Bush-based sensitivity analysis for approximating subnetwork diversion

Subnetwork analysis is often used in traffic assignment problems to reduce the size of the network being analyzed, with a corresponding decrease in computation time. This is particularly important in network design, second-best pricing, or other bilevel problems in which many equilibrium runs must be solved as a subproblem to a master optimization program. A fixed trip table based on an equilibrium path flow solution is often used, but this ignores important attraction and diversion effects as drivers (globally) change routes in response to (local) subnetwork changes. This paper presents an approach for replacing a regional network with a smaller one, containing all of the subnetwork, and zones. Artificial arcs are created to represent “all paths” between each origin and subnetwork boundary node, under the assumption that the set of equilibrium routes does not change. The primary contribution of the paper is a procedure for estimating a cost function on these artificial arcs, using derivatives of the equilibrium travel times between the end nodes to create a Taylor series. A bush-based representation allows rapid calculation of these derivatives. Two methods for calculating these derivatives are presented, one based on network transformations and resembling techniques used in the analysis of resistive circuits, and another based on iterated solution of a nested set of linear equations. These methods are applied to two networks, one small and artificial, and the other a regional network representing the Austin, Texas metropolitan area. These demonstrations show substantial improvement in accuracy as compared to using a fixed table, and demonstrate the efficiency of the proposed approach.     

Recursive estimation of average vehicle time headway using single inductive loop detector data

Vehicle time headway is an important traffic parameter. It affects roadway safety, capacity, and level of service. Single inductive loop detectors are widely deployed in road networks, supplying a wealth of information on the current status of traffic flow. In this paper, we perform Bayesian analysis to online estimate average vehicle time headway using the data collected from a single inductive loop detector. We consider three different scenarios, i.e. light, congested, and disturbed traffic conditions, and have developed a set of unified recursive estimation equations that can be applied to all three scenarios. The computational overhead of updating the estimate is kept to a minimum. The developed recursive method provides an efficient way for the online monitoring of roadway safety and level of service. The method is illustrated using a simulation study and real traffic data.     

A model for the visualization and analysis of elevator traffic

ABSTRACT

Analysis of elevator traffic in high rise buildings is critical to the performance evaluation of elevator group control systems (EGCS). Elevator dispatching methods or parking algorithms in an EGCS can be designed or modified according to analyses of traffic flow. However, interpretation of traffic flow based solely on numerical data may not be explicit and transparent for EGCS experts as well as for other non-expert building administration. In this study, we present a model for visualization and analysis of elevator traffic. First, we present an alternative approach for traffic analysis which we call route visualization. In the proposed approach, we initially decompose elevator traffic into its component parts and investigate each component independently. Then, using superposition of components we obtain a reconstructed model of overall traffic. This modeling approach provides component-based traffic analysis and representation of routes with intensities through data visualization. In the second part we introduce a multi-dimensional analysis of time parameters in ECGS. This approach provides a comparative analysis of several control algorithms such as dispatch or park algorithms for different combinations of traffic components.     

Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

Prediction of travel time variability for cost-benefit analysis

Unreliable travel times cause substantial costs to travelers. Nevertheless, they are often not taken into account in cost-benefit analyses (CBA), or only in very rough ways. This paper aims at providing simple rules to predict variability, based on travel time data from Dutch highways. Two different concepts of travel time variability are used, which differ in their assumptions on information availability to drivers. The first measure is based on the assumption that, for a given road link and given time of day, the expected travel time is constant across all working days (rough information: RI). In the second case, expected travel times are assumed to reflect day-specific factors such as weather conditions or weekdays (fine information: FI). For both definitions of variability, we find that the mean travel time is a good predictor. On average, longer delays are associated with higher variability. However, the derivative of variability with respect to delays is decreasing in delays. It can be shown that this result relates to differences in the relative shares of observed traffic ‘regimes’ (free-flow, congested, hyper-congested) in the mean delay. For most CBAs, no information on the relative shares of the traffic regimes is available. A non-linear model based on mean travel times can then be used as an approximation.     

往复式压缩机气阀密封面失效分析

气阀是压缩机中发生故障最频繁的部件,故障会直接导致机组排气压比失调、排温高等现象,很大程度上影响企业安全生产及设备的使用寿命.文中对压缩机气阀结构及其故障特征进行了简要阐述,并通过实例分析气阀的故障特征,结合HYSYS计算出工艺气压缩过程中的各组分相图,分析了压缩工艺中气带液的产生过程,总结概括了压缩机气阀密封面失效的...     

静态爆破法在深圳地铁施工中的应用

静态爆破是近年来发展起来的一种新型爆破施工技术,它可在无震动、无飞石,无噪音、无污染的条件下破碎或切割岩石或混凝土构筑物。深圳地铁2号线东延线土建工程安托山站—侨香站区间矿山法施工竖井系选用此工法在2 500 mm×3 000 mm雨水箱涵附近成功地进行了中、微风化花岗岩开挖施工,确保了雨水箱涵的安全性。     

Exploring airline passengers’ willingness to pay for carbon offsets

This study examines airline passengers’ willingness to pay for carbon-offsets. Using the contingent valuation method of double-bounded dichotomous choice format and a survey of over 1000 Taiwanese passengers flying to countries in Asia, Europe, North America, and Oceania to gauge their willingness-to-pay for airline carbon-offsets. The results suggest that despite the trip characteristics and personal background, air travel passengers’ knowledge and perceptions of the carbon-offset scheme also greatly influence the stated willingness to pay.     

百色低碳物流发展浅析

文章阐述了百色发展低碳物流的必要性,分析了百色低碳物流发展所面临的问题,提出了针对性的低碳物流发展思路及建议。     

三岸邕江特大桥悬臂拼装钢桁拱施工监控方法

文章结合三岸邕江特大桥工程实例,对比分析了悬臂拼装钢桁拱的施工监控特点,阐述了悬臂拼装钢桁拱施工监控的主要内容及组织实施流程。