大跨径混凝土桥梁施工挠度监测数据采集的自动化方案

针对大跨径预应力混凝土桥梁施工挠度监测中数据采集工作量大的特点。提出了利用PC-E500电子记簿采集外业数据。利用Delphi语言编程将数据导入Excel表格并从Excel表格中提取数据的自动化方案。     

智能压路机控制系统数据通信的实现

介绍了CAN总线及CANopen协议的技术特点,详细阐述了基于CAN总线技术的智能压路机控制系统数据通信的实现,使之达到了智能压路机的设计要求.     

帕萨特B5轿车电路-自动变速器控制系统(Ⅰ)

在帕萨特B5轿车布线图的基础上改画成该车电路原理图——自动变速器控制系统,并介绍该系统的主要功能,自动变速器故障码及其读取方法,自动变速器测量数据块及其读取方法。     

管桩加固软土路基桩土相对位移分析

管桩加固软土路基作为一种新的处理方式可以有效地解决路基稳定和总沉降的问题,但是桩顶平面会产生较大的桩土相对位移。对桩土相对位移的形成机理进行分析,利用桩土相对位移的原型观测试验,从变形的角度研究桩土协同工作性状,同时提出了桩土相对位移的控制方法。     

城市高架桥之高独柱墩横向位移探讨

结合城市高架高独柱墩顶部发生横向位移这一现象,对高独柱墩顶部横向荷载产生的原因进行初步分析,并应用三维非线性屈曲分析,阐述组合荷载所引起的大变形及混凝土徐变效应与墩顶横向位移之间的关系,提出了设计、施工类似结构时应注意的事项。     

基于BIM的设计管理

针对BIM技术应用的现状和现阶段国内企业的BIM设计管理工作中存在的问题,探索研究基于BIM设计特点的管理系统。通过构建高效的BIM软件设计工作环境、优化基于BIM设计特点的管理流程、建立设计项目数据框架的方式,达到BIM设计管理系统的高效性和协同性。     

Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.     

西南红层软岩地区铁路滑坡形成机理分析及治理措施

红层软岩地区铁路工程建设中滑坡问题突出。本文结合西南地区一铁路红层滑坡治理工程,利用该地区红层滑坡的现场调查结果,从红层软岩特性、地层岩性、地质地貌、水文地质条件、深孔位移监测数据等多方面对该地区铁路滑坡形成机理进行分析,并论述红层滑坡与一般滑坡的不同点,分析红层软岩岩体力学特性、地层主要成分以及红层软岩中的粉砂质泥岩在不同风化程度下的力学特性。根据分析结果提出治理措施,并对治理措施进行评价。总结得出地层岩性、地质水文、人为因素是导致红层滑坡病害发生的主要因素。     

Travel time estimation from sparse floating car data with consistent path inference: A fixed point approach

Estimation of urban network link travel times from sparse floating car data (FCD) usually needs pre-processing, mainly map-matching and path inference for finding the most likely vehicle paths that are consistent with reported locations. Path inference requires a priori assumptions about link travel times; using unrealistic initial link travel times can bias the travel time estimation and subsequent identification of shortest paths. Thus, the combination of path inference and travel time estimation is a joint problem. This paper investigates the sensitivity of estimated travel times, and proposes a fixed point formulation of the simultaneous path inference and travel time estimation problem. The methodology is applied in a case study to estimate travel times from taxi FCD in Stockholm, Sweden. The results show that standard fixed point iterations converge quickly to a solution where input and output travel times are consistent. The solution is robust under different initial travel times assumptions and data sizes. Validation against actual path travel time measurements from the Google API and an instrumented vehicle deployed for this purpose shows that the fixed point algorithm improves shortest path finding. The results highlight the importance of the joint solution of the path inference and travel time estimation problem, in particular for accurate path finding and route optimization.     

A generic data assimilation framework for vehicle trajectory reconstruction on signalized urban arterials using particle filters

With trajectory data, a complete microscopic and macroscopic picture of traffic flow operations can be obtained. However, trajectory data are difficult to observe over large spatiotemporal regions—particularly in urban contexts—due to practical, technical and financial constraints. The next best thing is to estimate plausible trajectories from whatever data are available. This paper presents a generic data assimilation framework to reconstruct such plausible trajectories on signalized urban arterials using microscopic traffic flow models and data from loops (individual vehicle passages and thus vehicle counts); traffic control data; and (sparse) travel time measurements from whatever source available. The key problem we address is that loops suffer from miss- and over-counts, which result in unbounded errors in vehicle accumulations, rendering trajectory reconstruction highly problematic. Our framework solves this problem in two ways. First, we correct the systematic error in vehicle accumulation by fusing the counts with sparsely available travel times. Second, the proposed framework uses particle filtering and an innovative hierarchical resampling scheme, which effectively integrates over the remaining error distribution, resulting in plausible trajectories. The proposed data assimilation framework is tested and validated using simulated data. Experiments and an extensive sensitivity analysis show that the proposed method is robust to errors both in the model and in the measurements, and provides good estimations for vehicle accumulation and vehicle trajectories with moderate sensor quality. The framework does not impose restrictions on the type of microscopic models used and can be naturally extended to include and estimate additional trajectory attributes such as destination and path, given data are available for assimilation.