A New Wireless Packet Scheduling Algorithm Based on EDF and Its Application in Multi-bottleneck Networks

Most of current wireless packet scheduling algorithms aim at resource allocation as fairly as possible or maximizing throughput. This paper proposed a new packet scheduling algorithm that aims at satisfying delay requirement and is the improvement of earliest due first (EDF) algorithm in wired networks. The main idea is to classify the packets based on their delay bound, scheduling the most "urgent" class of user and the users that have the best channel condition with higher priority. This algorithm can easily integrate with common buffer management algorithms, when buffer management algorithm cannot accept new arrival packets, try to modify scheduling policy. Packet scheduling algorithms in multiple bottleneck wireless networks were also discussed. A new variable multi-hop factor was defined to estimate the congestion situation (including channel condition) of future hops. Multi-hop factor can be integrated into packet scheduling algorithms as assistant and supplement to improve its performance in multi-bottleneck wireless networks.     

Train rescheduling model with train delay and passenger impatience time in urban subway network

This paper considers the train rescheduling problem with train delay in urban subway network. With the objective of minimizing the negative effect of train delay to passengers, which is quantified with a weighted combination of travel time cost and the cost of giving up the planned trips, train rescheduling model is proposed to jointly synchronize both train delay operation constraints and passenger behavior choices. Space–time network is proposed to describe passenger schedule‐based path choices and obtain the shortest travel times. Impatience time is defined to describe the intolerance of passengers to train delay. By comparing the increased travel time due to train delay with the passenger impatience time, a binary variable is defined to represent whether the passenger will give up their planned trips or not. The proposed train rescheduling model is implemented using genetic algorithm, and the model effectiveness is further examined through numerical experiments of real‐world urban subway train timetabling test. Duration effects of the train delay to the optimization results are analyzed. Copyright © 2017 John Wiley & Sons, Ltd.     

A methodology for identifying similar days in air traffic flow management initiative planning

This article describes a methodology for selecting days that are comparable in terms of the conditions faced during air traffic flow management initiative planning. This methodology includes the use of specific data sources, specific features of calendar days defined using these data sources, and the application of a specific form of classification and then cluster analysis. The application of this methodology will produce results that enable historical analysis of the use of initiatives and evaluation of the relative success of different courses of action. Several challenges are overcome here including the need to identify the appropriate machine learning algorithms to apply, to quantify the differences between calendar days, to select features describing days, to obtain appropriate raw data, and to evaluate results in a meaningful way. These challenges are overcome via a review of relevant literature, the identification and trial of several useful models and data sets, and careful application of methods. For example, the cluster analysis that ultimately selects sets of similar days uses a distance metric based on variable importance measures from a separate classification model of observed initiatives. The methodology defined here is applied to the New York area, although it could be applied by other researchers to other areas.     

基于机动车比功率的单点信号配时优化模型

为减少车辆延误和交通排放,基于机动车比功率提出信号交叉口红、绿灯期间污染物排放因子的标定方法.根据运筹学和交通流理论,以车辆延误和排放最小为目标建立单点交叉口信号配时优化模型.考虑小汽车尾气中的CO、HC和NOx三种污染物,利用 VISSIM 软件设计交通仿真实验,使用MATLAB软件编制参数标定和模型求解算法,根据车辆行驶状况数据标定每条车道组每种污染物的两类排放因子,并验证双目标信号配时优化模型.结果表明,与仅降低延误相比,双目标优化模型所获最优信号配时方案能使车均延误降低19%、交通排放减少11%.研究成果能有效减少交叉口延误和排放,为建立考虑交通排放的干道信号配时优化模型奠定理论基础.     

信号联动修正参数计算方法分析

为研究交通信号的自适应控制方法,需要对交叉口延误进行定量的分析与计算,而HCM2000推荐的延误计算模型对于自适应控制的信号交叉口的延误计算有不错的适用性。在此模型中,信号联动修正参数PF能较好的修正由于交叉口进行自适应控制而产生的延误变化。由于HCM2000给出的PF计算方法比较繁杂,计算方法的简化成为一个很好的研究切入点。     

重庆城市道路交叉口进口道通行能力调查研究

城市道路交叉口的通行能力是城市交通规划管理的基础参数。山地城市交叉口通行能力受多种因素影响,与平原区交叉口通行能力差别较大。通过分析交叉口通行能力的影响因素,选取具有代表性的交叉口,对其几何特征、交通特征进行观测,分析计算车头时距和启动延误数据,得到交叉口进口道的可能通行能力,发现山地城市交叉口一条进口道的可能通行能力比普通地区交叉口通行能力低200～400 PCU。     

世界银行贷款项目“卫津路拓宽工程”的经济效益计算

本市以天津城市主干道卫津路拓宽改造工程为例，论述城市道路经济效益计算方法。按全天高峰小时、非高峰小时，分别计算机动车和非机动车的运营成本、时间价值及事故费用，采用有、无项目对比法．进行经济效益计算。经济效益中以车辆行程时间延误与路口时间延误的节约作为主要效益。     

Auto-ignition and micro-explosion behaviors of droplet arrays of water-in-fuel emulsion

The characteristics of auto-ignition and micro-explosion behaviors of one-dimensional arrays of fuel droplets suspended in a chamber with high surrounding temperature were investigated experimentally with various droplet spacings, numbers of droplet and surrounding temperatures. The fuels used were pure n-decane and emulsified n-decane with varied water contents ranging from 10 to 30%. All experiments were performed under atmospheric conditions with high surrounding temperatures. An imaging technique using a high-speed camera was adopted to measure ignition delay, flame lifetime, and flame spread speed. The camera was also used to observe micro-explosion behaviors. As the droplet array spacing increased, the ignition delay also increased, regardless of water content. However, the lifetime of the droplet array decreased as the droplet spacing increased. The micro-explosion starting time remained unchanged regardless of the number of the droplets or the droplet spacing; however, it tended to be delayed slightly as the water percentage and droplet spacing increased.     

航班延误恢复调度的混合粒子群算法

为了优化航班延误恢复调度, 考虑了航班延误的经济效益、社会影响和经济损失构成, 定义了航线影响因子, 构建了一种新的航班延误恢复调度模型, 将局部搜索方法引入到粒子群算法中, 提出了求解航班延误恢复调度问题的混合粒子群算法。计算结果表明: 与先来先服务调度方法相比, 混合粒子群算法可以减少航班延误损失4.2%, 与基本粒子群算法和进化策略算法相比, 混合粒子群算法平均可减少航班延误损失2.0%, 随着航班延误恢复规模的增大, 算法优势会更明显。