共查询到19条相似文献，搜索用时 687 毫秒
1.
《黑龙江科技信息》2016,(30)
针对高速道路节点长时间、大面积拥堵现象,论述了浙江省交通厅利用联通通讯网络(手机)的交通信息采集系统进行车辆通行状况数据采集,并通过视频测试和浮动车测试两种方法对高速公路交通状态数据质量进行评测,评测过程中采集相应道路交通状态较为可靠的基准数据,通过与系统输出的交通状态结果进行对比误差分析,验证并评价系统发布结果的准确性。评测结果表明联通通讯网络(手机)的交通信息采集系统的对于高速公路的交通状态检测达到较好的精度水平,具备后期全面建成覆盖浙江省所有高速路网的基于手机数据的道路交通信息采集系统的技术基础,拓展浙江省交通信息化覆盖范围,不断满足政府对于宏观交通规划、决策、控制、管理的需求和公众用户对于实际出行的交通应用需求。 相似文献
2.
《科技通报》2016,(8)
图像在过度曝光采集的情况下会因为光圈的进光量过大导致图像的细节关键信息缺失,研究过度曝光图像的缺失信息修复算法,为图像的细节特征分析奠定基础。传统方法采用图像小波尺度分解方法进行图像缺失信息修复,随着光圈的增大,对细节信息的修复效果不好,提出一种基于改进的小波包分解的过度曝光图像缺失信息修复算法。构建了过度曝光图像的纹理信息特征传导模型,采用Harris角点检测算法实现对过度曝光图像的灰度特征匹配,采用小波包分解方法对图像缺失信息进行位置和尺度信息的重构,实现缺失信息修复。仿真结果表明,采用该算法进行过度曝光图像修复,图像的细节特征得到准确有效复原,提高图像的识别能力。 相似文献
3.
4.
随着科技的发展,道路交通信息的采集方式越来越多样化,目前应用于大范围交通信息采集的方式主要有2种,即基于手机采集和基于GPS浮动车采集。利用手机移动通信网络中的定位信息来分析推算动态交通状况是一种新兴的广域动态交通探测技术,车载GPS采集方式利用安装了GPS系统的行驶车辆,获得车辆运行状态数据,以反映实际道路的交通状态。文章结合Dempster-Shafer方法,对以上两种数据进行融合,估计道路的交通状态。将该方法应用于上海某道路进行实地验证,结果表明：相比于单一数据源来说,该方法能够提供时空覆盖面更广,精度更高的实时道路交通状态信息。 相似文献
5.
用全站仪采集测图数据后,进行内业数据传输时经常会遇到坐标位数缺失的问题。因此,为解决全站仪野外测图时导出数据位数缺失问题,本文提出以Excel为工具,利用Excel强大的表格制作与数据分析处理功能,对全站仪导出数据缺失位数进行批量改正。经实例检验,证明本方法具有简便易操作的优点。同时,本文方法可为全站仪野外测图缺失数据位数改正提供一种缺失位数改正的参考方法,对于全站仪野外测图具有重要的应用价值和实践意义。 相似文献
6.
针对南昌市现有ITS发展状况,基于交通用户信息需求分析,综合交通信息平台功能和性能分析,在此基础上,本文设计了南昌市综合交通信息平台系统框架结构,提出南昌市综合信息平台的系统模块划分,并对系统模块进行了分析,将有利地指导南昌市综合交通信息平台的建设. 相似文献
7.
我国智能交通系统专利状况分析 总被引：1，自引：1，他引：0
专利信息能够从一个侧面反映技术发展的趋势变化。通过中国专利检索系统(CPRS)中公开收录的专利数据,对智能交通系统主要是城市道路智能交通系统中的交通信息采集技术、交通信息处理技术、交通管理技术和交通信息服务技术等4个重点领域的专利申请情况分别进行研究。文章通过对专利申请态势、国内技术分布和国外来华专利布局进行对比分析,发现ITS领域存在的专利机会和风险,提出技术布局策略和发展建议。 相似文献
8.
<正>智能交通系统（Intelligent Transportation System，简称ITS）是指将先进的计算机，电子信息，传感器等技术运用于交通运输控制与决策中，以构建更加安全高效的交通运输环境。在ITS的构建中，运用大数据进行短时交通流预测起着重要作用。实现短时交通流的预测，可以帮助交管部门对复杂的交通状况进行监测和预测，以便及时采取措施展开交通管理和疏导；也可帮助出行者了解实时交通运行状态并作出合理安排，对交通拥堵的改善具有积极影响。因此，本文将道路短时交通流的预测作为研究对象，建立多因素复杂交通环境下的车流量预测模型。 相似文献
9.
10.
11.
《Journal of The Franklin Institute》2023,360(7):4973-5000
In recent years, regional traffic congestion has become increasingly frequent, which seriously affects the safety and efficiency of urban vehicles. Therefore, traffic flow prediction methods based on artificial intelligence are widely used in traffic management. However, the existing traffic flow prediction methods need to collect raw data, which involves risks of vehicle privacy leakage. Federated learning, which shares model updates without exchanging local data, has gradually become an effective solution to achieve privacy protection. A federated learning traffic flow prediction model for regional transportation systems is proposed in this paper. At the same time, due to the emergence of highly intelligent automatic driving vehicles, a vehicle scheduling system, which can control the departure and routes of vehicles in urban regions is developed in the proposed approach. A road weight measurement method combined with real time traffic information is introduced to optimize the driving routes of vehicles to reduce the average travel time. Additionally, departure strategy, is another factor that has a great influence on traffic efficiency, but is usually ignored in the past, and is also carefully compared and studied in this paper. The numerical results illustrate that the proposed schemes can effectively improve the privacy protection ability of model updates, reduce the scheduling completion time by using the traffic flow prediction model, and realize the comparative research between departure strategies, which provides a reference for developing a safe and efficient regional transportation system. 相似文献
12.
分析《中国图书馆分类法》第五版的类目变化情况,对其中U类（交通运输）的修订特点进行分析,将其类目设置与第四版进行对比,并指出图书馆标引人员在查找交通运输类相关资料时应注意的问题。 相似文献
13.
《Information processing & management》2022,59(1):102750
In the last few years, intelligent transport systems (ITS) have drawn growing attention, and these applications would have a clear and more comfortable experience for transportation. ITS provides applications with a chance to address the future condition on the route beforehand. The major issues in ITS to accomplish a precise and effective traffic flow prediction system are essential. Therefore, in this paper, a machine learning-assisted intelligent traffic monitoring system (ML-ITMS) has proposed improving transportation protection and reliability to tackle several challenges. The suggested ML-ITMS uses mathematical models to improve the accuracy estimation of traffic flow and nonparametric processes. The Machine Learning-based (ML) method is one of the best-known methods of nonparametric. It requires less prior information about connections between various traffic patterns, minor estimation limitations, and better suitability of nonlinear traffic data features. Human-Robot Interaction (HRI) helps resolve crucial issues concurrently on both the customers and service supplier levels at both ends of the transport system. Thus the experimental results show the proposed ML-ITMS to enhance traffic monitoring to 98.6% and better traffic flow prediction systems than other existing methods. 相似文献
14.
Nzeqqe Chantale Ebude Wang Mingyan 《科技广场》2007,(7):6-8
Most traffic control systems available in major cities in Cameroon are still out dated, make use of theories and models which are very slow to implement, waste resources and their efficiency is very low. Thus the number of road accidents encountered on our major highways and inter urban traffic networks has been increasing despite the various efforts made by government and certain NGO to synthesize road users on certain aspects of traffic control and safety road use. Taxis are not left out in the whole show and most of the blame always falls on them. The need to use available Information and Communication Technology ICT to improve on the control of traffic in inter urban cities and major highways is imperative. ITS optimizes the use of resources, reduce pollution, contribute to environmental protection and increases the national economy. . This paper starts by giving a brief situation of the transportation system in Cameroon, its drawbacks and proposes an optimized ITS based system. 相似文献
15.
