长江流域国际集装箱多式联运信息系统研究

通过大量调查研究和数据分析，阐述了长江流域国际集装箱多式联运以及EDI系统的发展现状，指出目前存在的问题，并提出若干建议。     

网络技术：政府能力提升的有效工具

政府能力体现为政府作用于社会的有效程度。科学技术的发展对于提升政府能力具有重要的促进重要。网络技术的发展为政府能力提升提供了一个有效工具，它直接推动了各国政府网络化、信息化的改造。本通过网络技术在政府组织、公共决策、政府行为、公务人员四个方面的具体应用来说明之，并提出我国政府网络化、信息化改造的政策建议。     

网络环境下高校图书馆发展趋势与对策

本文论述了网络环境下高校图书馆的发展趋势,指出了未来高校图书馆是实体图书馆和虚拟图书馆的结合体,同时探讨高校图书馆应采取的应对措施     

基于TOPSIS的铁路应急资源供应优先级研究

在改进传统TOPSIS法缺陷的基础上,针对各类应急资源在不同受灾点的供应优先级各不相同的特点,以提高铁路应急救援处理效率为目标,特别是应急资源储备量、调度运力和时间受约束的条件下,建立铁路应急资源供应优先级评价体系。分析确定影响应急资源供应优先级的评价指标,提出客观熵权计算法确定权重值,以避免由传统主观判断不确定而造成的评价结果不准确。通过计算欧式距离与理想解的相对贴近度,确定待评价铁路应急资源的供应优先级。最后结合模拟算例得出具体的应急资源供应顺序,结果较符合实际情况,验证了该评价方法的可操作性和实用性。     

绿色交通概念解析

分析了交通系统对资源环境的影响机理,在考察"可持续发展"、"低碳"、"节能减排"、"循环"等相关概念的基础上,提出绿色交通的内涵,并对其发展要求和具体理念进行了分析。     

Bayesian network-based formulation and analysis for toll road utilization supported by traffic information provision

Congestion pricing has been proposed and investigated as an effective means of optimizing traffic assignment, alleviating congestion, and enhancing traffic operation efficiencies. Meanwhile, advanced traffic information dissemination systems, such as Advanced Traveler Information System (ATIS), have been developed and deployed to provide real-time, accurate, and complete network-wide traffic information to facilitate travelers’ trip plans and routing selections. Recent advances in ATIS technologies, especially telecommunication technology, allow dynamic, personalized, and multimodal traffic information to be disseminated and impact travelers’ choices of departure times, alternative routes, and travel modes in the context of congestion pricing. However, few studies were conducted to determine the impact of traffic information dissemination on toll road utilizations. In this study, the effects of the provisions of traffic information on toll road usage are investigated and analyzed based on a stated preference survey conducted in Texas. A Bayesian Network (BN)-based approach is developed to discover travelers’ opinions and preferences for toll road utilization supported by network-wide traffic information provisions. The probabilistic interdependencies among various attributes, including routing choice, departure time, traffic information dissemination mode, content, coverage, commuter demographic information, and travel patterns, are identified and their impacts on toll road usage are quantified. The results indicate that the BN model performs reasonably well in travelers’ preference classifications for toll road utilization and knowledge extraction. The BN Most Probable Explanation (MPE) measurement, probability inference and variable influence analysis results illustrate travelers using highway advisory radio and internet as their primary mode of receiving traffic information are more likely to comply with routing recommendations and use toll roads. Traffic information regarding congested roads, road hazard warnings, and accident locations is of great interest to travelers, who tend to acquire such information and use toll roads more frequently. Travel time formation for home-based trips can considerably enhance travelers’ preferences for toll road usage. Female travelers tend to seek traffic information and utilize toll roads more frequently. As expected, the information provided at both pre-trip and en-route stages can positively influence travelers’ preferences for toll road usage. The proposed methodology and research findings advance our previous study and provide insight into travelers’ behavioral tendencies concerning toll road utilization in support of traffic information dissemination.     

广州地铁PIDS紧急信息发布功能优化实施方案

随着地铁线网的不断扩大,PIDS(乘客信息显示系统)紧急信息发布功能已经无法满足时效性等的需求,为此,广州地铁将对该功能进行升级改造,将完全集中式改为集中分布式,以适应未来的发展需要。     

Using survival models to estimate bus travel times and associated uncertainties

Transit agencies often provide travelers with point estimates of bus travel times to downstream stops to improve the perceived reliability of bus transit systems. Prediction models that can estimate both point estimates and the level of uncertainty associated with these estimates (e.g., travel time variance) might help to further improve reliability by tempering user expectations. In this paper, accelerated failure time survival models are proposed to provide such simultaneous predictions. Data from a headway-based bus route serving the Pennsylvania State University-University Park campus were used to estimate bus travel times using the proposed survival model and traditional linear regression frameworks for comparison. Overall, the accuracy of point estimates from the two approaches, measured using the root-mean-squared errors (RMSEs) and mean absolute errors (MAEs), was similar. This suggests that both methods predict travel times equally well. However, the survival models were found to more accurately describe the uncertainty associated with the predictions. Furthermore, survival model estimates were found to have smaller uncertainties on average, especially when predicted travel times were small. Tests for transferability over time suggested that the models did not over-fit the dataset and validated the predictive ability of models established with historical data. Overall, the survival model approach appears to be a promising method to predict both expected bus travel times and the uncertainty associated with these travel times.     

Measuring the success of reducing emissions using an on-board eco-driving feedback tool

This paper reports the findings of an eco-driving trial that was designed enable users to make pre-trip and on-route decisions when driving as to the optimal route to take. The basis of this paper will be to estimate how efficiently drivers are performing in relation to fuel consumption per kilometres (km). The analysis uses details on the vehicle specification, in terms of fuel efficiency, and relates this to the distance travelled to provide the user with information on the efficiency per km travelled. Eco-driving involves the training of individuals to change their driving patterns and to adapt to driving conditions. The results of the study show that eco-driving feedback is a powerful tool and how it can be used to reduce emissions.