An experimental approach to measuring the effects of a controllerconflict probe in a free routing environment

The unstructured traffic environment that is gradually evolving in the National Airspace System may necessitate decision aiding tools to help controllers manage aircraft traffic efficiently and within acceptable safety and workload levels. An experiment was designed to assess the effect of conflict detection and trial planning resolution aids and traffic conditions on the performance of controllers and the efficiency of flight. Twelve controllers participated in a high-fidelity simulation study in the Indianapolis Center dynamic simulation facility using the user request evaluation tool (URET). Study results indicated that URET clearly improves the acceptability of operations and may enhance safety, particularly in the unstructured environment. In addition, the study findings strongly support a shift toward more strategic air traffic control with conflict probe as well as a significant increase in the contribution of the D controller to the primary sector tasks. Because of study limitations, it was not possible to associate any quantitative estimates of airspace user benefits with the potentially more efficient resolution strategies. The results and experimental approach are discussed in terms of their contribution to measurement methods and issues in the evolutionary progression toward a free flight-based air traffic system     

A study of aircraft taxi performance for enhancing airport surfacetraffic control

In view of the ever-increasing air traffic, much attention in air traffic management research has been given to improving arrival and departure efficiency. As air traffic begins and ends at the airport, the issues of taxi delays and ground incursions are becoming more evident. The paper considers the surface-traffic problem at major airports and envisions a collaborative traffic and aircraft control environment where a surface traffic automation system will help coordinate surface traffic movements. Specifically, the paper studies the performance potential of high-precision taxi toward the realization of such an environment. A state-of-the-art nonlinear control system based on feedback linearization is designed for a detailed B-737 aircraft taxi model. The simulation model with the nonlinear control system is evaluated extensively in a scenario representing the demanding situation of an arrival aircraft crossing an adjacent active runway immediately following its own landing. The evaluation establishes the potential of an automated system to achieve high-precision taxi control, including the ability to comply with taxi clearances with tight time margins. Such a high-precision taxi capability reduces the time margin required for clearing taxiing aircraft to cross active runways, thus increasing the opportunity for issuing such clearances, which in turn reduces the need for aircraft to hold short at the runways to wait for the opportunity for crossing. The results from the analyses provide insight into future aircraft operational capabilities toward the design of the envisioned surface traffic automation system. Moreover, the nonlinear control design serves as a preliminary study for future auto-taxi functional development     

基于网络划分的VANET路由构建及数据传输方法

为提高车载自组网的路由扩展性,提出了一种基于网络划分的车载自组网路由构建及数据传输方法。首先,提出了一种新的车载自组网划分算法来把网络划分为多个子网,随后,搭建和维护各子网中的头尾节点间路由,最后,所有路由的搭建和维护都基于各个子网的头尾节点间路由。该方法将链路失败的影响局限于包含该链路的子网中,并且能够多次复用子网中的路由信息。仿真表明,在网络节点数和路由数目不断增多的情况下,相对于直接在网络中应用相关路由算法,文中方法显著地减小了路由代价,提高了网络性能。仿真结果充分地说明了文中方法的有效性。     

Adaptive routing algorithm for network load balancing

This paper introduces a routing algorithm which distributes the network traffic for each feasible route based on the reinforcement learning scheme. The aim of this algorithm is to reduce the transfer delay caused by congestion of the network. Most routing algorithms based on the reinforcement learning scheme could not avoid forwarding traffic toward the source of data packets. This property creates transfer loops and a lot of packet loss. In particular, the transfer loop may cause change in the order of packets, and also retransmit on the TCP connection. Thus, we employ a method that estimates the lower boundary of the probability for valid route to the destination, and this lower boundary can be used to reject the routes which cause the transfer loop. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Perfor mance of a QoS-based multiple-route ad hoc on-demand distance vector protocol for mobile ad hoc networks

This paper proposes a quality of service based multiple-route ad hoc on-demand distance vector (QoS-MRAODV) routing protocol for achieving and maintaining QoS in mobile ad hoc networks (MANETs). The QoS-MRAODV protocol supports one active QoS-based primary route and several backup routes to provide hot standby redundancy against frequent route failures that are prevalent in MANETs. Results from extensive performance simulation of the QoS-MRAODV protocol demonstrate that it is indeed a viable protocol for achieving and maintaining QoS support in MANETs, providing the additional benefits of fast route discovery time and low routing overhead without a significant increase in end-to-end packet delay.     

