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Transportation Research Record

Publication date: 2008-12-01
Volume: 2049 Pages: 176 - 185
Publisher: Transportation Research Board, Commission on Sociotechnical Systems, National Research Council, National Academy of Sciences

Author:

Viti, Francesco
Hoogendoorn, SP ; Immers, LH ; Tampère, Chris

Keywords:

CIB_TRAFFIC, Science & Technology, Technology, Engineering, Civil, Transportation, Transportation Science & Technology, Engineering, 0905 Civil Engineering, 1205 Urban and Regional Planning, 1507 Transportation and Freight Services, Logistics & Transportation, 3509 Transportation, logistics and supply chains, 4005 Civil engineering

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.