KNOWLEDGE-BASED GEOGRAPHIC INFORMATION SYSTEM FOR SAFETY ANALYSIS AT RAIL-HIGHWAY GRADE CROSSINGS
The development of a knowledge-based geographic information system for managing and analyzing safety-related information for rail-highway grade crossings is discussed in this paper. The allocation of federal funding for safety improvements at public, at-grade rail-highway crossings is made based on the performance of the states with respect to accident reduction. The motivation behind the work was to establish guidelines and to develop an integrated system that would ultimately result in accident reduction through better access and management of safety information. This was accomplished by using geographic information system (GIS) technology and decision support tools through integration of the GIS application with a statistical model and a knowledge-based expert system (KBES). The work continued an ongoing project that resulted in the integration of rail-highway grade crossing safety data from various sources, such as the FRA and Delaware Department of Transportation (DelDOT), into a data base management system. The selection and integration of the U.S. Department of Transportation (USDOT) accident prediction model into the system was also required. This paper describes the conversion of rail-highway grade crossing safety attribute data into a GIS-acceptable format, the development of the GIS application including the spatial analysis, visual display, and query capabilities, and the development of a KBES to account for site-specific and qualitative factors. The KBES is also capable of suggesting safety upgrade action(s) at the crossing. Interfacing of the KBES and the program for the USDOT model with the GIS and the framework of the complete package developed for safety analysis at rail-highway grade crossings are also discussed in the paper.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/0309061636
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Supplemental Notes:
- This paper appears in Transportation Research Record No. 1497, Artificial Intelligence and Geographical Information. Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
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Authors:
- Panchanathan, Sriram
- Faghri, Ardeshir
- Publication Date: 1995
Language
- English
Media Info
- Features: Figures; References; Tables;
- Pagination: p. 91-100
- Monograph Title: Artificial intelligence and geographical information
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Serial:
- Transportation Research Record
- Issue Number: 1497
- Publisher: Transportation Research Board
- ISSN: 0361-1981
Subject/Index Terms
- TRT Terms: Databases; Expert systems; Geographic information systems; Information management; Integrated systems; Management; Railroad grade crossings; Research; Safety
- Uncontrolled Terms: Management systems
- Old TRIS Terms: Safety research
- Subject Areas: Administration and Management; Data and Information Technology; Highways; Operations and Traffic Management; Railroads; Research; Safety and Human Factors; I80: Accident Studies;
Filing Info
- Accession Number: 00714948
- Record Type: Publication
- ISBN: 0309061636
- Files: TRIS, TRB
- Created Date: Dec 20 1995 12:00AM