基于GIS的配电网规划人工智能方法(二) 遗传算法在配电网初级布线系统中的应用

初级布线是整个配网规划过程的一个重要组成部分。遗传算法就其本质而言是一种用于处理复杂问题的鲁棒性强的启发式随机搜索算法。为了得到经济、高效、低耗的初级布线路径,将遗传算法作为一种路径寻优机制引入初级布线系统。该系统在地理信息系统直观的视图环境中,充分利用设备管理系统数据库所提供的地理图形数据和网络拓扑信息,为配网规划寻找到一条最优的初级布线路径。     

Problem resolution support for free flight operations

The MITRE Corporation's Center for Advanced Aviation System Development (CAASD) has been conducting research into new automation capabilities to support free flight operations. One of these capabilities is a problem resolution function to assist the en route sector controller team in handling the more complex traffic patterns that can result from a less structured free flight environment. This function is termed problem analysis, resolution and ranking (PARR). PARR is envisaged as an enhancement to the user request evaluation tool (URET) free flight phase 1 (FFP1) capability, and has been designated as priority research for the follow-on free flight phase 2 (FFP2) effort. PARR is being developed as a series of incremental enhancements, with the first step focusing on the resolution of aircraft-to-aircraft and aircraft-to-airspace problems. Follow-on enhancements include resolutions for metering and other traffic flow management (TFM) flow initiatives, resolutions for the avoidance of severe weather areas, and the integration into a common en route sector team CHI. A research management plan has been prepared by the Federal Aviation Administration and MITRE/CAASD to support this development process. The paper describes the initial PARR capabilities, along with an extension to incorporate assigned metering time constraints     

基于萤火虫算法的无人机组网多径路由算法

针对无人机自组网节点能量有限、移动快、数据多造成网络 QoS 下降的问题,提出将改进的萤火虫算法融入到多径路由 中形成萤火虫多径路由算法(AOMDV-FMRA)。 首先为减小速度对路径稳定度的影响,在路由发现过程中引入边界评价因子以 适应拓扑变化,再根据路径上节点的负载信息,对反向路由进行选择。 最后将能量评价参数映射到萤火虫算法中对收集到的路 径能量信息进行处理,作为流量分配的依据。 实验结果表明,与 AODV、AOMDV 相比,在节点速度高、网络流量大的环境中,算 法在端到端时延、网络生存时间、投递成功率、路由开销方面,均有良好性能。     

Online Behavior-Robust Feedback Information Routing Strategy for Mass Evacuation

Disaster response to manmade and natural events involves the quick evacuation of the affected population to safer areas. Given the potential for large-scale loss of life and property, there is a need for effective emergency strategies to mitigate the adverse effects of these disasters. Most existing evacuation traffic management strategies focus on increasing network capacity along the evacuation direction such as contraflow lanes, but other information or routing strategies have not been fully explored. Optimal routing strategies can be presented to evacuees as recommended routes. Advising evacuees that take system-optimal routes help balance the distribution of evacuation flows among multiple evacuation routes. However, a critical aspect in evaluating the effectiveness of such strategies is to properly account for the possible evacuation route-choice behavior. This study analyzed the situation in which evacuees are given a set of system-optimal paths; evacuees choose their evacuation routes, following a certain route-choice behavior (rational, panic, etc.). Discussions focus on the extent to which the routing effectiveness can be properly estimated, subject to the route-choice behavior. This paper further proposes a behavior-robust feedback information routing (FIR) strategy to further improve system performance. The FIR is based on the concept of closed-loop control that reacts to the system state and updates the advised routes. The FIR that targets the system-optimal routing strategy has been shown to be effective and robust for real-time evacuation traffic management.     

A Scalable Methodology for Evaluating and Designing Coordinated Air-Traffic Flow Management Strategies Under Uncertainty

As congestion in the United States National Airspace System (NAS) increases, coordination of en route and terminal-area traffic flow management procedures is becoming increasingly necessary to prevent controller workload excesses without imposing excessive delay on aircraft. Here, we address the coordination of flow management procedures in the presence of realistic uncertainties by developing a family of abstractions for implementable flow restrictions (e.g., miles-in-trail restrictions, ground delay programs, and slot-based policies). Using these abstractions, we are able to evaluate the impact of multiple restrictions on generic (uncertain) traffic flows and, hence, to design practical flow management strategies. We use the developed methodology to address several common design problems, including the design of multiple restrictions along a single major traffic stream and the design of multiple flows entering a congested terminal area or sector. For instance, we find that multiple restrictions along a stream can be used to split the backlog resulting from a single restriction and use this observation to develop low-congestion designs. We conclude the discussion by posing a tractable NAS-wide flow management problem using a simple algebraic model for a restriction.      

