Macro Impact Factors of Road Traffic Accidents and Prediction Analysis of Accident Fatalities

DOI

10.2991/978-94-6463-610-9_15How to use a DOI?

Keywords

multiple linear regression; traffic accident; death toll; macro impact factors

Abstract

This study aims to analyze and predict the number of deaths in road traffic accidents through multiple linear regression models, with a focus on examining macro influencing factors. The article collects multiple macroeconomic and social variables that affect the mortality rate of traffic accidents, including Gross Domestic Product (GDP), motor vehicle ownership, road mileage, number of motor vehicle drivers, and year-end total population. Firstly, the data was preprocessed, including missing value processing and outlier detection. Subsequently, a multiple linear regression model was used to model the data, and the assumptions of the model were validated. Through stepwise regression analysis, significant influencing factors were screened and the final regression model was constructed. The goodness of fit and predictive performance of the model are evaluated through cross validation and independent test sets. The results show that the number of motor vehicles, the length of highways open to traffic, and the number of motor vehicle drivers are the main macro factors affecting the number of deaths in traffic accidents. Based on this model, we can effectively predict the number of deaths in traffic accidents in the future, providing scientific basis for traffic management departments to formulate corresponding preventive measures. Research has shown that multiple regression models have high application value and accuracy in analyzing traffic accidents at the macro level.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Runze Li
AU  - Baohua Guo
PY  - 2024
DA  - 2024/12/16
TI  - Macro Impact Factors of Road Traffic Accidents and Prediction Analysis of Accident Fatalities
BT  - Proceedings of the 2024 International Conference on Rail Transit and Transportation (ICRTT 2024)
PB  - Atlantis Press
SP  - 135
EP  - 141
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-610-9_15
DO  - 10.2991/978-94-6463-610-9_15
ID  - Li2024
ER  -