Air traffic predictability framework – Development,performance evaluation and application

The performance of the Air Traffic Flow & Capacity Management (ATFCM) function relies fundamentally on the accuracy of air traffic predictability. Characterising this accuracy and assessing the potential benefits of increased accuracy is fundamental to enhance the performance of the Air Traffic Management (ATM) system and identifying areas that require improvement. This paper develops a framework to assess air traffic predictability. It validates the proposed framework with real operational data and applies it to the Maastricht Upper Area Control centre. The paper develops a methodology to assess the benefits of the deployment of enhanced predictability including capacity, resulting from improved operational concepts such as Airport-Collaborative Decision Making (A-CDM).     

关于我国铁路创建学习型组织的总体思考

阐述铁路创建学习型组织的重要意义和我国铁路学习型组织创建现状,结合铁路创建学习型组织的总体目标和具体目标,提出我国铁路创建学习型组织的基本原则和主要途径。     

The spatial and temporal variation in passenger service rate and its impact on train dwell time: A time-series clustering approach using dynamic time warping

This study aims to improve the understanding of the underlying mechanism of passenger boarding and alighting processes, as well as its potential influence on train dwell time and train operation. Empirical data collected from one of busiest metro stations in Seoul, Korea, demonstrates the spatial and temporal variation in the passenger service rate, as a result of interference between boarding, alighting, and standing passengers. This study postulates that the level of interference can be associated with the train car occupancy and the proximity of train door to entry points, as waiting passengers tend to cluster near the platform entries. A unique temporal service rate curve is derived from each door location. We introduce Dynamic Time Warping for similarity assessment and clustering. It revealed four groups of train doors showing distinct shapes of curve from each platform. The first cluster includes the train doors located closest to the platform entry points where the initial service rate is drastically impeded by severe inference among passengers. The level of interference gradually diminishes as the door is located farther away from the entry points, but the overall service rate decreases as well. A passenger service time model is derived to include the cluster variable. To test its significance, the prediction capability of the model is presented with and without the cluster variable. The results of this study may be used to guide waiting passengers along the platform to minimize interference and to avoid serious disruption during passenger service time.     

Enhancing art gallery visitors’ learning experience using wearable augmented reality: generic learning outcomes perspective

The potential of Information and Communication Technology-enhanced visitor learning experience is increasing with the advancement of new and emerging technologies in art gallery settings. However, studies on the visitor learning experience using wearable devices, and in particular, those investigating the effects of wearable augmented reality on the learning experience within cultural heritage tourism attractions are limited. Using the generic learning outcomes framework, this study aims to assess how the wearable augmented reality application enhances visitor’s learning experiences. Forty-four volunteers who were visiting an art gallery were divided into two groups, an experimental group and a control group. Following their visit to the gallery, the volunteers, who had and had not used wearable computing equipment, were interviewed, and the data were analysed using thematic analysis. Findings revealed that the wearable augmented reality application helps visitors to see connections between paintings and personalize their learning experience. However, there are some drawbacks such as lack of visitor–visitor engagement and the social acceptability.     

世界铁路工业市场的未来发展

按地域和产品类别,介绍世界铁路工业市场现状,并对到2015年世界铁路工业市场发展趋势进行预测。     

客运量的合成预测与概率模型

为适应交通运输业的发展,将运输需求的合成预测方法引入铁路客运量预测中,结合铁路客运量具有双峰形态分布随机变量的特点,对预测概率模型进行改进,得出“十五”末期铁路客运量的预测值,以及铁路月度客运量频率散点图和拟合概率曲线,为铁路运输的宏观指导、组织协调和生产、建设提供依据。     

Analysis of user satisfaction to promote public transportation: A pattern-recognition approach focusing on out-of-vehicle time

Public transportation has been regarded as one of the most sustainable forms of transport, because of which local governments have put efforts in increasing the mode share of public transportation. Recently, not only level of service but also user satisfaction has been focused on for the assessment of transport policy; however, several points have been overlooked in previous research, such as attribute-based satisfaction, the relationship between level of service and satisfaction, and user expectation. This paper deals with these issues while assuming the heterogeneity of satisfaction, which is an indicator of perception. Out-of-vehicle times, particularly headway and access time, were selected in the analysis because they can affect travel behavior of current and potential public transportation customers. In this analysis, pattern-recognition models were applied, and public transportation users were segmented in terms of perception. The results suggest several notable recommendations for public transport policies and investigations.