Analyzing the effectiveness of implemented highway safety laws for traffic safety across U.S. states

ABSTRACT Since highway safety laws vary greatly from state to state in the U.S., there is a need to analyze the effectiveness and performances of the implemented highway safety laws. The random-parameter zero-truncated negative binomial (RZTNB) models are proposed to analyze the effects of highway safety laws on fatal crashes at state levels. The results show that the proposed models are useful in describing the relationships between the fatal crashes and the explanatory variables with better goodness of fit. By accounting for the heterogeneities, the RZTNB model outperforms the negative binomial model and reveals new insights. The findings indicate that (1) compared to the secondary ban, the primary handheld cellphone ban is more effective; (2) establishing reasonable and acceptable speed limits can enhance the traffic safety; and (3) the implemented speed camera system and ignition interlock device have weaknesses and alternative methods should be considered when upgrading laws and regulations.

[1]  Max Cameron,et al.  Controversies and Speed Cameras: Lessons Learnt Internationally , 2005, Journal of public health policy.

[2]  Richard Tay.  Speed Cameras Improving Safety or Raising Revenue , 2010 .

[3]  Randy W. Elder,et al.  Effectiveness of ignition interlocks for preventing alcohol-impaired driving and alcohol-related crashes: a Community Guide systematic review. , 2011, American journal of preventive medicine.

[4]  Xiang Liu,et al.  Accident Analysis and Prevention Analysis of U.s. Freight-train Derailment Severity Using Zero-truncated Negative Binomial Regression and Quantile Regression , 2022 .

[5]  M J Maher,et al.  Are speed enforcement cameras more effective than other speed management measures? The impact of speed management schemes on 30 mph roads. , 2005, Accident; analysis and prevention.

[6]  Kristy B Arbogast,et al.  An evaluation of the effectiveness of forward facing child restraint systems. , 2004, Accident; analysis and prevention.

[7]  Robert D Foss,et al.  Effect of North Carolina's restriction on teenage driver cell phone use two years after implementation. , 2012, Accident; analysis and prevention.

[8]  Peter D. Loeb,et al.  The Cell Phone Effect on Motor Vehicle Fatality Rates: a Bayesian and Classical Econometric Evaluation , 2010 .

[9]  Sheldon Howard Jacobson,et al.  Evaluating the impact of legislation prohibiting hand-held cell phone use while driving , 2010 .

[10]  Boris Antić,et al.  Impact of the new road traffic safety law on the number of traffic casualties in Serbia , 2011 .

[11]  Tarek Sayed,et al.  Accident prediction models with random corridor parameters. , 2009, Accident; analysis and prevention.

[12]  V Siskind.  Does license disqualification reduce reoffence rates? , 1996, Accident; analysis and prevention.

[13]  Andrew M. Welki,et al.  How highway safety regulations and enforcement activities affect subcategories of motor vehicle fatalities , 2009 .

[14]  Stephen H Richards,et al.  Assessment of the effects of highway geometric design features on the frequency of truck involved crashes using bivariate regression , 2015 .

[15]  A. Wagenaar,et al.  Effects of drivers' license suspension policies on alcohol-related crash involvement: long-term follow-up in forty-six states. , 2007, Alcoholism, clinical and experimental research.

[16]  Rune Elvik,et al.  The deterrent effect of increasing fixed penalties for traffic offences: the Norwegian experience. , 2007, Journal of safety research.

[17]  Douglas M. King,et al.  Assessing the long term benefit of banning the use of hand-held wireless devices while driving , 2012 .

[18]  Andrew M. Welki,et al.  The effect of cell phones on international motor vehicle fatality rates: A panel-data analysis , 2014 .

[19]  Michael A. Regan,et al.  Text messaging amongst New Zealand drivers: Prevalence and risk perception , 2012 .

[20]  Oh Hoon Kwon,et al.  Evaluating the effectiveness of the law banning handheld cellphone use while driving , 2014 .

