Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/28091
Title: Investigation of helmet use behavior of motorcyclists and effectiveness of enforcement campaign using CART approach
Authors: ADNAN, Muhammad 
Gazder, U.
Issue Date: 2019
Publisher: ELSEVIER SCI LTD
Source: International Association of Traffic and Safety Sciences Research, 43(3), p. 195-203.
Abstract: Use of the helmet is beneficial in reducing the severity of injuries and avoiding fatalities for motorcyclists, therefore, legislation exists in almost all countries. In practice, the situation is different regarding the helmet use, especially in the developing countries. This paper investigates the helmet use behavior of motorcyclists in Karachi, Pakistan. It determines the significant factors affecting the helmet use in Karachi (Pakistan) and recommending effective campaign measures to promote helmet use. It is vital in relation to the exponential growth of motorcycle users and poor enforcement of traffic rules. Repeated cross-sectional data collected before (n = 226) and after (n = 277) the helmet use enforcement campaign is analyzed using univariate and non-parametric classification and regression tree (CART) techniques. A significant number of motorcyclists do not hold a driving license and CART analysis highlighted the significance of this variable along with exposure to the road environment (measured as daily usage of motorcycle) to explain helmet use. Campaign effects are found temporary, therefore, serious efforts are required to design coherent and structured awareness and enforcement programs.
Keywords: Helmet use behavior; Enforcement campaign; Repeated cross-sectional survey; CART; Karachi
Document URI: http://hdl.handle.net/1942/28091
ISSN: 0386-1112
e-ISSN: 2210-4240
DOI: 10.1016/j.iatssr.2019.02.001
ISI #: WOS:000485807200008
Rights: 2018 International Association of Traffic and Safety Sciences. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Category: A1
Type: Journal Contribution
Validations: vabb 2022
Appears in Collections:Research publications

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