Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 38, 06 June 2024
Open
Access | Article
Research on the prediction of traffic accident by linear regression
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Abstract
Traffic accident is getting increasingly serious. Although previous researchers use a variety of methods to predict the traffic accident, there are numerous demerits that need to be improved. This article demonstrates 12 variables that impact the traffic accident with 679 samples of accidents in UK from 2012 to 2014. This paper first analyses the relevance between dependent and independent variables, and also two independent variables to show the correlation between each factor. By using the multiple linear regression, it is concluded that although some independent variables do not have relationship with the dependent variable ‘urban or rural area’, Accident Severity, Number of Casualties, Road Type, Speed limit, Junction Control show significant relationship with the dependent variable. The paper also considers the 95% confidence interval in order to compare the effective density of data. Overall, the prediction of traffic accident is based on a number of factors and a sizable sample of accidents to summarize the impact that traffic accidents bring.
Keywords
Traffic accident, multiple linear regression, confidence interval
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Mathematical Physics and Computational Simulation
- ISBN (Print)
- 978-1-83558-461-3
- ISBN (Online)
- 978-1-83558-462-0
- Published Date
- 06 June 2024
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/38/20240546
- Copyright
- 06 June 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited