Interactive image-based information visualization for aircraft trajectory analysis

Objectives: The objective of the presented work is to present novel methods for big data exploration in the Air Traffic Control (ATC) domain. Data is formed by sets of airplane trajectories, or trails, which in turn records the positions of an aircraft in a given airspace at several time instants, and additional information such as flight height, speed, fuel consumption, and metadata (e.g. flight ID). Analyzing and understanding this time-dependent data poses several non-trivial challenges to information visualization.Materials and methods: To address this Big Data challenge, we present a set of novel methods to analyze aircraft trajectories with interactive image-based information visualization techniques.As a result, we address the scalability challenges in terms of data manipulation and open questions by presenting a set of related visual analysis methods that focus on decision-support in the ATC domain. All methods use image-based techniques, in order to outline the advantages of such techniques in our application context, and illustrated by means of use-cases from the ATC domain.Results: For each considered use-case, we outline the type of questions posed by domain experts, data involved in addressing these questions, and describe the specific image-based techniques we used to address these questions. Further, for each of the proposed techniques, we describe the visual representation and interaction mechanisms that have been used to address the above-mentioned goals. We illustrate these use-cases with real-life datasets from the ATC domain, and show how our techniques can help end-users in the ATC domain discover new insights, and solve problems, involving the presented datasets.     

基于IDM的需求扰动供应链协调契约研究

针对具有需求扰动风险的供应链协调问题，基于利益驱动机制，设计出一种新的保险契约模式，建立相应的供应链模型并求解分析。结果表明：均匀分布市场需求下赔偿上限应足够大，且契约参数满足相关条件时供应链可以达到完美协调。最后通过数值分析了赔偿参数对订货量和保费的影响。     

A review of the impact of parking policy measures on travel demand

This paper reviews the empirical evidence relating to the impact of parking policy measures on the demand for parking and for travel. Disaggregate modal choice models, disaggregate parking location models and site‐specific studies of parking behaviour are examined. With regard to modal choice models, it is concluded that few studies deal adequately with parking factors, but that there is some support for the view that parking policy measures are a relatively important influence on modal choice. When parking location models are examined parking policy variables are shown to have a substantial impact on choice of parking location. With regard to site‐specific studies, the paper concludes that there is a great variation in the parking price elasticities quoted, which reflects partly the methodological problems associated with such studies. Suggestions to improve model specification are made.     

喀什经济开发区综合交通规划中交通需求预测

喀什地区位于中国的西大门，与5个国家接壤，有6个国家一类口岸对外开放，区域优势明显．对喀什经济开发区交通需求的科学研究是促进该研究区域交通运输事业规范而高速发展的关键．本文采取时间序列预测法、弹性系数法、综合评价法等方法，系统全面地对该区域交通需求预测进行了分析，为该区域综合交通规划与建设奠定了基础．     

负离子发生器车内微颗粒净化效率研究

由于汽车的普及,车内的空气质量引发消费者越来越多的关注。糟糕的车内空气质量会增大人们罹患某种特定疾病的概率,因此控制与减少车内空气污染成为汽车生产设计商所追求的目标。微颗粒污染物,即PM2.5是车内空气污染物的重要来源之一。负离子因能有效沉降空气中的微颗粒,成为车内快速去除微颗粒污染的重要手段。在文章中,我们通过在车内进行微颗粒沉降实验,记录微颗粒物浓度在负离子仪以及车内空调内/外循环净化模式下的变化,并通过SPSS与MATLAB对污染物浓度进行数学建模分析。结果表明:单独使用负离子仪器并无法有效降低车内空气的颗粒浓度,而必须配合车内空气循环系统。在负离子作用下,结合车内空气循环系统,微颗粒浓度迅速下降,下降速度与空气交换速度和微颗粒在空气中的迁移速度相关。     

Exploiting floating car data for time-dependent Origin–Destination matrices estimation

The study evaluates the added value generated by estimating dynamic demand matrices by information gathered from Floating Car Data (FCD).

Firstly, adopting a large dataset of FCD collected in Rome, Italy, during May 2010, all the monitored trips on a specific district of the city (Eur district) have been collected and analysed in terms of (i) spatial and temporal distribution; (ii) actual route choices and travel times. The data analysis showed that demand data from FCD are usually not suitable to retrieve directly demand matrices, due to a strong dependence of this information from the penetration rate of the monitoring device. Instead, origin–destination travel times and route choice probabilities from FCD are a much more reliable and powerful information with respect to FCD origin–destination flows, since they represent the traffic conditions and behaviors that vehicles experiment along the path.

Thus, several synthetic experiments have been conducted adopting both travel times and route choice probabilities as additional information, with respect to standard link measurements, in the dynamic demand estimation problem. Results demonstrated the strength and robustness associated to these network based data, while link measurements alone are not able to define the real traffic pattern. Adopting both the information of origin–destination travel times and route choice probabilities during the demand estimation process, the spatial and temporal reliability of the estimated demand matrices consistently increases.     

Bi-objective routing problem with asymmetrical travel time distributions

Recent studies have confirmed that travelers consider travel time reliability in addition to average travel time when making route choice decisions. In this study, we develop a bi-objective routing model that seeks to simultaneously optimize the average travel time and travel time reliability. The semi-standard deviation (SSD) is chosen as the reliability measure because it reflects travelers' concerns over longer travel time better than the commonly used standard deviation. The Pareto-optimal solutions to the bi-objective model are found by using an improved strength Pareto evolutionary algorithm. Tests on a real-world urban network with field measured travel time data have demonstrated good performance of the algorithm in the aspects, such as computational efficiency, quick convergence, and closeness to the global Pareto-optimal. Overall, the bi-objective routing model generates reasonable path recommendations. The SSD-based model is sensitive to the asymmetry of travel time distribution and tends to avoid paths with excessively long delays. This would be particularly helpful to those users placing high values on travel time reliability.     

浙东地区公路隧道调光参数影响因素实测分析与调光控制探讨

为掌握公路隧道调光参数的变化特征,更好地解决调光控制与隧道照明需求匹配的问题,采用改进的环境简图法结合环形线圈车检器同步获取浙东沿海丘陵地区6条公路隧道的长序列洞外亮度L20(S)和交通流数据。实测结果表明： 1）对浙东地区,公路隧道春、夏、秋、冬季的L20(S)峰值比例约为0.95∶1∶0.95∶0.85,晴天、云天、阴天、重阴天的L20(S)比例约为1∶0.6∶0.18∶0.11; 2）L20(S)是影响浙东地区公路隧道照明需求的主要因素,其对调光控制节能的贡献超过95%,交通流对隧道照明需求的影响较为有限; 3）隧道越短,调光控制所取得的节能效果越显著,短隧道采用无级调光,照明能耗可降低50%以上。     

Experimental and numerical investigations on laser-welded corrugated-core sandwich panels subjected to air blast loading

Experimental investigations on the laser-welded triangular corrugated core sandwich panels and equivalent solid plates subjected to air blast loading are presented. The experiments were conducted in an explosion tank considering three levels of blast loading. Results show that the maximum deflection, core web buckling and core compaction increased as the decrease of stand-off distance. Back face deflections of sandwich panels were found to be nearly half that of equivalent solid plates at the stand-off distances of 100 mm and 150 mm. At the closest stand-off distance of 50 mm, the panel was found to fracture and fail catastrophically. Autodyn-based numerical simulations were conducted to investigate the dynamic response of sandwich panels. A good agreement was observed between the numerical calculations and experimental results. The model captured most of the deformation/failure modes of panels. Finally, the effects of face sheet thickness and core web thickness on the dynamic response of sandwich panel were discussed.     

救援时间限制下高速公路网应急设施点选址模型

应急资源布局问题是高速公路应急管理的关键。通过建立数学模型,提出一种优化高速公路网中应急设施点布局方法。首先,通过分析高速公路网中应急需求的布局特点,依据事故发生概率、事故影响范围和路段平均车流量确定在某个交通事故情形下需求点的应急需求。然后,基于需求分析建立应急设施点选址模型。通过救援时间限制确定设施点的覆盖条件,选择救援时间短、物资供给能力强的待选点建立设施点。最后,采用基于拉格朗日松弛的启发式算法对模型进行求解。通过计算实例验证,该布局方法针对高速公路网的应急需求,保障了应急事件救援时间,为高速应急设施点布局提供了新思路,可适用性强。