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。     

基于广西旅游业的道路客运发展探析

文章针对广西道路旅客运输的现状及广西道路客运企业发展旅游业的优越条件,以＂运游结合＂为切入点,介绍以快捷优质的客运服务带动＂慢旅游＂道路客运企业发展旅游业的新模式,对采取＂运游结合＂经营模式,提高服务质量,发展＂慢旅游＂提出了相关的建议。     

Comparing smart scheme effects for congested highways

A high level objective for many international governments and local operators is that highways should be managed in a way that is sustainable in terms of a Low Carbon Energy future. Recent initiatives such as the Strategic Transport Technology Plan and the policy and legal framework promoted by the European Commissions’ Intelligent Transport System (ITS) Directive and ITS Action Plan may assist with this objective. However, many levels of complexity are inherent within the (ITS) schemes that are now part of highway management, due to the linkage of various technological components to complex systems and services. Maintaining efficient, sustainable co-operative performance is therefore a major task, with inconsistencies between product suppliers, network managers and operators. As a result, it is of considerable interest to the highway operators and high level policy makers to be able to assess the performance of individual ITS schemes and furthermore, to be able to compare performance between ITS schemes. In this paper, an illustration is provided of a methodology that can be used to assess the performance of ITS schemes according to a set of sustainability criteria. A case study is introduced which compares the performance of anticipated Active Traffic Management (ATM) schemes for what the road network operator (Highways England) perceive to be the four most congested highways in England (in terms of annual average daily traffic flows). Appropriate action can then be taken to improve the energy and sustainable management of Information Communication Technology (ICT) and transport systems for the benefit of a smarter, sustainable and efficient future.     

Generation and recovery of airborne delays in air transport

The analysis of the causes behind the appearance and propagation of delays is one of the major topics inside Air Transport Management research. Existing research focuses by and large on Air Traffic Flow Management regulations and reactionary delays; less attention has been devoted to the study of the mechanisms governing the generation and absorption of delays while airborne, in spite of their important economical and environmental consequences. Here we present a methodology to detect delay-generating events, based on the comparison of planned and real trajectories; these events are then used to characterise several aspects of the dynamics of the system, e.g. its resilience. We apply this methodology to a historical data set of flights crossing the European airspace during 2011, and observe an overall resilient system, able to absorb as much delays as it generates; yet resilience is not constant, but strongly depends on the phase of the flight, and shows high spatial and temporal heterogeneities. We anticipate the proposed methodology to open new doors for the development of a better systemic performance, by enabling the characterisation and understanding of this fundamental type of delay.     

公交企业在公交都市建设中的地位与任务

建设公交都市已成为大都市缓解城市交通拥堵的发展方向。本文在公交都市建设实践及研究成果的基础上，分析了常规公交在公交都市中的地位及公交企业的使命，提出了公交企业在公交都市建设中的任务体系，对公交企业的经营管理有一定的指导作用。     

城市综合公共交通体系及其体系设计研究

随着我国城市化进程的加快，城市交通问题日益突出，大力发展公共交通逐渐成为公认的解决城市交通拥堵的有效途径之一。为了从城市整体层面提高公共交通服务能力和水平，提出城市综合公共交通体系的概念，并探讨该体系的若干设计内容。     

A ‘sustainability window’ of urban form

With global environmental change and the rise of global megacities, environmental and social externalities of urban systems, and especially of urban form, become increasingly prevalent. The question of optimal urban form has been debated and investigated by different disciplines in numerous contexts, including those of transport costs, land consumption and congestion. Here we elucidate theoretically how urban form and the urban transport system systematically modifies sustainability concerns, such as greenhouse gas emissions, local air pollution and congestion. We illustrate our analytical considerations with empirical analysis. Denser urban form would almost unambiguously mitigate climate change, but it would also lead to undesired effects, such as a higher proportion of urban dwellers affected by air pollution. Our study presents a ‘sustainability window’ by highlighting trade-offs between these sustainability concerns as a function of urban form. Only a combination of transportation policies, infrastructure investments and progressive public finance enables the development of cities that perform well in several sustainability dimensions. We estimate that a residential population density between 50 and 150 persons/ha and a modal share of environmental modes above at least 50% corresponds to the sustainability window of urban form. The parameters of the sustainability window of urban form is subject to policy changes and technological progress.     

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.