专家系统中的知识表示及其实时处理方法研究

文章以飞机驾驶员辅助决策系统为实俐，建立并开发了一种面向对象的黑板模型．提出并实现了驾驶员辅助决策专家系统实例中知识的表示和实时知识处理的解决方案。该方案通过改善黑板模型的控制方式，提高了知识处理的并发性，同时引入消息管理器机制来实现对知识的实时处理。实际应用表明本方案比较适合于大型的知识系统的开发。     

基于电子车牌的智能交通灯控制系统设计

城市机动车辆的增加,且现有的交通信号灯控制时间与轮转时间固定不变,不但不能有效地应对交通现状,反而会加剧拥堵。该设计方案通过电子车牌获取各路段内实时车流量,并据此对交通信号灯进行智能控制。本系统成本低、实时性好,将提高车辆通行效率。     

遗传算法在船舶转向避碰幅度决策中的应用研究

针对船舶避碰决策系统中的船舶运动趋势和避碰时机,应用遗传算法模型,实时预测各目标船相对于本船在下一时刻的运动参数,预估目标船相对于本船的最近会遇距离（DCPA）和最近会遇时间（TCPA）。同时,应用遗传算法模型预测避碰最优角度问题。仿真结果表明,该方法能有效提高船舶海上航行的灵活性和安全可靠性,达到提前预警和帮助驾驶员提前做好避碰准备等目的。     

基于数据挖掘的主配网一体化协同监视方法

为了实现主网和配网之间线路运行状态以及相关设备运行状态的协同决策、协同监管，研究基于数据挖掘的主配网一体化协同监视方法。将采集的数据进行格式统一化处理，传送至数据管理层，数据管理层完成数据清洗及校验后，分类存储；协同监视层通过主配网历史数据模型、实时估计以及态势预判感知存储数据，采用随机森林算法构建协同决策规则库，将感知结果与协同决策规则库进行匹配，获取故障控制决策。测试结果表明，该方法的感知性能良好，可快速完成故障和控制策略的匹配，满足主配网一体化协同监视需求。     

基于单片机的智能交通灯控制系统

本文提出了一种基于单片机的智能交通灯控制系统方案。该方案采用STC89C52作为微处理器,超声波传感器为车流量检测器件,红绿灯和倒计时显示模块为控制对象。通过超声波传感器对道路车流量进行检测,并将其检测数据送与单片机控制系统处理,从而实时分配各道路车辆通行的时间。灵活的智能交通控制系统能够改善交通状况,提高道路的通行效率。     

基于AI识别的隧道智能监控与显示系统

文中设计了一个基于AI识别技术的隧道智能监控与显示系统,该系统在提高隧道的运行安全和管理效率方面具有显著优势。通过实时监测隧道内的交通状况和环境状态,驾驶员可以获取隧道内的实时交通信息,并根据预警提示做出更合理的驾驶决策。此外,交通管理人员能及时发现并解决问题,提高事故处理的响应速度和准确性。在未来的研究中,将继续加强对该系统的深入研究和实践,进一步推动其在交通领域中的实际应用。     

基于移动通信的城市停车诱导信息系统设计

随着汽车保有量不断增加,停车难已成为城市交通普遍问题。从分析城市停车诱导系统功能和提高停车设施利用率的角度出发,结合实际城市交通情况,采用PGIS技术,提出一个整体性、实时动态的停车诱导信息系统。该系统设计通过仿真验证有效．因此将为城市交通管理控制、驾驶员出行提供更准确和有效的诱导决策辅助信息。     

基于ADSP-BF548的驾驶员疲劳检测系统设计

为防止由疲劳驾驶引发的交通事故,采用基于视觉特征PERCLOS的疲劳检测算法,并以ADI公司ADSP-BF548处理器为算法硬件平台,实时检测驾驶员的疲劳状态。本系统通过车载摄像头实时拍摄驾驶员人脸图像,然后经帧差、投影、模板匹配等图像处理方法正确定位驾驶员的人眼位置,最后根据单位时间内人眼闭合时间所占比,超过阈值则适时预警。实验表明,基于ADSP-BF548的驾驶员疲劳检测系统具有良好的准确性和实时性。     

