National Data Warehouse

Author:

Viti Francesco1,Hoogendoorn Serge P.1,Immers Lambertus H. (Ben)2,Tampère Chris M. J.2,Lanser Sascha Hoogendoorn3

Affiliation:

1. Transportation and Planning Department, Delft University of Technology, Stevinweg 1, P.O. Box 5048, 2600 GA, Delft, Netherlands, and Department of Mechanical Engineering, Katholieke Universiteit Leuven Belgium.

2. Department of Mechanical Engineering, Katholieke Universiteit Leuven, Celestijnenlaan 300A, P.O. Box 2422, 3001 Heverlee, Belgium.

3. Rijkswaterstaat AVV, Dutch Transport Research Centre, Rotterdam, Netherlands.

Abstract

Every day, traffic managers and road users use different sources of information on the current state of the road network in their decision process. The efficiency of these decisions strongly depends on how accurate, reliable, and timely the available information is. Moreover, the data collected are typically scattered in space and time; large areas are usually unmonitored, and data quality is undependable. Within this view, the distribution of a unique data set that contains sufficient levels of quality over the whole network may improve the way information is provided to the user and improve the effectiveness of management strategies. The need for guaranteed standard levels of data quality for road authorities and service providers motivated the establishment of the National Data Warehouse project to provide traffic information as well as information on the status of the road network system as a whole. This information is extended to a basic network level, which allows road authorities or service providers to combine this information with their own data set and obtain a broader view of the problems that occur on the network they manage or monitor. The requirements that such a data bank should satisfy—namely, the accuracy and reliability of information (which depend on the spatial location and aggregation time)—were investigated. The impact of these elements has been quantified through theoretical and numerical analysis, showing that both elements strongly affect good estimation and prediction of travel times and network states, especially under variable traffic conditions.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Reference5 articles.

1. Traffic flooding the low countries: How the Dutch cope with motorway congestion

2. Filekosten op het Nederlaudse Hoofdwegennet in 1997. McKinsey & Company for AVV (former Dutch Ministry of Transport), Rijswijk, Netherlands, 1997.

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Comparison of different Bayesian methods for estimating error bars with incident duration prediction;Journal of Intelligent Transportation Systems;2021-03-10

2. A Review of European National Access Points for Intelligent Transport Systems Data;2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC);2020-09-20

3. Geospatial Analysis and the Internet of Things;ISPRS International Journal of Geo-Information;2018-07-10

4. A METHOD AND APPLICATION TO IDENTIFY REASONS FOR DECREASING VEHICLES’ DRIVING SPEED IN CITIES;Scientific Journal of Silesian University of Technology. Series Transport;2018-03-30

5. Improvement of Network Performance by In-Vehicle Routing Using Floating Car Data;Journal of Advanced Transportation;2017

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3