。     

Effects of income inequality on evacuation,reentry and segregation after disasters

Large-scale disasters often trigger mass evacuation due to significant damages to urban systems. Understanding the evacuation and reentry (return) process of affected individuals is crucial for disaster management. Moreover, measuring the heterogeneity in the individuals' post-disaster behavior with respect to their socio-economic characteristics is essential for policy making. Recent studies have used large-scale location datasets collected from mobile devices to analyze post-disaster mobility patterns. Despite the availability of such data and the societal importance of the problem, no studies have focused on how income inequality affects the equity in post-disaster mobility. To overcome these research gaps, we overlay mobility data with income information from census to quantify the effects of income inequality on evacuation and reentry behavior after disasters, and the resulting spatial income segregation. Spatio-temporal analysis using location data of more than 1.7 million mobile phone users from Florida affected by Hurricane Irma reveal significant effects of income inequality on evacuation behavior. Evacuees with higher income were more likely to evacuate from affected areas and reach safer locations with less damage on housing and infrastructure. These differences were common among evacuees from both inside and outside mandatory evacuation zones. As a result of such effects of inequality, significant spatial income segregation was observed in the affected areas. Insights on the effects of income inequality on post-disaster mobility and spatial segregation could contribute to policies that better address social equity in pre-disaster preparation and post-disaster relief.     

基于狄利克雷过程混合模型的城市活动聚类方法研究

手机信令数据不仅记录个体出行轨迹，也为分析城市活动空间分布特征提供了基础.本文提出一种基于狄利克雷混合模型的城市活动特征聚类方法，以手机信令提取居民出行OD为基础，将每个基站的到发出行量作为表征该基站所处空间位置的活动特征，研究特征的聚类方法.引入狄利克雷分布作为先验分布，由中餐馆模型推定特征聚类数量.与其他聚类方法相比，该方法最大的优点在于无需事先指定聚类数量，避免了传统聚类方法的缺陷.将本文方法应用到三亚市城市活动特征聚类当中，结果能够有效地反应不同城市功能组团的活动特征.     

Road vehicle emission inventory of a Brazilian metropolitan area and insights for other emerging economies

The vehicle fleet in the Ceará state has grown 180% over the last ten years. The growth of the resulting emissions is unknown in view of the expansion of this fleet in the greater Fortaleza Metropolitan Area (FMA). The largest fleet in the FMA is in the Fortaleza city itself, where flex fuel vehicles predominate (∼30%). Flex fuel motorcycles increased significantly (greater than 800%) between 2010 and 2015. This paper aims to estimate the road vehicle emissions of carbon monoxide (CO), non-methane hydrocarbons (NMHC), aldehydes (RCHO), nitrogen oxides (NO_x), and particulate matter (PM) from the main road vehicle fleets of Fortaleza and its metropolitan area using a macrosimulation, bottom-up method, between 2010 and 2015. The results showed that road vehicle emissions of CO, NMHC and RCHO increased mainly by Otto cycle vehicles increase due to the introduction of flex fuel vehicles; however, the NO_x and PM emissions noticeable reduction is also a result of emission policies that seed the introduction of new technologies. In 2015, more than 70,000 tons of CO (21.2 ton/1000person), 8000 tons of NMHC (2.5 ton/1000person), 290 tons of RCHO (0.09 ton/1000person), 15,000 tons of NO_x (4.4 ton/1000person) and 600 tons of PM (0.2 ton/1000person) were emitted in the region under study. Comparing with other Brazilian regions, FMA emit higher levels of pollutants per inhabitant than the state of São Paulo and the state of Rio de Janeiro but lower levels than Porto Alegre city.     

The carbon footprint of business travel in the knowledge-intensive service sector

We explore the travel needs and patterns, and the corresponding carbon footprint, of small service organizations during different phases of knowledge-intensive business processes, and compare the results with the priorities given to travel-related goals by staff. We apply a combination of focus group data, mobile positioning, and individual follow-up interviews as study methods. The need for physical travel is determined by a combination of the perceived potential for knowledge creation and transfer offered by each trip, the strength of interpersonal relationships in business networks, and the significance of the travel goal in terms of economic sustainability. The priorities given to travel goals reflect the environmental load of business travel only in domestic contexts, where executing core business processes accounted for the highest carbon footprint. We propose the ways in which the management of business interactions could take into account sociotechnical environment and social recognition of low-carbon communication and travel modes.     