基于移动通信的城市停车诱导信息系统设计

随着汽车保有量不断增加,停车难已成为城市交通普遍问题.从分析城市停车诱导系统功能和提高停车设施利用率的角度出发,结合实际城市交通情况,采用PGIS技术,提出一个整体性、实时动态的停车诱导信息系统.该系统设计通过仿真验证有效,因此将为城市交通管理控制、驾驶员出行提供更准确和有效的诱导决策辅助信息.     

基于WFPN和多Agent黑板模型的PAAIS知识处理研究

驾驶员辅助决策人工智能系统（PAAIs）是辅助飞机驾驶员进行决策的智能系统，其核心是知识处理。文章采用黑板模型与多Agent技术相结合来构建PAAIS的知识处理架构，以加权模糊Petri网（WFPN）进行模糊知识表示，并提出有效的模糊推理算法。     

Spatial experience based route finding using ontologies

Spatial experiences in route finding, such as the ability of finding low‐traffic routes, exert a significant influence on travel time in big cities; therefore, the spatial experiences of seasoned individuals such as taxi drivers in route finding can be useful for improving route‐finding algorithms and preventing using routes having considerable traffic. In this regard, a spatial experience‐based route‐finding algorithm is introduced through ontology in this paper. To this end, different methods of modeling experiences are investigated. Then, a modeling method is chosen for modeling the experiences of drivers for route finding depending on the advantages of ontology, and an ontology based on the taxi drivers’ experiences is proposed. This ontology is employed to create an ontology‐based route‐finding algorithm. The results are compared with those of Google maps in terms of route length and travel time at peak traffic time. According to the results, although the route lengths of route‐finding method based on the ontology of drivers’ experiences in three cases (from nine cases) are greater than that based on Google maps, the travel times are shorter in most cases, and in some routes, the difference in travel time reaches only 10 minutes.     

The strategy and deployment plan for VICS

The objective of a vehicle information and communication system (VICS) is to disperse traffic by providing drivers with road traffic information to enable them to satisfy their natural desire to “get there faster”. Put simply, VICS is based on drivers' arbitrary selection of routes and on the automobile's unique ability to take any desired route. The objective is to promote the safe, smooth flow of traffic by naturally distributing the flow of traffic, which is done by guiding cars to the appropriate routes in accordance with drivers' instinctive desire to reach their destinations quickly by avoiding traffic congestion. VICS distributes road traffic information such as traffic jams or accidents to drivers in real time, and stimulates drivers for accurate and proper utilization     

Traffic management improvement by integrating modern communicationsystems

The motivation for the research discussed in this article is to enable better driving through the use of modern communications technology. Therefore, one- and two-way communication systems have been investigated for their specific advantages in the improvement of driver information, safety, and traffic flow. The possibilities of various cellular communications systems are presented. Autonomous in-car navigation systems have reached marketability, and are able to perform static route guidance for drivers. These systems can be improved by giving them a knowledge of the current traffic situation to enable dynamic route guidance. This information can be transmitted via different communication systems, which are discussed     

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.     

A Framework For Handling Local Broadcast Storm Using Probabilistic Data Aggregation In VANET

Data aggregation is used to combine correlated data items from different vehicles before redistributing to other vehicles in the vehicular ad hoc networks (VANET). The number of retransmissions and the communication overhead can be reduced considerably by using aggregation. It is a prerequisite for applications that require periodic dissemination of information into a large region so that, drivers can be informed well in advance and can take alternative route in case of traffic congestion. Dissemination of information to vehicles through broadcasting creates a broadcast storm problem in VANET. In this paper a novel framework is proposed for handling the local broadcast storm problem using probabilistic data aggregation which reduces the bandwidth consumption and hence improves the information dissemination. This system exploits the knowledge base and stores the decisions for aggregation and is based on a flexible and extensible set of criteria. These criteria’s can be application specific and can enable a dynamic fragmentation of the road according to the various application requirements. The framework is evaluated for VANET based traffic information system through simulation for strictly limited bandwidth and local broadcast problem. The results demonstrate that completely structure-free probabilistic data aggregation reduces the bandwidth consumption by eliminating the local broadcast problem.     

