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1.
《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
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设计并实现了一种基于DM642视频车辆检测系统。提出了一种基于虚拟线圈匹配的算法,算法原理是估计车辆的速度和结合背景差统计量来检测通过监测区域的车辆,把算法移植到DM642平台中进行处理运行,处理结果可以满足视频处理的实时性要求,并且算法对外界环境变化的干扰有一定的鲁棒性,准确的车流量检测精度,并且运行稳定。 相似文献
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智能交通系统的发展与思考 总被引：7，自引：0，他引：7
随着社会经济的不断发展和交通量的持续增长，智能交通系统日益引起人们的关注，已成为未来交通运输的发展方向。本文较详细地介绍了ITS的基本概念和服务领域以及深圳ITS的发展情况，并提出发展建议。 相似文献
4.
智能交通系统中短时交通流预测系统的研究 总被引：12，自引：0，他引：12
短时、实时交通流预测是城市交通控制与诱导的基础，也是智能交通系统的重要功能之一。研究表明，没有一种预测模型和方法能够适用于各种环境和条件下的交通流预测。本文提出并建立了一种短时交通流的智能预测系统，按照智能预测和组合预测的思想，实现预测模型的智能选择，以及多个预测模型的预测结果的综合。仿真试验结果表明，系统具有较强的适应性，提高了预测的准确性。该系统采用多智能体技术进行设计和实现，文章给出了这种基于多智能体的智能交通预测支持系统的系统结构和工作原理。 相似文献
5.
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
6.
ITS系统处理交通状态信息数据质量好坏是后续交通诱导和运营应用的关键,所以数据质量的保障是ITS的重要组成部分。对于ITS处理的交通状态信息(路段速度及流量),由于各种原因会造成数据的不完整和缺失,这种情况下会直接影响交通管理和科研研究效果。本文针对缺失数据给出了修复的策略以及修复数据来源;然后根据不同条件使用适应的修复模型;最后对方法进行了实际数据验证。该方法对于定点检测器和移动检测器处理的交通状态缺失数据处理均可参考适用。 相似文献
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Najmeh Daroogheh Nader Meskin Khashayar Khorasani 《Journal of The Franklin Institute》2018,355(8):3753-3794
Health monitoring of nonlinear systems is broadly concerned with the system health tracking and its prediction to future time horizons. Estimation and prediction schemes constitute as principle components of any health monitoring technique. Particle filter (PF) represents a powerful tool for performing state and parameter estimation as well as prediction of nonlinear dynamical systems. Estimation of the system parameters along with the states can yield an up-to-date and reliable model that can be used for long-term prediction problems through utilization of particle filters. This feature enables one to deal with uncertainty issues in the resulting prediction step as the time horizon is extended. Towards this end, this paper presents an improved method to achieve uncertainty management for long-term prediction of nonlinear systems by using particle filters. In our proposed approach, an observation forecasting scheme is developed to extend the system observation profiles (as time-series) to future time horizon. Particles are then propagated to future time instants according to a resampling algorithm instead of considering constant weights for the particles propagation in the prediction step. The uncertainty in the long-term prediction of the system states and parameters are managed by utilizing dynamic linear models for development of an observation forecasting scheme. This task is addressed through an outer adjustment loop for adaptively changing the sliding observation injection window based on the Mahalanobis distance criterion. Our proposed approach is then applied to predicting the health condition as well as the remaining useful life (RUL) of a gas turbine engine that is affected by degradations in the system health parameters. Extensive simulation and case studies are conducted to demonstrate and illustrate the capabilities and performance characteristics of our proposed and developed schemes. 相似文献
9.
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
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《Information processing & management》2020,57(1):102139
The increased popularity of micro-blogging applications together with the widespread of location-aware devices have resulted in the creation of large streams of geo-tagged data. Such data provides a great opportunity for researchers to explore event detection and prediction. In particular, road traffic detection and prediction are of great importance to various applications, i.e. Intelligent Transportation Systems. Current works proposed traffic jam detection from a single data source with a single language. However, for countries where the residents are speaking two, or more, languages and are interacting with more than one online social platform, single-language and single-source systems are insufficient to capture the necessary online information. Therefore, in this paper, we introduce SNSJam, an effective system to detect and predict road traffic jams using cross-lingual (English and Arabic) data collected from multiple dynamic sources, such as Twitter and Instagram. SNSJam classifier not only detect traffic events, but also identifies the causes of traffic jams. To identify the location of a traffic event, a Location Recognizer is developed that extracts locations from text and GPS of the post. Additionally, the Location Recognizer supports user-defined locations, which are common names among people. Our experiments show that by combining Arabic and English data streams, the accuracies of traffic events detection and prediction are significantly improved as compared with that of the individual languages. Additionally, combining data streams from multiple sources (Twitter and Instagram) further improved the accuracies of event detection and prediction over any individual source. A visualization interface was developed to show the detected spatio-temporal traffic events on a dynamic map. The detection and prediction results are validated against ground truth data obtained from the concerned authorities in the UAE. 相似文献
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《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
13.
