Modelling and assessing local area differences in road casualties: a case study in England

Hindle, G. A.; Hindle, Giles; Hindle, T.; Souli, S.

Abstract

The context of this research is the governmental targeting of road casualty reductions in England. Local authorities have a major role to play in achieving such targets and this research explores the relationships between road casualties and local authority characteristics such as population, road networks, traffic, and geography. Regression models are identified for types of road casualty to provide local area expectations against which observed numbers can be compared. A number of issues are identified that raise concerns about the current methods adopted for assessing road safety performances and about the implementation of this approach at local levels. These issues include the large impact on assessments of judgements of casualty severity and of estimates of starting point casualties when estimating reductions over time. This study leads to recommendations for ways in which current approaches to road casualty appraisal might be improved. © 2009 Operational Research Society Ltd. All rights reserved.

Citation

Hindle, G. A., Hindle, G., Hindle, T., & Souli, S. (2009). Modelling and assessing local area differences in road casualties: a case study in England. Journal of the Operational Research Society, 60(6), 781-788. https://doi.org/10.1057/palgrave.jors.2602623

• Journal Article Type: Article
• Acceptance Date: Mar 1, 2008
• Online Publication Date: Dec 21, 2017
• Publication Date: Jun 1, 2009
• Deposit Date: Nov 13, 2014
• Journal: Journal Of The Operational Research Society
• Print ISSN: 0160-5682
• Electronic ISSN: 1476-9360
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 60
• Issue: 6
• Pages: 781-788
• DOI: https://doi.org/10.1057/palgrave.jors.2602623
• Keywords: Marketing; Management Science and Operations Research; Strategy and Management; Management Information Systems
• Public URL: https://hull-repository.worktribe.com/output/468067
• Contract Date: Nov 13, 2014