中小城市直达公交网络优化

为了在非直达需求均能满足最少换乘的基础上进一步提高公交网络的直达率,建立了以直达率最大化和直达总时间最小化为目标的直达公交网络优化模型。与现有的研究相比,增加了换乘次数最小化约束,并采用具有遗传迭代机制的元启发式算法求解模型。利用Floyd算法求解初始网络最短路径,经线路删减、合并等操作后作为初始公交网络,使得模型具有高质量的初始解;通过space P法建模计算网络总换乘次数,在原有发车频率、最大车辆配备数、线路长度等约束下增加换乘次数最小化约束,采用频率共享规则进行客流分配,并与现有研究结果进行对比。结果表明,对于4条线路的Mandl's Swiss网络,在不考虑发车频率优化时,直达率较现有研究的试验1、2、3分别提高9.7%、8.41%和0.39%。     

Dijkstra算法在公交换乘最短路径中的应用

Dijkstra算法是求加权图中从某一源点到其余各点最短路径的算法,通过对传统的Dijkstra算法进行分析,提出一种改进算法,使其适合应用于求公交换乘最短路径问题。     

基于SPFA算法的公交线路优化模型

综合考虑换乘次数、乘车费用和乘车时间三方面因素,建立公交线路的组合优化模璎.从图论的角度将问题转化为在赋权有向图中寻求最短路径,通过改进的SPFA算法求解模型.改进算法用数组储存站点的信息,队列储存待优化点,然后采用动态优化逼近的方法进行搜索,时间复杂度为,运行时间短,稳定性好,并可以得到全部的最优路线.     

质量体积双约束下车辆装载与配送路径联合优化研究

目的 针对质量与体积共同限制的配送路径问题,综合考虑订单不可拆分、货物的体积等约束,构建包含路径最短和装载率最高双目标的车辆装载与配送路径联合优化模型。方法 在车辆路径优化模型的求解方面,首先利用聚类算法对配送区域进行划分,然后通过车辆的载质量判断是否能进行站点货物的配送,最后利用遗传算法求得最优路径。在三维装载模型的求解上使用贪心算法和基于块的启发式算法,解决了货物的装箱问题。结果 基于某公司具体实例对模型与算法的可行性进行了验证,优化后配送的车辆减少了1辆,配送距离减少了154.247km,平均装载率达到了93.89%,节省了企业的配送成本。结论 所构建的模型以及求解的算法可以提高装载率和配送效率,为解决车辆装载与配送路径联合优化问题提供理论依据。     

基于城市公交系统的最优换乘线路策略研究

针对乘客选择出行公交线路的问题,对较完善的城市公交系统进行分析研究,建立城市公交系统时间、费用及综合最优模型,给出时间、费用及综合浪费度的定义,基于Dijkstra最短路径算法思想,提出综合最优模型下的换乘策略算法,该算法为出行者提供最优公交线路的选择策略。     

任意两点间最短路径的新算法研究

最短路径问题是图论研究中的一个经典算法问题,Dijkstra算法和Floyd算法是解决任意两点间最短路径的常用办法。从局部最优到整体最优的思想出发,得出求解最短路径的一个新方法,即两点间的最短路径是途经当前最短路径集的复合路径和直达路径的最短者,然后以此方法给出求解任意两点间最短路径的一个新算法,最后简述新算法在针对特定问题时相对于经典算法的优势。     

基于改进网络最大流的道路通行能力优化研究

基于图论网络最大流理论基础,建立了一种改进的网络最大流模型。首先,根据最基本的网络最大流模型,采用Ford-Fulkerson算法求解出理论最大通行能力为46人/s;其次,考虑通行的道路选择性,建立最短路模型,利用Dijkstra算法计算各个单源到各个单汇的最短路径,并通过A*算法排除与最短距离相差较大的路径,从而筛选出有效路径;然后,利用最短路模型结果加强原模型中的约束条件,利用单纯形法求解出实际最大通行能力为23人/s;最后,建立以道路扩宽成本最低为目标函数的线性规划模型对道路进行优化改造。研究结果表明,现有道路设计能够满足道路通行需求,若需提高道路通行能力且要求道路改造最小,可以适当扩宽路网中的关键道路。     

