基于单片机的地震仪器采集站控制优化

地震仪器是一种重要的油气勘探设备。在地震仪器中,由电源站为采集站提供电能,采集站的控制方案影响电源站的带道数量。为了提高电源站的带道数量,减少勘探成本,本文根据对地震仪器供电模型的分析,针对采集站启动状态对电源站带道数量的影响,提出了一套采集站单片机控制的优化方案,并进行了实验验证。实验结果表明,在55米道距时,电源站带道数量可提高至40道,优化方案切实、有效。     

车联网中路边设施的分布式调度策略的研究

为了降低碳排放量和部署成本,利用太阳能给车联网路边设施(Road Side Unit, RSU)供电是一个可行的方法.本文针对太阳能供电的RSU,提出了两个分布式的在线调度策略,旨在最大化服务车辆数.在基于Markov链的调度策略中,采用Markov链表述RSU能量状态,并通过对动作的奖励最大化服务的车辆数;在基于阈值的调度策略中,RSU计算服务车辆时所消耗的能量,并结合自己的能量状态,选择服务的车辆.仿真结果表明,本文提出的在线调度策略增加了服务车辆数.     

基于RSU辅助的车载机会网络通信能力增强方案

针对传统车载机会网络通信能力的有限性及随机化的问题,提出一种通过部署路边单元(RSU)进行辅助通信来增强车载机会网络通信能力的方案.该方案利用RSU稳定的覆盖、存储和传输优势,有效克服传统车载机会网络通信时间间隔长、传输能力有限等缺点.以北京和上海各自一个月的出租车全球定位系统(GPS)数据为基础,对车辆与RSU的相遇特性进行了分析,发现该方案通过合理部署RSU对车辆信息进行缓存,可以极大地提高车辆间的通信概率.理论分析和仿真实验表明,利用RSU可以完成车与车之间大数据的传输,能极大提升车载机会网络的通信能力.     

ETC系统及车载单元剖析

随着我国公路建设的快速发展和汽车保有量的迅速增加,传统的收费系统难以满足发展需求,电子收费系统ETC是解决问题的有效手段.而车载单元OBU是ETC系统中的重要设备,本文就电子收费系统ETC以及车载单元OBU做出简要描述,旨在表明ETC的发展前景和对于OBU的不断优化进行探讨。     

VANET中基于RSU辅助签名环形成的方案

车辆自组织网络(Vehicular Ad-hoc Network,VANET)使交通系统更加智能和高效。信道的开放性以及车辆移动的高速性等特点,导致VANET存在诸如身份、传输数据以及位置等隐私信息泄露问题。目前,针对VANET的身份隐私泄露问题,越来越多的学者采用基于环签名的方案,但是车辆如何在行驶过程中与周围车辆组成签名环一直是一个难解决的问题。针对基础设施部署较完善地区,文中提出一种基于RSU(Road-Side Unit)辅助签名环形成的方案。该方案通过RSU收集覆盖区域内车辆的公钥并广播公钥集,从而确定区域内车辆的签名环,并利用双线性对映射实现RSU与车辆间消息传输的基于身份加密的过程。安全分析和实验证明,所提方案在基础设施较完善地区能够拥有较好的效率和安全性。     

Routing using reinforcement learning in vehicular ad hoc networks

In vehicular ad hoc networks (VANETs), the frequent change in vehicle mobility creates dynamic changes in communication link and topology of the network. Hence, the key challenge is to address and resolve longer transmission delays and reduced transmission stability. During the establishment of routing path, the focus of entire research is on traffic detection and road selection with high traffic density for increased packet transmission. This reduces the transmission delays and avoids carry-and-forward scenarios; however, these techniques fail in obtaining accurate traffic density in real-time scenario due to rapid change in traffic density. Thus, it is necessary to create a model that efficiently monitors the traffic density and assist VANETs in route selection in an automated way with increased accuracy. In this article, a novel machine learning architecture using deep reinforcement learning (DRL) model is proposed to monitor and estimate the data essential for the routing protocol. In this model, the roadside unit maintains the traffic information on roads using DRL. The DRL predicts the movement of the vehicle and makes a suitable routing path for transmitting the packets with improved transmission capacity. It further uses predicted transmission delays and the destination location to choose the forwarding directions between two road safety units (RSUs). The application of DRL over VANETs yields increased network performance, which provides on-demand routing information. The simulation results show that the DRL-based routing is effective in routing the data packets between the source and destination vehicles than other existing method.     

OBU设备DSRC协议一致性测试技术

研究基于电子收费专用短程通信（DSRC）协议标准设计的OBU设备的DSRC协议一致性测试技术,通过分析OBU设备的特点及DSRC协议的国家标准,按照ISO／IEC9646协议一致性测试标准,结合TTCN-3测试技术,提出一套完整的DSRC协议一致性测试解决方案,该方案主要包括抽象测试集的设计和测试平台的架构2个部分。     

ETC用5.835GHz微带阵列天线的设计

设计了一种ETC用低旁瓣圆极化微带阵列天线,应用于电子收费(ETC)的路测单元(RSU)。为实现低旁瓣、圆极化的效果,对2个微带天线单元运用旋转与相位补偿的方法进行轴比改进,并以改进后的2单元作为辐射单元制作了一款基于道尔夫-切比雪夫幅度分布的微带天线阵列。经过仿真与实际测量,该天线具有很好的低旁瓣、圆极化的效果。该天线对于ETC系统以及其他类似的天线系统具有很好的理论与实际意义。     

基于DSRC协议的ETC应用研究与实现

基于DSRC协议的高速公路电子不停车收费(ETC)系统存在价格昂贵、通用性差的问题。为此,简化车载设备对错误信息帧的处理,采用微控制器设计并实现符合ETC复合消费交易应用流程规范的通信帧数据链路层及应用层信息的解析、封装。测试结果表明,程序移植到车载设备硬件系统后,系统运行稳定,时效性符合国家标准要求。     

Performance enhancement of traffic information gathering (PEnTInG) algorithm for vehicular ad‐hoc networks

Vehicular ad‐hoc networks (VANETs) play a vital role in today's context of vehicular traffic. In this paper, clusters of vehicles are created on the basis of average speed of the vehicles. One cluster communicates with the next cluster through a cluster head and also share the same information with next cluster heads and installed road side units (RSUs). By using this technique, we can solve the problem of rough driving behavior and road terrorism which is due to speed variation of vehicles and fake information dissemination by the drivers. Many a times, drivers may spread fake accident‐related information into the network which is a serious cause of concern in VANETs. It is ensured that such drivers are not allowed to spread wrong information in the network to avoid accidents. To solve this problem, we developed performance enhancement of traffic information gathering (PEnTInG) algorithm that selects only those drivers/vehicles as cluster heads in a cluster who has maximum value of the cluster head factor (CHF). The CHF is derived by considering different weights in range of 0 to 1 of relative average speed, time to leave, trust factor, and neighborhood degree. Further, the elected cluster head shares and stores the same information with the RSUs. In case, a driver wants to disseminate fake or wrong information in a network, then that vehicle driver can be easily tracked by the local authority by accessing RSU data. Simulation results show that the stability of PEnTInG is increased by 25% against the existing schemes viz. lowest‐ID, MCMF, and cluster‐based technique.