城市道路工程建设项目的优先排序——以编制天津中心城区2000年～2010年干道路网建设计划为例

进入二十一世纪 ,天津将为完善规划干线路网继续做出坚持不懈的努力。为了使项目建设计划更加科学化 ,本文特对影响道路工程建设项目排序的诸因素进行了分析 ,做到了定性与定量相结合 ,在此基础上 ,提出了 2 0 0 0年～ 2 0 0 5年 ,2 0 0 6年～ 2 0 1 0年道路建设项目的实施计划的建议     

贵阳市艺校立交桥设计

本文介绍新建贵阳市艺校立交桥的交通概况 ,流量分析 ,设计特点与内容。     

不确定条件下的汽车产品开发投资评价模型构建

主要提出了在不确定条件下汽车开发投资的评价模型。首先对汽车开发投资的不确定性进行了分析,然后根据总结的汽车行业不确定的特征,构建了汽车产品投资的评价模型体系,包括实物期权思想下的汽车产品开发决策模型、在专家评价模型基础上构建的汽车产品立项评价模型和在过程评价模型基础上构建的汽车产品开发过程评价模型。     

具有随机利率和波动率的复合期权定价

在复合期权的定价研究中,Geske(1979)公式的不足之处在于其假设利率和波动率均为常数.Geman-El Karoui-Rochet(1995)、Hull(1998,2000)等人也是假设波动率或利率之一为常数.本文对Geske公式加以推广,得出了利率和波动率都随机波动时的复合期权定价公式,具有更强的实践意义.     

沈阳市两种严重失误的道路立交设计方案

沈阳市于1988年修建了方型广场立交,1992年修建了5座“土台子”立交,这6座立交属于两种方案,都存在严重缺憾,历经8a最长17a运营之后,终于在今年全部拆除或部分拆除。为了总结这一事件的经验教训,对这两种立交设计方案的出台和实施情况进行了回顾,提出了该立交设计方案的种种弊端和科学地决策立交设计方案的建议。     

超大跨隧洞工程施工经验介绍

某洞库工程开挖跨度达44.4 m,同时具有矢跨比甚小、断面扁平的特点,如何优化开挖方案、确保工程安全、优质施工,是值得深入探讨和研究的问题。文章分析了影响超大跨形成的因素,介绍了该工程开挖方案的确定、实施及有关体会,对后续类似工程施工有一定借鉴作用。     

烟大渤海海峡隧道的可行性研究探讨

文章从环渤海及沿海地区的经济发展需要和渤海海峡的自然、地质条件等情况出发,论述了修建渤海海峡跨海通道的必要性,研究分析了海峡通道的“南桥北隧”方案,并对海底隧道的不同方案及其施工方法进行了比较。回顾和展望了世界各国和我国修建水底隧道的情况和规划前景,以我国目前的隧道技术水平和经济实力为依据,论证了在近几十年内修建渤海海峡隧道的可行性,并提出应尽快组织力量进行渤海海峡隧道的前期地质调查及规划工作。     

生物岛-大学城沉管隧道最终接头设计

最终接头的位置和选型对沉管隧道的工期和造价有较大影响,以生物岛-大学城隧道最终接头的设计实例,介绍了沉管隧道最终接头的设计方案和施工技术措施,对今后类似工程的设计有一定的指导意义。     

Real time transit demand prediction capturing station interactions and impact of special events

Demand for public transportation is highly affected by passengers’ experience and the level of service provided. Thus, it is vital for transit agencies to deploy adaptive strategies to respond to changes in demand or supply in a timely manner, and prevent unwanted deterioration in service quality. In this paper, a real time prediction methodology, based on univariate and multivariate state-space models, is developed to predict the short-term passenger arrivals at transit stations. A univariate state-space model is developed at the station level. Through a hierarchical clustering algorithm with correlation distance, stations with similar demand patterns are identified. A dynamic factor model is proposed for each cluster, capturing station interdependencies through a set of common factors. Both approaches can model the effect of exogenous events (such as football games). Ensemble predictions are then obtained by combining the outputs from the two models, based on their respective accuracy. We evaluate these models using data from the 32 stations on the Central line of the London Underground (LU), operated by Transport for London (TfL). The results indicate that the proposed methodology performs well in predicting short-term station arrivals for the set of test days. For most stations, ensemble prediction has the lowest mean error, as well as the smallest range of error, and exhibits more robust performance across the test days.     

Real world vehicle emissions: Their correlation with driving parameters

Vehicular population in developing countries is expected to proliferate in the coming decade, centred on Tier II and Tier III cities rather than large metropolis. WLTP is being introduced as a global instrument for emission regulation to reduce gap between standard test procedures and actual road conditions. This work aims at quantifying and discernment of the gap between WLTC and real-world conditions in an urban city in a developing country on the basis of driving cycle parameters and simulated emissions for gasoline fuelled light passenger cars. Real world driving patterns were recorded on different routes and varying traffic conditions using car-chasing technique integrated with GPS monitoring and speed sensors. Real-world driving patterns and ambient conditions were used to simulate emissions using International Vehicle Emissions model for average rate (g/km) and Comprehensive Modal Emissions Model for instantaneous emission (g/s) analysis. Cycle parameters were mathematically calculated to compare WLTC and road trips. The analyses revealed a large gap between WLTC and road conditions. CO emissions were predicted to be 155% higher than WLTC and HC and NOx emissions were estimated to be 63% and 64% higher respectively. These gaps were correlated to different driving cycle parameters. It was observed that road driving occurs at lower average speeds with higher frequency and magnitudes of accelerations. The positive kinetic energy required by road cycles, was 100% higher than WLTC and the Relative Positive Acceleration (RPA) demanded by road cycles, was found to be 60% higher in real-world driving patterns and thereby contribute to higher emissions.