Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency
Joint Authors
Muneeb Abid, Malik
Zou, Yajie
Tang, Jinjun
Zhang, Yue
Wu, Lingtao
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-09
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Annual fatal traffic accident data often demonstrate time series characteristics.
The existing traffic safety analysis approaches (e.g., negative binomial (NB) model) often cannot accommodate the dynamic impact of factors in fatal traffic accident data and may result in biased parameter estimation results.
Thus, a linear Poisson autoregressive (PAR) model is proposed in this study.
The objective of this study is to apply the PAR model to analyze the dynamic impact of traffic laws and climate on the frequency of fatal traffic accidents occurred in a large time span (from 1975 to 2016) in Illinois.
Besides, the NB model, NB with a time trend, and autoregressive integrated moving average model with exogenous input variables (ARIMAX) are also developed to compare their performances.
The important conclusions from the modelling results can be summarized as follows.
(1) The PAR model is more appropriate for analyzing the dynamic impacts of traffic laws on annual fatal traffic accidents, especially the instantaneous impacts.
(2) The law that allows motorcycles and bicycles to proceed on a red light following the rules applicable after a “reasonable period of time” leads to an increase in the frequency of annual fatal traffic accidents by 14.98% in the short term and 30.69% in the long term.
The climate factors such as average temperature and precipitation concentration period have insignificant impacts on annual fatal traffic accidents in Illinois.
Thus, the modelling results suggest that the PAR model is more appropriate for annual fatal traffic accident data and has an advantage in estimating the dynamic impact of traffic laws.
American Psychological Association (APA)
Zhang, Yue& Zou, Yajie& Wu, Lingtao& Tang, Jinjun& Muneeb Abid, Malik. 2020. Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1180703
Modern Language Association (MLA)
Zhang, Yue…[et al.]. Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency. Journal of Advanced Transportation No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1180703
American Medical Association (AMA)
Zhang, Yue& Zou, Yajie& Wu, Lingtao& Tang, Jinjun& Muneeb Abid, Malik. Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1180703
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1180703