对公共交通线网优化与换乘枢纽规划的研究

本文从公交网络和交通供需关系入手,分析了城市公交网络的设计准则,从而对城市公交网络优化模型进行了研究;通过对公交换乘枢纽的研究,分析了公交换乘枢纽换乘影响因素,提出了城市公交换乘枢纽布局优化方法。     

RMS中工件路径网络生成方法

利用图论建立RMS中工件路径网络生成模型。给出设备物理布局生成的3种算法：设备物理规划布局算法、基于二次布置问题(QAP)模型的VMC设备物理布局算法以及已有设备物理布局算法。给出AGV路径网络生成算法、AGV路径网络生成改进算法、可替代路径网络生成算法,包括节点间最短路径寻找子算法、路径网络预处理子算法。算法的输入为表示重构对象节点间距离信息的距离矩阵文件和表示某生产周期多工艺路线的流量文件,输出为优化的路径网络。用Visual C 实现了以上算法,实例测试验证了算法的正确性。     

基于退火算法的物流配送网的求优研究

模拟退火算法是一种启发式算法,是受到加热紧缩的退火过程所启发而提出来一种求解组合优化问题的一种逼近算法。算法要优于传统的贪婪算法,避免了陷入局部最优的可能,从而达到全局最优解。在物流配送网络中经常为有一些寻求最短路径等问题出现,为了能够达到最短、最优、最经济等,需要进行物流配送路径寻优。文中采用模拟退火算法进行一个示例的验证,效果证明可行。     

Link stability and mobility in ad hoc wireless networks

The fact that ad hoc networks are required to support mobility of individual network nodes results in problems arising when routing data. These problems include route loss, poor longevity of established routes and asymmetric communications links. Mobility of nodes also increases the control traffic overhead and affects the performance of the protocol. Mobility can, however, be exploited to improve route longevity when establishing the route. In some situations, the source of information is not available (e.g. GPS information in the underground), hence protocols relying on this information will fail to operate correctly. In such situations, alternative `self-content' information should be available to perform the needed task of routing. Three novel schemes that make use of such information, the heading direction angle, to provide a mechanism for establishing and maintaining robust and long-lived routes are presented. The results show that these schemes reduce the overhead and increase the route longevity when compared with the AODV protocol. The schemes described can operate as a standalone mechanism or can be adopted by other routing protocols in order to improve their performance.     

基于虚拟化的轻量级背景流量节点生成及部署算法研究

进行了网络攻防分析,针对传统的背景流量模拟技术在生成及部署方面存在背景流量大小}限、背景流量真实性不足、背景流量生成工具部署的数量和位置}限的问题,提出了一种基于虚拟化的轻量级背景流量节点生成及部署算法,该算法是一种基于资源量的目标流量映射、基于最短路由的背景流量应用添加、基于最少通信代价的节点映射的三阶段算法,解决了背景流量节点在网络攻防实验中大规模快速生成及灵活部署的问题。实验结果表明,使用轻量级背景流量节点,生成的背景流量满足网络自相似性,资源消耗小、启动速度快,并且可根据实际网络攻防实验的需求进行动态、灵活、快速的大规模部署。     

Configuring wide area computer networks

Summary Modern computer networks consist of wide area backbone networks which serve as major highways to transfer large volumes of communication traffic between access points, and local access networks which feed traffic between the backbone network and end user nodes. The topological design of wide area computer communication networks consists of selecting a set of locations for network control processors (NCPs) placement, deciding on backbone links and their capacities to connect the NCPs, linking end user nodes to the NCPs and selecting routes for routing messages between communicating end user pairs. This paper presents some of the problems faced by network designers starting from the capacity assignment problem, moving to routing and capacity assignment, followed by the topological design and capacity assignment problem; the last problem presented is the topological design and capacity expansion over time. The problems are complex combinatorial optimization problems, which require developing new solution procedures. The paper presents the problems and discusses models and solution procedures. The paper concludes with a discussion and directions for further research.This research was partially supported by a Dean's grant for faculty research at the Owen Graduate School of Management, Vanderbilt University, Nashville, TN 37203, USA.     

