基于航模辅助观测的车辆轨迹提取方法

为了克服交通流定点视频观测方法在观测范围上的局限性,提出了一种基于飞行航模辅助视频观测的地面道路车辆轨迹提取方法．首先应用飞行航模在空中拍摄获得道路交通流视频,并将视频分解为连续逐帧图片;其次应用针孔成像模型和空间坐标转换算法,对逐帧航拍图片内的车辆坐标进行提取和转换,以获得车辆的运行时空轨迹数据;最后进行了该方法的3类误差分析.结果表明,该方法在标准棋盘格试验下提取坐标的相对误差小于5％,实际道路交通目标坐标提取的精度达到90％以上．航模辅助视频观测法可实现对交通目标的大范围低成本观测,能够满足交通工程的观测需求．     

基于用户反馈的WiFi位置指纹数据库更新算法

为使Wi Fi位置指纹数据库,不在定位区域Wi Fi环境发生改变时,出现位置指纹过时现象,设计一种更新算法。该算法使用用户的反馈数据,考虑了AP信号不稳定情况下AP新增与撤销的检测问题;消除了手机热点等临时AP对传统更新算法的影响;最终通过检测AP位置移动等引起的RSS改变,加速位置指纹数据库的更新。实验结果表明,在实际环境中该算法在指纹数据库的更新效率上优于传统更新算法。     

城市车载网络中基于停放车辆辅助的数据分发

VANETs(vehicular ad hoc networks)具有节点高速移动、网络间歇性连通和拓扑高度动态变化等特点.要分发的数据很难被维持在目标区域的道路上,不能持续为行驶经过的车辆提供服务.鉴于城市区域道路两旁长时间拥有大量停放车辆这一事实,提出了VANETs中基于停放车辆辅助的数据分发策略PADD(parked-vehicle assisted data dissemination).PADD按照簇的结构对目标区域内的路边停放车辆进行管理,将要分发的数据从数据源路由到目标区域合适的停车簇,并采用订阅/发布机制在停车簇一跳范围内实现数据分发.理论分析证明了停放车辆辅助的有效性;基于真实城市地图和交通数据的模拟实验结果表明:与现有的几种数据分发算法相比,PADD能以较低的网络负载和较小的传输延迟获得较高的数据传输成功率.     

车辆网络中一种有效的警告消息散布协议

针对车辆网络的警告消息散布问题进行研究,提出一种有效的警告消息散布协议WMD.在WMD中,时间被分成一个个带时间槽的时间帧,每个时槽被分成两个子时槽,第一个时槽用来实时获取邻居位置,第二个时槽用来散布警告消息.为了实时获取邻居位置,WMD采取自适应的发送策略.通过理论分析,对每个时间帧的发送次数以及每个时间帧的长度进行优化.基于真实车辆行驶数据进行仿真实验.实验结果表明,相比其他方法,WMD实现了较快的散布速率和较高的接收率.     

无线多用户投影网关切换技术设计与实现

针对目前无线投影网关多用户切换技术研究的缺失及必要性,为了减少切换带来的延迟、抖动,提出了多用户的切换协议。通过实现基于Wi-Fi Direct的无线投影网关系统,模拟多用户使用场景,给出了详细的切换流程、数据结构,同时分析了延迟产生的原因,提出了数据预缓冲技术,进一步对多用户切换进行改进,最后通过实验测试证明其在减少切换延时的有效性。     

Contention-based forwarding with multi-hop connectivity awareness in vehicular ad-hoc networks

Recent vehicular routing proposals use real-time road traffic density estimates to dynamically select forwarding paths. Estimating the traffic density in vehicular ad hoc networks requires the transmission of additional dedicated messages increasing the communications load. These proposals are generally based on unicast sender-based forwarding schemes. The greedy nature of sender-based forwarding can result in the selection of forwarders with weak radio links that might compromise the end-to-end performance. To overcome these limitations, this paper presents TOPOCBF, a novel contention-based broadcast forwarding protocol that dynamically selects forwarding paths based on their capability to route packets between anchor points. Such capability is estimated by means of a multi-hop connectivity metric. The obtained results demonstrate that TOPOCBF can provide good packet delivery ratios while reducing the communications load compared to unicast sender-based forwarding schemes using road traffic density estimates.     

车载自组织网络路由协议的仿真研究

本文简要介绍了车载自组织网络和移动自组织网络中两个典型的路由协议:表驱动路由协议DSDV和按需路由协议AODV;还介绍了一个实用的移动模型,使仿真实验更加接近现实。在Linux下使用网络仿真工具NS2对这两个典型协议进行仿真,并对仿真结果进行分析比较和性能评价,得出:AODV和DSDV协议都不太适用于车辆自组织网络,所以设计适合车辆网路的协议是急需解决的问题。     

ICBF：汽车Ad-Hoc网络中一种改进的CBF算法

汽车Ad-Hoc网络是一种特殊的Ad-Hoc网络,其路由层面临着许多挑战。本文提出汽车Ad-Hoc网络中一种改进的CBF算法--ICBF。通过速度、方向和距离三个重要的因素控制定时器,更准确地选择下一跳转发节点;利用城市场景下汽车与相邻汽车之间速度差较小的特点,减少了数据包的广播;提出一种新的锚点路径选择算法,使得ICBF协议能够主动地感知地理拓扑和交通密度,从而达到优化路由性能的目的。实验表明,在城市场景下,ICBF算法能提高数据转发成功率,减少网络的带宽负荷。     

Automated construction of Wi-Fi-based indoor logical location predictor using crowd-sourced photos with Wi-Fi signals

Owing to the recent proliferation of smartphones and the SNS, a large number of images taken by smartphones at various places have been uploaded to SNSs. In addition, smartphones are equipped with various sensors such as Wi-Fi modules that enable us to generate an image associated with the sensory information that represents the context in which the image was captured. This study demonstrates the benefits of images associated with Wi-Fi signals in the automated construction of a Wi-Fi-based indoor logical location classifier that predicts a semantic location label of a user’s position for shopping complexes. In this study, a logical location class refers to the store class label in a shopping complex, such as Starbucks and H&M. Given a collection of images associated with Wi-Fi signals taken at a shopping complex and the complex’s floor plan, the proposed method first estimates the store label at which an image was taken by analyzing the image and crawled online images of branch stores. Then, the 2D coordinates of the images taken at branch stores on the floor coordinate system can be estimated using the floor plan. Subsequently, by using the Wi-Fi signals of the branch store images and their estimated 2D coordinates, we construct a transformation function that maps Wi-Fi signals onto the 2D coordinates, and we adopt this function to predict an indoor location class of an observed Wi-Fi scan from a smartphone possessed by an end user. The proposed transformation function comprises an ensemble of sub-functions designed based on CVAEs. Finally, we demonstrate the effectiveness of the proposed method for three actual shopping complexes.     

Ultrawideband coupled relative positioning algorithm applicable to flight controller for multidrone collaboration

In this study, we introduce a loosely coupled relative position estimation method that utilizes a decentralized ultrawideband (UWB), Global Navigation Support System and inertial navigation system for flight controllers (FCs). Key obstacles to multidrone collaboration include relative position errors and the absence of communication devices. To address this, we provide an extended Kalman filter-based algorithm and module that correct distance errors by fusing UWB data acquired through random communications. Via simulations, we confirm the feasibility of the algorithm and verify its distance error correction performance according to the amount of communications. Real-world tests confirm the algorithm's effectiveness on FCs and the potential for multidrone collaboration in real environments. This method can be used to correct relative multidrone positions during collaborative transportation and simultaneous localization and mapping applications.