基于云服务的交通量计算系统的设计

为了提高交通量数据采集与计算能力,基于云服务设计了一个交通量计算系统,集中处理全市交通量数据.应用了Windows Mobile智能设备开发技术编写了手机端交通量计数器程序,通过3G网络实现了交通量原始数据的上传.在云服务中心,应用了Excel VBA二次开发技术生成了各种统计图表,调查员在工作中,随时可下载统计图,了解交叉口的实时交通流量、流向等数据.实践证明,该交通量计算系统扩展性良好,能应对大城市交通量计算需求,能够推进智慧交通、智慧城市的建设.     

GSM-R网络安全性分析与对策

GSM—R是在GSM的基础上,针对铁路移动通信的特点而开发的一种专用无线通信系统,其安全性受到网络结构与用户终端移动性本身的制约。本文通过分析GSM—R网络的体系结构特点,讨论了GSM—R系统中存在的网络安全隐患,并提出了相应的防范措施。     

GSM-R在铁路通信中的作用

GSM-R 是欧洲铁路联盟(UIC)在 TDMA 数字移动通信中引入特殊寻址方式和高级语音呼叫业务而形成的技术体制。铁道部决定采用欧洲 GSM—R作为我国铁路移动通信体制,并根据我国铁路行车密度高、运输组织复杂等特点,引进通用分组无线业务子系统(GPRS),与既有线调度通信系统相结合。GSM-R 能够在一个综合平台上提供丰富的综合调度通信业务,特别是能够为列车控制提供无线数据传输,具有强大的调度功能。     

基于二进制签名树的移动受信证书管理模型

对目前PKI体系中的证书信任关系和用户受信证书管理进行分析,指出由于数字证书的体积问题,限制了受信根证书的移动,从而制约了移动用户网络安全事务的处理。提出基于二进制签名树的移动受信证书管理模型。利用该模型把用户的受信证书与用户的私钥和个人证书一起存储于IC卡中,使移动用户利用便携的IC卡能方便安全地建立信任关系,进行网络安全事务处理。通过对移动受信证书管理模型存储计算和受信证书验证计算分析,该模型具有较小的存储体积和受信证书验证计算量。     

A trade-off analysis between penetration rate and sampling frequency of mobile sensors in traffic state estimation

The rapid-growth of smartphones with embedded navigation systems such as GPS modules provides new ways of monitoring traffic. These devices can register and send a great amount of traffic related data, which can be used for traffic state estimation. In such a case, the amount of data collected depends on two variables: the penetration rate of devices in traffic flow (P) and their data sampling frequency (z). Referring to data composition as the way certain number of observations is collected, in terms of P and z, we need to understand the relation between the amount and composition of data collected, and the accuracy achieved in traffic state estimation. This was accomplished through an in-depth analysis of two datasets of vehicle trajectories on freeways. The first dataset consists of trajectories over a real freeway, while the second dataset is obtained through microsimulation. Hypothetical scenarios of data sent by equipped vehicles were created, based on the composition of data collected. Different values of P and z were used, and each unique combination defined a specific scenario. Traffic states were estimated through two simple methods, and a more advanced one that incorporates traffic flow theory. A measure to quantify data to be collected was proposed, based on travel time, number of vehicles, penetration rate and sampling frequency. The error was below 6% for every scenario in each dataset. Also, increasing data reduced variability in data count estimation. The performance of the different estimation methods varied through each dataset and scenario. Since the same number of observations can be gathered with different combinations of P and z, the effect of data composition was analyzed (a trade-off between penetration rate and sampling frequency). Different situations were found. In some, an increase in penetration rate is more effective to reduce estimation error than an increase in sampling frequency, considering an equal increase in observations. In other areas, the opposite relationship was found. Between these areas, an indifference curve was found. In fact, this curve is the solution to the optimization problem of minimizing the error given any fixed number of observations. As a general result, increasing sampling frequency (penetration rate) is more beneficial when the current sampling frequency (penetration rate) is low, independent of the penetration rate (sampling frequency).