几种典型Ad hoc路由协议的仿真分析

路由算法是无线自组网的重要组成部分,路由的好坏直接影响网络的性能.文章以无线自组网在电力系统通信中的应用为出发点,研究了DSDV,DSR,AODV和OLSR四种典型的路由协议,采用定性比较和仿真实验的方法,分析了静止节点在不同规模和负载流量场景下,路由协议的分组投递率、时延、吞吐率以及路由控制开销的变化情况,并在此基础上,对4种协议的性能进行了比较和评估,为基于无线自组网的电力系统通信提供了路由选择参考.     

一种电力通信网最大不相交双路由配置方法

针对现有电力通信网路由算法不能为业务分配双路由的问题,提出一种最可靠环路策略下的最大不相交双路由算法(the maximally disjoint routing algorithm under the most reliable loop strategy, MRMLS)。研究了公共通信网中三种类型的双路由算法,考虑了双路由算法可能面临的网络结构,阐述了采用最大不相交双路由算法的必要性。分析了最大不相交双路由的可靠性,并采用最可靠环路策略完成最大不相交双路由的分配工作。改进了原有最大不相交双路由算法,使所提算法充分考虑节点与链路的可靠性。仿真实验将MRMLS与其他两种方法进行对比,验证了MRMLS的可行性与有效性。     

Examination of Multiple Mode/Route-Choice Paradigms Under ATIS

The objective of this paper is to collect and analyze data that can be used to model mode- and different route-choice paradigms using same subjects and same experiment. In this paper, the authors estimated five models to address drivers' diversion, compliance, and route choice. In addition, the effect of advanced traveler information systems (ATIS) on the mode choice is also considered. A travel simulator was used as a dynamic data collection tool. The simulator uses a realistic network, two modes of travel, real historical volumes, and different weather conditions. It provides five different levels of traffic information/advice, one at a time, and collects dynamic mode choices and pretrip (long-term) and en-route (short-term) route choices. The binomial and multinomial generalized extreme equations (BGEE and MGEE) were used to account for the correlation between repeated choices made by the same subject. In addition, MGEE accounts for the correlation between alternatives in multidimensional route-choice models. The modeling results showed that travel time and familiarity with the device that provides the information had significant effects on the first four models. It is shown that developing in-vehicle information devices may lead to a less transit usage in some cases; this indicates a potential drawback of this technology. Expressway users are shown as the most travel-time savers who would divert if they are guided to a less-travel-time alternative. The number of traffic signals on the normal and advised routes affects the diversion from the normal route and compliance with the pretrip advised route. This paper underlines the importance of modeling correlation, if it exists, in mode/route-choice data.     

Stability and performance of intersecting aircraft flows underdecentralized conflict avoidance rules

This paper considers the problem of two intersecting aircraft flows under decentralized conflict resolution rules. Considering aircraft flowing through a fixed control volume, new air traffic control models and scenarios are defined that enable the study of long-term aircraft flow stability. For a class of two intersecting aircraft flows, this paper considers conflict scenarios involving arbitrary encounter angles. It is shown that aircraft flow stability, defined both in terms of safety and performance, is preserved under the decentralized conflict resolution algorithm considered. It is shown that the lateral deviations experienced by aircraft in each flow are bounded     

A self-adaptive key flow routing adjustment algorithm

Congestion may decrease throughput and transfer efficiency of network, and lead to serious degradation of quality of service (QoS) acquired by end users. Present routing adjustment methods against congestion mostly consider single-point congestion. They cannot deal with multi-point congestion. This paper presents a probability-based routing adjustment algorithm, which solves the interference problem when several flows are adjusted simultaneously. While multiple points in the network are being or about to be congested, several key flows are rerouted by this algorithm at the same time to make traffic distribution more reasonable so as to avoid congestion. Meanwhile, the algorithm in this paper confines the path length of key flows to avoid QoS reduction due to overlength of key flows. Simulation shows that this method, compared with present algorithms, maintains better load balance and path length. Therefore it effectively increases the throughput of the network.     

软件定义网络的流量调度算法研究

目前,NOX、FloodLight等SDN控制器均提供了类似于传统路由器OSPF协议的最短路径转发算法,这些算法通过SDN控制器收集全局交换机静态参数从而进行路径计算,但并没有利用SDN系统的优势即获得运行时的动态信息来优化算法性能,在流量过大时传统算法容易导致网络拥堵。对SDN的路由算法进行研究,应用粒子群算法并利用SDN技术的特点对网络的负载均衡问题进行相关的优化。仿真实验表明与ECMP算法相比,提出的算法可以在一定程度提升网络的整体利用率,降低网络的时延和拥塞。     

Heuristic techniques for accelerating hierarchical routing on road networks

The route computation module is one of the most important functional blocks in a dynamic route guidance system. Although various algorithms exist for finding the shortest path, their performance tends to deteriorate as the network size increases. We present an efficient hierarchical routing algorithm that finds a near-optimal route and evaluate it on a large city road network. Solutions provided by the hierarchical routing algorithm are compared with the optimal solutions to analyze and quantify the loss of accuracy. We propose a novel yet simple heuristic to substantially improve the performance of the hierarchical routing algorithm with acceptable loss of accuracy. A network pruning technique has been incorporated into the algorithm to reduce the search space and the correctness of the results is evaluated. The improved hierarchical routing algorithm that incorporates the heuristic techniques has been found to be over 50 times faster than a typical shortest path algorithm.     

Online Learning Solutions for Freeway Travel Time Prediction

Providing travel time information to travelers on available route alternatives in traffic networks is widely believed to yield positive effects on individual drive behavior and (route/departure time) choice behavior, as well as on collective traffic operations in terms of, for example, overall time savings and-if nothing else-on the reliability of travel times. As such, there is an increasing need for fast and reliable online travel time prediction models. Previous research showed that data-driven approaches such as the state-space neural network (SSNN) are reliable and accurate travel time predictors for freeway routes, which can be used to provide predictive travel time information on, for example, variable message sign panels. In an operational context, the adaptivity of such models is a crucial property. Since travel times are available (and, hence, can be measured) for realized trips only, adapting the parameters (weights) of a data-driven travel time prediction model such as the SSNN is particularly challenging. This paper proposes a new extended Kalman filter (EKF) based online-learning approach, i.e., the online-censored EKF method, which can be applied online and offers improvements over a delayed approach in which learning takes place only as realized travel times are available.     

Link travel time prediction for decentralized route guidancearchitectures

A critical problem in decentralized route guidance is to communicate anticipated congestion to individual drivers in such a way that the routes chosen are likely to be consistent with the forecast. We propose a prediction technique for decentralized route guidance architectures to identify time-dependent link travel times which when communicated to drivers leads to time-dependent fastest paths consistent with this forecast. The fixed-point property of the forecast is assured by an iterative process of traffic simulations followed by dynamic route determinations until the routes and hence the resulting dynamic link times become stable. The resulting routes yield an inherently accurate forecast of congestion as well as being user-optimal by construction. A back-dating process is utilized to insure the discovery of a stable routing after a finite and usually small number of iterations, An empirical case study based on the roadway network in Troy, MI is included     

A cross-layer design and ant-colony optimization based load-balancing routing protocol for ad-hoc networks

In order to periodically reassess the status of the alternate path route (APR) set and to improve the efficiency of alternate path construction existing in most current alternate path routing protocols, we present a cross-layer design and ant-colony optimization based load-balancing routing protocol for ad-hoc networks (CALRA) in this paper. In CALRA, the APR set maintained in nodes is aged and reassessed by the inherent mechanism of pheromone evaporation of ant-colony optimization algorithm, and load balance of network is achieved by ant-colony optimization combining with cross-layer synthetic optimization. The efficiency of APR set construction is improved by bidirectional and hop-by-hop routing update during routing discovery and routing maintenance process. Moreover, ants in CALRA deposit simulated pheromones as a function of multiple parameters corresponding to the information collected by each layer of each node visited, such as the distance from their source node, the congestion degree of the visited nodes, the current pheromones the nodes possess, the velocity of the nodes, and so on, and provide the information to the visiting nodes to update their pheromone tables by endowing the different parameters corresponding to different information and different weight values, which provides a new method to improve the congestion problem, the shortcut problem, the convergence rate and the heavy overheads commonly existed in existing ant-based routing protocols for ad-hoc networks. The performance of the algorithm is measured by the packet delivery rate, good-put ratio (routing overhead), and end-to-end delay. Simulation results show that CALRA performs well in decreasing the route overheads, balancing traffic load, as well as increasing the packet delivery rate, etc. Translated from Journal of ACTA Electronica Sinica, 2006, 34(7): 1199–1208 [译自: 电子学报]