A study of the relation between traffic accidents and election posters
DOI:
https://doi.org/10.55329/htsi5120Keywords:
ARMAX, election posters, risk assessment, time series analysis, Traffic accidentsAbstract
Inattention in traffic is a risk factor for the occurrence of accidents. Elements surrounding traffic could potentially be a safety risk for road users. This study investigates the relation between election posters and traffic accidents using a seasonal autoregressive-moving-average model with exogeneous variables (seasonal ARMAX) correcting for variations in meteorological conditions and general traffic volume indicated through public holidays. Danish traffic accident micro data are used to construct a time series for daily number of accidents in city zones adjusted for probable known accident causes, namely drunk driving, narcotics, drivers deemed unfit to drive, and accidents related to low visibility. Model parameters are determined from Maximum Likelihood estimation on the period from 1 January 1997 to 15 December 2009 with an indicator for general election periods. The presence of general election posters is associated with an increased risk of traffic accidents (p = 0.003), when correcting for meteorological variables and public school holidays. While a causal relation between traffic accidents and the presence of election posters cannot be concluded from the analysis, we find distraction from election posters to be the most likely explanation for the associated increase in traffic accidents. On average, the model indicates that 1.18 additional daily accidents occur for general elections in Denmark. In total, that amounts to 127 additional accidents for the investigated period of time. This study shows that such sudden changes in traffic surroundings are significantly related to increased safety risks which could lead to a better discussion of relevant traffic legislation.
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Author Biographies
Albert Skovgaard Bisgaard, Technical University of Denmark, Denmark | COWI, Denmark
Albert Skovgaard Bisgaard is an industrial PhD student, conducting research at the Technical University of Denmark and COWI A/S. With a specialized focus in stochastic modeling and forecasting, Albert Skovggard Bisgaard has applied mathematical modeling in various projects within energy and pharmaceutical science. His current doctoral research is centered on pioneering data-driven predictive maintenance strategies tailored for the railway sector.
CRediT contribution: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing—original draft, Writing—review & editing.
Magnus Hamann Poulsen, Technical University of Denmark, Denmark
Magnus Hamann Poulsen graduated from the Technical University of Denmark with a Master of engineering in mathematical modeling and computation. Throughout his studies, Magnus Hamann Poulsen has mainly worked with methods in dynamical modeling and time-series modeling. These methods have been applied to various problems with an emphasis on applications in the area of Power-to-X.
CRediT contribution: Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing—original draft, Writing—review & editing.
Anders Stockmarr, Technical University of Denmark, Denmark
Anders Stockmarr is an associate professor at the Department of Applied Mathematics and Computer Science, at the Technical University of Denmark. Anders Stockmarr has worked extensively with aspects of longitudinal modelling, time series and stochastic processes in both teaching and research, and has a keen interest in disseminating scientific results in forms that provide societal benefit.
CRediT contribution: Funding acquisition, Investigation, Methodology, Supervision, Validation, Visualization, Writing—review & editing.
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Copyright (c) 2024 Albert Skovgaard Bisgaard, Magnus Hamann Poulsen, Anders Stockmarr
This work is licensed under a Creative Commons Attribution 4.0 International License.