Traffic Volume Prediction Based on Multi-Sources GPS Trajectory Data by Temporal Convolutional Network

Predicting urban traffic volume is of great significance to traffic management and urban construction. An accurate prediction model can help drivers optimize driving routes, allocate resources reasonably and reduce urban traffic congestion. Most of the existing studies do not consider the complex nonlinear spatio-temporal relationship. In the spatial dimension, they do not consider the impact of regional semantics and regional interactions. In the temporal dimension, they ignore the impact of long-term historical information and key time points. Aiming at the complexity of traffic data, in this paper, we design a ResNet-TCN model to predict the urban traffic volume. Firstly, we construct and extract features from the vehicle GPS tracking and external information, such as velocity, time, location and weather. Then, we obtain regional semantic information by the ResNet model and combine the weights of the regional division with the average vehicle velocity into a two-channel matrix. We extract the key features of the matrix sequence and predict the velocity by the TCN model. Finally, we estimate the traffic volume through a traffic volume inference model in the traffic field. We conduct a large number of experiments on the actual dataset of Chengdu and compare our model with the existing models. The experimental results show that our method has better performance on prediction accuracy.

     

基于模糊C均值聚类和随机森林的短时交通状态预测方法

交通拥堵长期以来是城市面临的主要问题之一,解决交通拥堵瓶颈刻不容缓。准确的短时交通状态预测有利于市民预知交通出行信息,及时采取措施避免陷入拥堵困境。该文提出一种基于模糊C均值聚类(FCM)和随机森林的短时交通状态预测方法。首先,利用一种新颖的融合时空信息的自适应多核支持向量机(AMSVM)来预测短时交通流参数,包括流量、速度和占有率。其次,基于FCM算法分析历史交通流,获取历史交通状态信息。最后,利用随机森林算法分析所预测的短时交通流参数,得到最终预测的短时交通状态。该方法在融合时空信息的同时采用随机森林算法应用于短时交通状态预测这一全新的研究领域。实验结果表明,FCM对历史交通状态的评估方式适用于不同的高速路和城市道路场景。其次,随机森林比其它常见的机器学习方法具有更高的预测精度,从而提供实时可靠的短时交通出行信息。     

基于MSP430F149的红绿灯自动显示装置的设计

本项目设计主要解决在交通路口由于驾驶员对红绿灯辨识不清而存在的交通隐患，提供一种设计合理、自动化程度高、安全快捷的红绿灯自动报警装置。电路主要由红绿灯状态信息、电源模块、无线发射模块、无线接收模块、MP3模块、车内控制器等模块构成。基于无线传输的红绿灯自动报警显示装置可以自动为驾驶员提供交通路口的红绿灯状态信息，让驾驶员在通过交通路口时轻松自如、安全快捷的通过，从而减少交通事故的发生。     

基于智能终端定位的智能交通疏导系统研发

在城市发展到比较成熟的阶段,缓解交通堵塞可借鉴智能交通系统(Intelligent Transportation System,ITS)的理念,文章在现有的无线通信设施和车辆系统上,通过融合信息与通信技术、移动互联网和智能终端设备构建一套道路交通流量计算和道路交通服务系统。该系统通过车载智能终端的GPS数据进行实时交通流量计算,并且将计算的交通流量信息实时地反馈给驾驶车辆的用户,方便用户出行道路选择,缓解交通阻塞。