人体生物节律理论揭示了人的体力、情绪和智力的周期性变化规律,及其对人们行为的影响。驾驶员的行为是引发道路交通事故的主要因素。利用人体生物节律理论对驾驶员及交通运输企业进行安全行车的管理和指导,能够有效地减少和预防道路交通事故的发生,改善道路交通安全状况。 相似文献
16.
通过对城市交通大数据的分析,研究中心主城区主干道路交通违法行为。利用优化的数学模型进行数字化及可视化分析,找出交通违法行为的现状和分布规律;采用粒计算的思想对数据进行信息粒化,在周期性的数据中找到数据的总体波动,剥落Low层数据,筛选出Up层和R层数据,选取不同模型对数据进行线性拟合与对比,显示Fourier级数模型拟合结果更优;对每条路线的车辆交通违法信息逐一分析,结果显示二号路线在7—8月份出现车辆交通违法56.38次,四号线路线在6月份出现8次。文中建立新的数学模型来处理周期性数据,模型精确度高,能明确评估城市交通违法情况。 相似文献
17.
《Information processing & management》2023,60(3):103243
The detection and identification of traffic signs is a fundamental function of an intelligent transportation system. The extraction or identification of a road sign poses the same problems as object identification in natural contexts: conditions of illumination are variable and uncontrollable, and various objects frequently surround road signs. These difficulties make the extraction of features difficult. The fusion of time and space features of traffic signs is important for improving the performance of sign recognition. Deep learning-based algorithms are time-consuming to train based on a large amount of data. They are difficult to deploy on resource-constrained portable devices and conduct sign detection in real time. The accuracy of sign detection should be further improved, which is related to the safety of traffic participants. To improve the accuracy of feature extraction and classification of traffic signs, we propose MKL-SING, a hybrid approach based on multi-kernel support vector machine (MKL-SVM) for public transportation SIGN recognition. It contains three main components: a principal component analysis for image dimension reduction, a fused feature extractor, and a multi-kernel SVM-based classifier. The fused feature extractor extracts and fuses the time and space features of traffic signs. The multi-kernel SVM then classifies the traffic signs based on the fused features. Different kernel functions in the multi-kernel SVM are fused based on a feature weighting procedure. Compared with single-core SVM, multi-kernel SVM can better process massive data because it can project each kernel function into high-dimensional feature space to get global solutions. Finally, the performance of SVM-TSR is validated based on three traffic sign datasets. Experiment results show that SVM-TSR performs better than state-of-the-art methods in terms of dynamic traffic sign identification and recognition. 相似文献
18.
智能汽车可实现城市资源的统筹调度、优化分配和顺畅流动,是实现交通治理智能化升级的重要突破口。为促进中国实现交通治理的智能化升级,从车端视角对智能汽车科技群进行系统梳理,建立涵盖人工智能、通信、地理信息数字化和计算机科学四大领域的基本框架,通过综合评估发现中国在5G通信技术、应用软件开发能力、导航与定位领域具有部分优势,但在高性能芯片、车用人工智能算法以及信息安全等核心技术领域存在明显的瓶颈和短板。在此基础上,描绘面向交通治理能力升级的中国智能汽车科技创新协同发展战略和技术路线图,提出由智能汽车提供商、软硬件提供商及平台运营商等多方共同主导的网状生态系统的未来智能汽车产业生态理想图景,并梳理分析各类相关企业在实践中有效分工协作的特色商业模式。最后分别从国家和企业层面给出践行智能汽车科技创新发展战略、支撑交通治理智能化升级的方向性建议。 相似文献