Authentication of Vehicles and Road Side Units in Intelligent Transportation System

Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents, economically damaging traffic jams, hijacking, motivating to wrong routes, and financial losses for businesses and governments. Smart and autonomous vehicles are connected wirelessly, which are more attracted for attackers due to the open nature of wireless communication. One of the problems is the rogue attack, in which the attacker pretends to be a legitimate user or access point by utilizing fake identity. To figure out the problem of a rogue attack, we propose a reinforcement learning algorithm to identify rogue nodes by exploiting the channel state information of the communication link. We consider the communication link between vehicle-tovehicle, and vehicle-to-infrastructure. We evaluate the performance of our proposed technique by measuring the rogue attack probability, false alarm rate (FAR), misdetection rate (MDR), and utility function of a receiver based on the test threshold values of reinforcement learning algorithm. The results show that the FAR and MDR are decreased significantly by selecting an appropriate threshold value in order to improve the receiver’s utility.     

Travel time prediction under heterogeneous traffic conditions using global positioning system data from buses

Travel time information is a vital component of many intelligent transportation systems (ITS) applications. In recent years, the number of vehicles in India has increased tremendously, leading to severe traffic congestion and pollution in urban areas, particularly during peak periods. A desirable strategy to deal with such issues is to shift more people from personal vehicles to public transport by providing better service (comfort, convenience and so on). In this context, advanced public transportation systems (APTS) are one of the most important ITS applications, which can significantly improve the traffic situation in India. One such application will be to provide accurate information about bus arrivals to passengers, leading to reduced waiting times at bus stops. This needs a real-time data collection technique, a quick and reliable prediction technique to calculate the expected travel time based on real-time data and informing the passengers regarding the same. The scope of this study is to use global positioning system data collected from public transportation buses plying on urban roadways in the city of Chennai, India, to predict travel times under heterogeneous traffic conditions using an algorithm based on the Kalman filtering technique. The performance of the proposed algorithm is found to be promising and expected to be valuable in the development of APTS in India. The work presented here is one of the first attempts at real-time short-term prediction of travel time for ITS applications in Indian traffic conditions.     

基于灰色模糊数的公交线网优化研究

在考虑信息不完全的情况下,用灰色模糊数对公交线网优化问题进行了研究。在给出了公交线网优化的约束条件与优化目标的基础上,利用灰色模糊数建立了公交线网优化的决策模型。灰色模糊数是用三参数区间参与优化过程,在允许参数在一定范围内变化的情况下,计算后得到的结果是一个区间向量,其中向量值最大的为所求结果,适用于城市公交线网的优化问题。实例应用分析表明,优化后的公交线网效率提高,可达性良好,可满足城市公交可持续发展的要求。     

Traffic simulation based ship collision probability modeling

Maritime traffic poses various risks in terms of human, environmental and economic loss. In a risk analysis of ship collisions, it is important to get a reasonable estimate for the probability of such accidents and the consequences they lead to. In this paper, a method is proposed to assess the probability of vessels colliding with each other. The method is capable of determining the expected number of accidents, the locations where and the time when they are most likely to occur, while providing input for models concerned with the expected consequences. At the basis of the collision detection algorithm lays an extensive time domain micro-simulation of vessel traffic in the given area. The Monte Carlo simulation technique is applied to obtain a meaningful prediction of the relevant factors of the collision events. Data obtained through the Automatic Identification System is analyzed in detail to obtain realistic input data for the traffic simulation: traffic routes, the number of vessels on each route, the ship departure times, main dimensions and sailing speed. The results obtained by the proposed method for the studied case of the Gulf of Finland are presented, showing reasonable agreement with registered accident and near-miss data.     