[21]  Michael J Kallan,et al.  Effect of booster seat laws on appropriate restraint use by children 4 to 7 years old involved in crashes. , 2007, Archives of pediatrics & adolescent medicine.

[22]  Fred L. Mannering,et al.  The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives , 2010 .

[23]  Kangwon Shin,et al.  Evaluation of the Scottsdale Loop 101 automated speed enforcement demonstration program. , 2009, Accident; analysis and prevention.

[24]  Linda Mountain.  Costing lives or saving lives? A detailed evaluation of the impact of speed cameras on safety. , 2004 .

[25]  Breno Sampaio,et al.  Identifying peer states for transportation policy analysis with an application to New York's handheld cell phone ban , 2014 .

[26]  Amy L. Tobler,et al.  General deterrence effects of U.S. statutory DUI fine and jail penalties: long-term follow-up in 32 states. , 2007, Accident; analysis and prevention.

[27]  Paul Atchley,et al.  The choice to text and drive in younger drivers: behavior may shape attitude. , 2011, Accident; analysis and prevention.

[28]  Michael J Kallan,et al.  Effectiveness of child safety seats vs seat belts in reducing risk for death in children in passenger vehicle crashes. , 2006, Archives of pediatrics & adolescent medicine.

[29]  Andrew M. Welki,et al.  The impact of highway safety regulation enforcement activities on motor vehicle fatalities , 2007 .

[30]  C Raymond Bingham,et al.  The impact of Michigan's text messaging restriction on motor vehicle crashes. , 2014, The Journal of adolescent health : official publication of the Society for Adolescent Medicine.

[31]  Masao Ichikawa,et al.  Effects of Increasing Child Restraint Use in Reducing Occupant Injuries Among Children Aged 0–5 Years in Japan , 2015, Traffic injury prevention.

[32]  Anne T McCartt,et al.  Evaluation of automated speed enforcement on Loop 101 freeway in Scottsdale, Arizona. , 2008, Accident; analysis and prevention.

[33]  Fred L Mannering,et al.  A note on modeling vehicle accident frequencies with random-parameters count models. , 2009, Accident; analysis and prevention.

[34]  Junwook Chi,et al.  Are cell phone laws in the U.S. effective in reducing fatal crashes involving young drivers , 2013 .

[35]  Lawrence E Decina,et al.  Child restraint system use and misuse in six states. , 2005, Accident; analysis and prevention.

[36]  Nang-Ngai Sze,et al.  Effective measures for combating drink-driving offenses: an attitudinal model for Hong Kong , 2014 .

[37]  Anne T McCartt,et al.  Effects of Washington, D.C. Law on Drivers' Hand-Held Cell Phone Use , 2006, Traffic injury prevention.

[38]  Mauro D'Apuzzo,et al.  Safety Evaluation of Automated Section Speed Enforcement System , 2012 .

[39]  MA Harrison,et al.  College students' prevalence and perceptions of text messaging while driving. , 2011, Accident; analysis and prevention.

[40]  Andy H. Lee,et al.  Truncated negative binomial mixed regression modelling of ischaemic stroke hospitalizations , 2003, Statistics in medicine.

[41]  L E Decina,et al.  Increasing child safety-seat use and proper use among toddlers. Evaluation of an enforcement and education program. , 1994, Accident; analysis and prevention.

[42]  Kristy B Arbogast,et al.  Recent trends in child restraint practices in the United States. , 2004, Pediatrics.

[43]  Stephen H Richards,et al.  Examining the Influence of Speed Limits for Multilane Highways with Curbs and Gutters , 2014 .

[44]  Anne T McCartt,et al.  Long-Term Effects of Handheld Cell Phone Laws on Driver Handheld Cell Phone Use , 2010, Traffic injury prevention.

[45]  Rune Elvik,et al.  Effects on Accidents of Automatic Speed Enforcement in Norway , 1997 .