基于巨磁电阻的车位检测技术研究

在户外进行停车场车位检测容易受到不同外界因素的干扰,从而造成不必要的车位信息错误,给停车场的管理和停车用户带来诸多不便。针对这类户外停车场车位检测的实际要求以及对相关车位检测技术的研究,提出以基于巨磁电阻的车位检测技术作为核心检测技术,即汽车在停放或离开车位时使得地磁场与巨磁电阻之间磁场关系发生的变化来判断车位上车辆的变化,并且配套的设计了基于巨磁电阻检测的硬件系统和软件系统,分别用于停车位的车位检测和车位的显示,同时通过对巨磁电阻灵敏度的调节来更加灵活和准确地进行检测。试验结果表明,相比于其他车位检测技术该车位检测技术拥有更高精度和更强稳定性。      

Increasing the accuracy of loop detector counts using adaptive neural fuzzy inference system and genetic programming

Loop detectors are devices that are most commonly used for obtaining data at intersections. Multiple detectors are usually required to monitor a location, and this reduces the accuracy of detectors for collecting traffic volumes. The purpose of this paper is to increase the accuracy of loop detector counts using Adaptive Neural Fuzzy Inference System (ANFIS) and Genetic Programming (GP) based on detector volume and occupancy. These methods do not need microscopic analysis and are easy to employ. Four approaches for one intersection are used in a case study. Results show that the models can improve intersection detector counts significantly. Results also show that ANFIS produces more accurate counts compared to regression and GP.     

地铁隧道火灾自动报警系统的设计

地铁隧道的特殊环境给火灾探测装置选型带来很多困难,光纤测温系统的出现为解决地铁隧道火灾探测器的设置问题提供了一个很好的选择.分析地铁隧道火灾的原因、特点,针对地铁隧道的环境特点,对火灾探测器的功能、作用和选型进行分析,给出地铁隧道中的火灾自动报警系统的设置方案.     

阿姆斯特丹城市道路线圈检测器布设方法研究

基于宏观基本图(Macroscopic Fundamental Diagram,MFD)的网络交通控制方法受到越来越多的国家的重视,它可以更有效的节约资源和提高效率。然而建立MFD需要以收集网络范围内详细的交通数据为前提,阿姆斯特丹的城市道路错综复杂,若在每个城市道路路段都布设线圈检测器需要巨大的经济支持和维护。基于Vissim的仿真实验的方法,建立阿姆斯特丹的MFD;通过实验方法确定城市道路中对于建立网络MFD起着显著的影响关键路段,为线圈检测器的布设提供了理论依据。     

动态交通信息采集技术比较分析

动态交通信息是ITS各子系统应用的基础和保障,如何获得准确、实时的动态交通信息对ITS的应用效果起着至关重要的作用。因此,有必要在对动态交通信息采集技术进行分类的基础上,对各类动态交通信息采集技术进行比较研究。指出各自的优缺点和适用场合,并对未来的发展方向进行展望。     

舰船水压场频域检测的环境干扰特性分析

舰船水压场以其难于人工模拟性,被作为舰船的重要目标特性广泛应用于水中目标检测中,而对其进行频域检测又是最常用的舰船水压场信号检测方法。复杂多变的海洋环境中,诸多因素都对舰船水压场信号的频域检测性能产生显著影响,文章对在我国沿海不同海域获得的大量环境水压场数据进行分析,得到影响舰船水压场信号频域检测的主要因素,为水中目标探测器设计提供参考。     

Forecasting road traffic conditions using a context-based random forest algorithm

With the ability to accurately forecast road traffic conditions several hours, days and even months ahead of time, both travellers and network managers can take pro-active measures to minimise congestion, saving time, money and emissions. This study evaluates a previously developed random forest algorithm, RoadCast, which was designed to achieve this task. RoadCast incorporates contexts using machine learning to forecast more accurately contexts such as public holidays, sporting events and school term dates. This paper evaluates the potential of RoadCast as a traffic forecasting algorithm for use in Intelligent Transport System applications. Tests are undertaken using a number of different forecast horizons and varying amounts of training data, and an implementation procedure is recommended.     

沥青路面浅层强度探测仪检测参考标准研究

为了使沥青路面浅层强度探测仪SDSAP(Strength Detector of Shallow Asphalt Pavement)能够更好地应用于沥青路面检测评价,针对不同空隙率下的沥青混合料,通过仪器的冲击贯入实验和室内强度试验,初步建立了沥青路面浅层强度探测仪的检测参考标准。     

Length-based vehicle classification using event-based loop detector data

Length-based vehicle classification is an important topic in traffic engineering, because estimation of traffic speed from single loop detectors usually requires the knowledge of vehicle length. In this paper, we present an algorithm that can classify vehicles passing by a loop detector into two categories: long vehicles and regular cars. The proposed algorithm takes advantage of event-based loop detector data that contains every vehicle detector actuation and de-actuation “event”, therefore time gaps between consecutive vehicles and detector occupation time for each vehicle can be easily derived. The proposed algorithm is based on an intuitive observation that, for a vehicle platoon, longer vehicles in the platoon will have relatively longer detector occupation time. Therefore, we can identify longer vehicles by examining the changes of occupation time in a vehicle platoon. The method was tested using the event-based data collected from Trunk Highway 55 in Minnesota, which is a high speed arterial corridor controlled by semi-actuated coordinated traffic signals. The result shows that the proposed method can correctly classify most of the vehicles passing by a single loop detector.     

道路交通网络中移动型检测器最小样本量优化方法研究

本文综合考虑交通流数据的质量及其成本等因素，对服务于ATMS的移动型检测器最小样本量的确定原则进行设计，建立一种基于行程时间估计最小样本量的确定方法，并利用微观仿真模拟软件对城市道路不同服务水平下的交通运行状态进行模拟分析。通过设置不同的检测器样本量方案，并利用优化方法对不同方案采集的交通流信息进行分析，确定合理的移动型检测器最小样本量。