Models of perceived cycling risk and route acceptability

Perceived cycling risk and route acceptability to potential users are obstacles to policy support for cycling and a better understanding of these issues will assist planners and decision makers. Two models of perceived risk, based on non-linear least squares, and a model of acceptability, based on the logit model, have been estimated for whole journeys based on responses from a sample of 144 commuters to video clips of routes and junctions. The risk models quantify the effect of motor traffic volumes, demonstrate that roundabouts add more to perceived risk than traffic signal controlled junctions and show that right turn manoeuvres increase perceived risk. Facilities for bicycle traffic along motor trafficked routes and at junctions are shown to have little effect on perceived risk and this brings into question the value of such facilities in promoting bicycle use. These models would assist in specifying infrastructure improvements, the recommending of least risk advisory routes and assessing accessibility for bicycle traffic. The acceptability model confirms the effect of reduced perceived risk in traffic free conditions and the effects of signal controlled junctions and right turns. The acceptability models, which may be used at an area wide level, would assist in assessing the potential demand for cycling and in target setting.     

Cyclist safety on bicycle boulevards and parallel arterial routes in Berkeley,California

This study compares the safety of bicyclists riding on bicycle boulevards to those riding on parallel arterial routes in Berkeley, California. Literature on the impact of motor vehicle traffic characteristics on cyclist safety shows that high motor vehicle speeds and volumes and the presence of heavy vehicles are all detrimental to cyclist safety. This suggests that cyclists may be safer on side streets than on busy arterials. Bicycle boulevards—traffic-calmed side streets signed and improved for cyclist use—purport to offer cyclists a safer alternative to riding on arterials. Police-reported bicycle collision data and manually collected cyclist count data from bicycle boulevards and parallel arterial routes in Berkeley, California from 2003 to 2010 are used to test the hypothesis that Berkeley's bicycle boulevards have lower cyclist collision rates and a lower proportion of bicycle collisions resulting in severe injury. While no significant difference is found in the proportion of collisions that are severe, results show that collision rates on Berkeley's bicycle boulevards are two to eight times lower than those on parallel, adjacent arterial routes. The difference in collision rate is highly statistically significant, unlikely to be caused by any bias in the collision and count data, and cannot be easily explained away by self-selection or safety in numbers. Though the used dataset is limited and the study design is correlational, this study provides some evidence that Berkeley's bicycle boulevards are safer for cyclists than its parallel arterial routes. The results may be suggestive that, more generally, properly implemented bicycle boulevards can provide cyclists with a safer alternative to riding on arterials.     

Efficient Routing Protocol with Localization Based Priority & Congestion Control for UWSN

The nodes in the sensor network have a wide range of uses, particularly on under-sea links that are skilled for detecting, handling as well as management. The underwater wireless sensor networks support collecting pollution data, mine survey, oceanographic information collection, aided navigation, strategic surveillance, and collection of ocean samples using detectors that are submerged in water. Localization, congestion routing, and prioritizing the traffic is the major issue in an underwater sensor network. Our scheme differentiates the different types of traffic and gives every type of traffic its requirements which is considered regarding network resource. Minimization of localization error using the proposed angle-based forwarding scheme is explained in this paper. We choose the shortest path to the destination using the fitness function which is calculated based on fault ratio, dispatching of packets, power, and distance among the nodes. This work contemplates congestion conscious forwarding using hard stage and soft stage schemes which reduce the congestion by monitoring the status of the energy and buffer of the nodes and controlling the traffic. The study with the use of the ns3 simulator demonstrated that a given algorithm accomplishes superior performance for loss of packet, delay of latency, and power utilization than the existing algorithms.