Investigating Peltzman effects in adopting mandatory seat belt laws in the US: Evidence from non-occupant fatalities

Lv, Jinpeng; Lord, Dominique; Zhang, Yunlong; Chen, Zhi

doi:10.1016/j.tranpol.2015.06.012

Cited by 13 publications

(10 citation statements)

References 17 publications

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“…Before presenting the model, the linear autoregressive (AR) process is firstly introduced. e AR model describes the random variables at some time by using the linear combination of random variables at earlier time as equation (1). It is a common form of time series.…”

Section: Methodsmentioning

confidence: 99%

“…Among many factors, the traffic law is considered an effective measure to reduce the severity of injuries and the number of fatalities as a means of macroeconomic regulation and control. Some existing studies have analyzed the impact of certain traffic laws on the number of traffic accidents, such as the seat belt law [1], driving under the influence (DUI) law [2,3], and alcohol control law [4]. However, the dynamic impacts of these traffic laws on traffic accidents have not been adequately studied.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency

Zhang

Zou

et al. 2020

Journal of Advanced Transportation

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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.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency

Zhang

Zou

et al. 2020

Journal of Advanced Transportation

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“…Second, drivers may feel that enforcement is only limited to major highways, thus, they are unlikely to receive a violation. Finally, as seatbelt use becomes more prevalent, drivers may underestimate the risk of injury from distracted driving because of increased protection “Peltzman effect” (Lv et al 2015 ). Further research is needed to explore the underlying causes and possible interventions to reduce mobile phone use among drivers.…”

Section: Discussionmentioning

confidence: 99%

The effectiveness of introducing detection cameras on compliance with mobile phone and seatbelt laws: a before-after study among drivers in Riyadh, Saudi Arabia

et al. 2018

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BackgroundBecause Saudi Arabia (SA) has struggled with the burden of Road Traffic Injuries (RTIs) for decades, a new automated citations system was implemented in 2018 to improve compliance with seatbelt and mobile phone laws. Therefore, the purpose of this study is to evaluate the impact of the system on the prevalence of seatbelt and mobile phone use among drivers in Riyadh. This is an observational study conducted between 2017 and 2018. A Pre-Post evaluation was employed to determine the impact of a camera detection system on seatbelt and mobile phone use. Two research coordinators collected the observations at several highways and inner intersections around Riyadh (n = 3400). We evaluated differences in the prevalence of seatbelt and mobile phone use across the two time periods using a chi-2 test. In addition, we evaluated the association between the new intervention and traffic violation using a logistic regression model.ResultsThe overall seatbelt compliance increased significantly from 33.9% (95% CI = 31.7–36.2) to 75.8% (95% CI = 73.7–77.8; P < 0.01). In addition, mobile phone use declined significantly from 13.8% (95% CI = 12.2–15.5) to 9.8 (95% CI = 8.8–9.1; P < 0.01). We found the detection system to be associated with a significant increase in seatbelt use and also a significant decline in mobile phone use while driving. After implementing the intervention, drivers were 6.1 times (OR = 6.1, 95% CI = 5.2–7.0) more likely to wear seatbelts than before the technology went into effect. Similarly, drivers observed after implementing the cameras were 32% (OR = 0.68, 95% CI = 0.55,0.84) less likely to use mobile phones while driving than those seen prior to the intervention.ConclusionsThis study found a significant reduction in traffic violations following the implementation of a camera detection system in Riyadh. This positive impact is evidence for the role preventative structural strategies play to improve traffic safety and reduce RTI in SA. Therefore, these findings may facilitate further support for policymakers that public health interventions play a significant role to improve traffic safety. Seatbelt and mobile phone use while driving should continue to be monitored, and traffic police may evaluate whether increasing the fine is associated with a significant reduction in traffic violations and associated crashes.

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“…Hence, the drivers are less concerned and worried about traffic safety. Another explanation is that drivers believe if they are in danger, CV technology would promptly remind them how to avoid a crash; thus, they have a lower risk perception about dangerous situations [58].…”

Section: A Differences In the Responses Between Non-cv And CV Enviromentioning

confidence: 99%

Intention of Risk-Taking Behavior at Unsignalized Intersections Under the Connected Vehicle Environment

et al. 2021

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With the rapid emergence of connected vehicle (CV) technologies, there is a shortage of research to understand CV technology's effect on drivers' risk-taking behavioral intentions. This paper aims to analyze driver responses to the real-time information by comparing their reactions to driving intentions between the CV and non-CV environments. A multi-group structural equation model (SEM) is employed to explore the heterogeneity in the relationships between behavioral intentions, attitudes, subjective norms, perceived behavioral control, and risk perceptions under the two different environments. This study reveals two key findings: 1) regarding driver responses to the theory of planned behavior (TPB) model, there are significant differences in attitudes and risk perceptions between the CV and non-CV environments; 2) irrespective of driving environments, risk-taking behavioral intentions are directly related to perceived behavioral control and risk perceptions. While intentions are directly related to attitudes but not associated with subjective norms under the non-CV environment. In contrast, intentions are directly related to subjective norms but not associated with attitude under the CV environment. The findings provide a theoretical basis for using TPB to evaluate CV technology's effects and understanding the differences between the CV and non-CV environments. INDEX TERMS Connected vehicles, Risky driving intentions, Structural equation model, Theory of planned behavior, Unsignalized intersections.

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Investigating Peltzman effects in adopting mandatory seat belt laws in the US: Evidence from non-occupant fatalities

Cited by 13 publications

References 17 publications

Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency

Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency

The effectiveness of introducing detection cameras on compliance with mobile phone and seatbelt laws: a before-after study among drivers in Riyadh, Saudi Arabia

Intention of Risk-Taking Behavior at Unsignalized Intersections Under the Connected Vehicle Environment

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