The impacts of changing flight demands and throughput performance on airport delays through the Great Recession

Several significant events between 2007 and 2009 impacted flight demands and the abilities of the three major New York area airports to handle demand. This paper assesses the results of applying a probabilistic simulation method – which isolates the individual contributions of changes in flight demand and changes in airport throughput performance to changes in flight delays – to diagnose how these different events may have caused operational changes at these airports, and in turn, how the results may be used to inform policies for appropriate countermeasures. The analysis revealed two key observations. Firstly, certain patterns in throughput performance shifts caused the most significant delays, and were more likely to have been caused by controller staffing issues rather than caps. Secondly, relatively constant average delays from one year to the next may result from significant demand drops accompanied by large throughput performance degradations at an airport. This suggests that not only operational limitations on capacity encourage airlines to reduce schedules, but that changed demands can also impact throughput performance. Overall, the analysis indicates that caps may not have provided their fully intended delay benefits. Although they successfully reduced overall flight demands at LGA and JFK, they also directly limited throughput performance at critical times, in turn limiting delay benefits. In addition, demands at the busiest times of the day appear to be relatively inelastic to these operational limitations, insofar as demand profiles at EWR and JFK remained “peaky” in 2008 and 2009. Also, the recession was largely responsible for reducing demands at the airports in 2009, but the delay benefits of this were dampened by a corresponding throughput performance degradation. Based on the above observations, a more direct demand management policy combined with policies that focus on maintaining high staffing capabilities at critical times of the day may be considered, to reduce the likelihood of major queue formation on days that do experience sustained demands. The results also suggest that a more flexible caps system, particularly during times of heavy queues, could be explored. Although airport practitioners have keen understandings of how their airports operate, without the support of quantitative analysis tools, it can be more difficult to argue the need for appropriate countermeasures. An analysis such as the one presented here can provide the detailed quantitative substantiation required to build cases for these targeted policy directives and infrastructure investments.     

Towards a generic benchmarking platform for origin–destination flows estimation/updating algorithms: Design,demonstration and validation

Estimation/updating of Origin–Destination (OD) flows and other traffic state parameters is a classical, widely adopted procedure in transport engineering, both in off-line and in on-line contexts. Notwithstanding numerous approaches proposed in the literature, there is still room for considerable improvements, also leveraging the unprecedented opportunity offered by information and communication technologies and big data. A key issue relates to the unobservability of OD flows in real networks – except from closed highway systems – thus leading to inherent difficulties in measuring performance of OD flows estimation/updating methods and algorithms. Starting from these premises, the paper proposes a common evaluation and benchmarking framework, providing a synthetic test bed, which enables implementation and comparison of OD estimation/updating algorithms and methodologies under “standardized” conditions. The framework, implemented in a platform available to interested parties upon request, has been flexibly designed and allows comparing a variety of approaches under various settings and conditions. Specifically, the structure and the key features of the framework are presented, along with a detailed experimental design for the application of different dynamic OD flow estimation algorithms. By way of example, applications to both off-line/planning and on-line algorithms are presented, together with a demonstration of the extensibility of the presented framework to accommodate additional data sources.     

Optimization models for differentiating quality of service levels in probabilistic network capacity design problems

This paper develops various chance-constrained models for optimizing the probabilistic network design problem (PNDP), where we differentiate the quality of service (QoS) and measure the related network performance under uncertain demand. The upper level problem of PNDP designs continuous/discrete link capacities shared by multi-commodity flows, and the lower level problem differentiates the corresponding QoS for demand satisfaction, to prioritize customers and/or commodities. We consider PNDP variants that have either fixed flows (formulated at the upper level) or recourse flows (at the lower level) according to different applications. We transform each probabilistic model into a mixed-integer program, and derive polynomial-time algorithms for special cases with single-row chance constraints. The paper formulates benchmark stochastic programming models by either enforcing to meet all demand or penalizing unmet demand via a linear penalty function. We compare different models and approaches by testing randomly generated network instances and an instance built on the Sioux–Falls network. Numerical results demonstrate the computational efficacy of the solution approaches and derive managerial insights.     

城市交通能耗区的识别及等级划分方法研究

随着社会经济的发展，机动车保有量急剧增长，城市化过程中交通拥堵问题日趋严重，交通能源消耗加剧。为了降低由此带来的损失，需要及时探明路网中交通效率低、能耗高的区域，并采取有效的交通管理措施。通过研究交通状态与能耗的关系，进行相应的交通参数分析，建立能耗区识别及等级划分模型，计算得到3个等级能耗区的界定阈值分别为0．411和0．678。     

Implementation of interactive transit information kiosks at New York City transit facilities: Analysis of user utilization and lessons learned

Transit Traveler Information Systems (TTIS) comprise a wide range of technologies that transit agencies use to provide reliable and timely transit-related information to customers. The touch-screen interactive information kiosk is an example of these emerging TTIS technologies. This paper examines the implementation of interactive touch-screen information kiosks, known as “On the Go!” Touch-Screen Travel Stations, at Metropolitan Transportation Authority-New York City Transit (MTA-NYCT) facilities in 2011. It analyzes data from passenger intercept surveys, from the kiosks’ built-in application usage logs and from field observations to understand actual passenger utilization of the kiosks and to assess the implications for transit agencies. The field observations also made it possible to obtain a profile of kiosk users, which sheds light on the concept of the “digital divide.” The findings, presented as lessons learned, can help agencies elsewhere develop guidelines and effective strategies for implementing similar interactive transit information systems.     

Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.     

A critical review of container security operations

Containers, which permit fast and safe handling between modal systems, are the main equipment used in intermodal transport. Unfortunately, enhancement of the efficiency and velocity of container operations has created a breach in traditional security, also known as container security. This paper presents a critical literature review of container security operations. We aim to identify current trends and future research directions in container security. We propose a classification framework based on the following elements: presenting the container security perspective, identifying threats, evaluating container security, balancing costs/benefits and the degree of security, balancing time savings/reduction and the degree of security, and securing containerized transportation processes. We discuss the current studies of these problems, the methodologies adopted and important insights into container security.     

融合可持续理念的交通规划方案比选方法——以亚特兰大大都市区为例

越来越多的机构开始为交通系统的可持续发展定义,并试图将这一概念融入区域交通规划过程.然而,只有极少数的区域规划机构意识到了交通系统和土地利用变化给经济、环境和社会生活质量(这三者通常被认为是可持续交通系统的三个基本方面)带来的广泛影响.首先,论述了使用多个可持续发展指标的多准则决策方法,并应用其评估亚特兰大大都市区的三...