《Information processing & management》2022,59(4):102954
This paper aims to propose an intrinsic partial linear modelling (IPLM) framework for characterizing the complex relationship between the response manifold-valued data and a set of explanatory variables such as age, education years, or gender. Such manifold value data are widespread in medical imaging, gesture recognition, computer vision, feature tracking, shape modeling, and others. Compared with most nonparametric and parametric models for manifold-valued data, our IPLM as a semi-parametric model contains both parametric and nonparametric components, leading to better adaptability, interpretation, fitting, and robustness. Furthermore, we propose an iterative estimation strategy to estimate unknown components in IPLM and use simulation experiments to display the performance of the proposed estimation methods. Finally, we apply the proposed IPLM to model the association between the brain subcortical region Corpus Callosum (CC) 2D shape and multiple covariates, such as age, gender, or disease diagnosis, show its wide application in estimating the continuous 2D shape trajectories and comparing the difference in different groups. 相似文献
14.
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
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当代无人机特点是数量众多、应用范围广、活跃频次高和用户众多。对于安全运行，高标准的无人机软硬件系统可靠性和鲁棒性至关重要。无人机运行高度依赖于新技术和外部高技术基础设施。其中，低空公共航路网（又称低空“天路”）是一种保障低空无人机安全和高效运行的关键新型基础设施。深入研究与推进低空“天路”为核心的无人机应用基础设施建设对于发展城市空中交通网、助力智慧交通发展非常有意义。文章在梳理无人机应用关键基础设施的基础上，进行了基于低空“天路”的新型基础设施建设的未来展望。 相似文献
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智能车辆是智能交通系统研究的热点领域,开展智能车辆的障碍物检测技术研究,是车辆辅助驾驶及无人驾驶的关键技术之一。随着计算机硬件的快速发展,计算性能不断提高,一些新的算法或方法也不断被提出,而障碍物检测技术仍然是智能车辆研究的重点和难点。文章介绍了双目立体视觉相关的一些理论,对近年来的一些基于双目立体视觉的障碍物检测方法分析并进行综述。 相似文献
17.
《Journal of The Franklin Institute》2022,359(18):10331-10354
Industrial telerobotics system (ITS) enables robots to implement remote, dangerous, and complicated manufacturing tasks by incorporating human intelligence. Higher requirements are put forward for the working speed and performance of ITS. However, for ITS, only asymptotic convergence can be realized by existing control strategies, which have poor robust performance. In view of these theoretical and practical problems, this article addresses fixed-time synchronization control issue for a class of ITS with unknown parametric/nonparametric uncertainties and external disturbances. Satisfactory force and position performance can be achieved with the designed novel control algorithms. Firstly, based on the impedance control frame, two reference models are constructed for the master and slave robots by considering force and position signals transmission between master and slave, respectively. Then, a new adaptive sliding mode disturbance observer (ASMDO) is developed to realize the estimation of external disturbances and system uncertainties in higher speed and higher precision under relaxed assumption. Moreover, a novel continuous fixed-time control (CFTC) scheme is developed to guarantee good position and force synchronization performances, simultaneously. Finally, the effectiveness of the suggested control method is validated with simulations and experimental results. 相似文献
18.
Yongyuan Yu Jun-e Feng Biao Wang Peihe Wang 《Journal of The Franklin Institute》2018,355(12):5324-5335
Derived from a simplified intelligent traffic control system, sampled-data controllability and stabilizability of Boolean control networks are considered. Compared with the existing case of uniform (periodic) sampling in Boolean control networks, the nonuniform one is more general. Using linear span with integral coefficients, the distribution of sampling points can be obtained. Then by constructing novel systems, some necessary and sufficient conditions are proposed to determine sampled-data controllability and stabilizability. Finally, two illustrative examples, which are on apoptosis networks and traffic control systems, respectively, are worked out to show the effectiveness of the obtained results. 相似文献
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物联网技术的飞速发展为提升高速公路网运行管理效率提供了全新的解决思路。首先针对重庆高速公路网发展概况与运行管理现状,综合分析重庆高速公路网运行管理信息系统现状及在系统结构、信息共享、信息流转、联动管控中存在的问题,提出加强高速公路网运行管理信息化建设的必要性;然后,结合物联网技术发展的大环境,提出基于物联网的高速公路网运行管理信息系统的建设目标和思路,重点分析路网运行管理的6类18项应急事件的联动管理功能需求和工作流程,据此设计包括交通信息感知层、网络传输层和交通管理与服务应用层的重庆高速公路网运行管理信息平台物联网架构;最后,对保障重庆高速公路网运行管理信息平台有效运行的管理体系进行研究。 相似文献
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鉴于学术界对于交通中心节点的评估识别还存在指标体系考虑因子不足、计算方法导致信息损失等问题,且未见全国层面的区县级精度研究,构建涵盖政治战略、社会经济、交通运输、国土生态等方面共18个指标的中心节点评估指标体系,基于我国全国区县级单元,利用专家赋值法和多维魔方法开展更全面、更详细、更精准的交通节点评估识别,以提高综合交通的整体运转效率,实现交通与国土空间的协同发展。评估识别出687个区县级中心节点并分为3个级别,这些中心节点具有良好的全国性服务与覆盖水平。总体上看,经济越发达、区域面积越大的省份拥有较多的中心节点,土地面积在中心节点筛选中作用凸显;经济较发达、区域面积较小的省份拥有的中心节点占单元总数的比例较高,经济因素的作用更明显。 相似文献