Network-level accident-mapping: Distance based pattern matching using artificial neural network
- Submitting institution
-
De Montfort University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11184
- Type
- D - Journal article
- DOI
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10.1016/j.aap.2013.12.001
- Title of journal
- Accident Analysis & Prevention
- Article number
- -
- First page
- 105
- Volume
- 65
- Issue
- -
- ISSN
- 0001-4575
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 16
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper is based on a project commissioned by the UK High-ways Agency to achieve reliable and accurate mapping of traffic accidents onto the correct road segments where the accidents actually occurred. The developed algorithm has been received well by High-ways agency given that they used the algorithm for at least three years to map accidents inaccurately geo-localised. The line of research has been developed further with another project at Loughborough University (Conference Paper) and currently I supervise a PhD student (Fee Waiver) working in accurate geo-localization
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -