Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/6984

Title: Profiling of high-frequency accident locations by use of association rules
Authors: GEURTS, Karolien
WETS, Geert
Issue Date: 2003
Citation: Transportation research record, 1840. p. 123-130
Abstract: In Belgium, traffic safety is one of the government's highest priorities. The identification and profiling of black spots and black zones (geographical locations with high concentrations of traffic accidents) in terms of accident-related data and location characteristics must provide new insights into the complexity and causes of road accidents, which, in turn, provide valuable input for governmental actions. Association rules were used to identify accident-related circumstances that frequently occur together at high-frequency accident locations. Furthermore, these patterns were analyzed and compared with frequently occurring accident-related characteristics at low-frequency accident locations. The strength of this approach lies with the identification of relevant variables that make a strong contribution toward obtaining a better understanding of accident circumstances and the discerning of descriptive accident patterns from more discriminating accident circumstances to profile black spots and black zones. This data-mining algorithm is particularly useful in the context of large data sets for road accidents, since data mining can be described as the extraction of information from large amounts of data. the results showed that human and behavioral aspects are of great importance in the analysis of frequently occurring accident patterns. These factors play an important role in identifying traffic safety problems in general. However, the accident characteristics that were the most discriminating between, high-frequency and low-frequency accident locations are mainly related to infrastructure and location.
URI: http://hdl.handle.net/1942/6984
DOI: 10.3141/1840-14
ISI #: 000189447100014
ISSN: 0361-1981
Category: A1
Type: Journal Contribution
Validation: ecoom, 2005
Appears in Collections: Research publications

Files in This Item:

There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.