Evaluation is a key component of data-driven decision-making and should be standard business practice for transportation safety management programs. Through evaluation, we will know if our efforts are making a difference, or if we should pursue a different course of action. This session will showcase the results of several program evaluations from the U.S. and internationally. Using a hybrid approach, each speaker will have approximately 7 minutes to provide an overview of their research and results. This will be followed immediately by a poster session where you can interact with the speakers for more details about any aspect of their research.
The Road Safety Lessons of Australia
Wesley Marshall, University of Colorado, DenverShow Abstract
Despite similarities to the US in terms of transportation, land use, and culture, Australia kills 5.3 people per 100,000 population on the roads each year, as compared to the US rate of 12.4. Similar trends hold when accounting for distance driven and the number of registered cars. This paper seeks to understand what is behind the road safety disparities between these two countries.
The results suggest that a number of inter-related factors have a role in the better road safety outcomes of Australia as compared to the US. This includes Australia doing a better job with issues such as seat belt usage and impaired driving as well as their efforts to help curb vehicle speeds and reduce exposure. Design-related differences include a much greater reliance on roundabouts and narrower street cross-sections as well as guidelines that encourage self-enforcing roads. Policy-related differences include stronger and more extensive enforcement programs, restrictive licensing programs, and higher driving costs.
Combined with a more urban population and multimodal infrastructure, Australia tends to discourage driving mileage and exposure while encouraging safer modes of transportation such as transit, at least more so than in most of the US. While it is difficult to attribute recent road safety successes to individual policies, Australia continues to expand their lead on the US in terms of safety outcomes and is a country with road safety lessons worthy of consideration.
Serious Road Traffic Injuries in Europe, Lessons from the EU Research Project Safetycube
Wendy Weijermars, SWOV Institute for Road Safety ResearchShow Abstract
Niels Bos, SWOV Institute for Road Safety Research
Annelies Schoeters, Belgian Road Safety Institute
Klaus Machata, Austrian Road Safety Board (KFV)
Ashleigh Filtness, Loughborough University
Jean-Christophe Meunier, Belgian Road Safety Institute
Robert Bauer, Austrian Road Safety Board (KFV)
Nina Nuyttens, Belgian Road Safety Institute
Katherine Perez, Agencia de Salut Publica de Barcelona (ASPB)
Jean-Louis Martin, IFSTTAR
Emmanuelle Dupont, Belgian Road Safety Institute
Laurie Brown, Loughborough University
Heiko Johannsen, MHH
Pete Thomas, Loughborough University
The EU research project SafetyCube pays specific attention to serious road injuries, defined as non-fatal road traffic casualties with a MAIS3+ injury severity rating. By means of surveys, information was collected on current practices concerning the estimation of the number of MAIS3+ casualties and on costs related to serious road injuries in different European countries. Moreover, the effect of differences in practices on the estimated number of MAIS3+ casualties was investigated by applying different methods to the same data. Finally, by means of a literature review, analysis of additional case studies and burden of injury calculations, health impacts of serious road injuries were investigated. This paper presents six main lessons learnt from the SafetyCube research.
Practices concerning the estimation of the number of MAIS3+ casualties differ between countries; some countries apply correction factors to police data, other countries use hospital data and a third group of countries uses linked police and hospital data. Practices also differ concerning the selection of MAIS3+ road traffic injuries within hospital data. Differences in methodology appear to affect the MAIS3+ estimate. Therefore, one should be careful when comparing figures from different countries. The SafetyCube guidelines can support further harmonization.
It is important to reduce the number of serious road injuries because injuries can have major impacts on a casualty’s life and pose a burden to society. About 75% of the MAIS3+ road traffic casualties indicate not to be fully recovered three years post-crash. Moreover, serious road injuries cost countries up to 2.7% of their GDP.
Cost–Benefit Analysis of the Highway Safety Improvement Program Projects in Wisconsin Using Empirical Bayes Method
Yashar Zeinali Farid, University of Wisconsin, MadisonShow Abstract
Yu Song, University of Wisconsin, Madison
Andrea Bill, University of Wisconsin, Madison
David Noyce, University of Wisconsin, Madison
The Highway Safety Improvement Program (HSIP) is a core Federal-aid program which aims to reduce traffic fatalities and serious injuries on all public roads in the United States. HSIP projects implemented in Wisconsin cross a wide spectrum of highway safety improvements and enhancements. The objective of this paper is to present aggregated Benefit-Cost analysis of the HSIP projects implemented between 2007 and 2012 in Wisconsin in order to help determine the best future HSIP projects. The Benefit-Cost ratios are computed based on Before-After and Empirical Bayes methods and the cost of each project is compared with actual benefits observed in terms of reduction in the number of target crashes in the after period. Results indicate that in general, the HSIP projects implemented in Wisconsin yielded an average Benefit-Cost ratio of greater than one. Rumble strips, convert-to-signalized intersection, and guardrail-end-update projects yielded the highest Benefit-Cost ratios while convert-to-interchange and visibility improvement projects resulted in low ratios.
An Assessment of the Effectiveness of Highway Safety Laws to Reduce Crashes: Use of Multivariate Dynamic Tobit Models
Chunjiao Dong, University of Tennessee, KnoxvilleShow Abstract
Shashi Nambisan, University of Alabama
Chunfu Shao, Beijing Jiaotong University
Jin Zeng, University of Tennessee, Knoxville
Highway safety laws aim to influence driver behavior so as to reduce the frequency and severity of crashes, and their outcomes. There are 11 types of highway safety laws in the United States. For one specific highway safety law, it would have different effects on the crashes across severities. Understanding such effects can help policy makers upgrade current laws and hence improve traffic safety. To investigate the effects of highway safety laws on crashes across severities, multivariate models are needed to account for the interdependency issues in crash counts across severities. Based on the characteristics of the dependent variables, multivariate dynamic Tobit (MVDT) models are proposed to analyze crash counts that are aggregated at the state level. Lagged observed dependent variables are incorporated into the MVDT model to account for potential temporal correlation issues in crash data. The state highway safety law related factors are used as explanatory variables and socio-demographic and traffic factors are used as control variables. Three models, a MVDT model with lagged observed dependent variables, a MVDT model with unobserved random variables, and a multivariate static Tobit (MVST) model are developed and compared. The results show that among the investigated models, the MVDT models with lagged observed dependent variables have the best goodness-of-fit. The findings indicate that, compared to the MVST, the MVDT models have better explanatory power and prediction accuracy. The MVDT model with lagged observed variables can better handle the stochasticity and dependency in the temporal evolution of the crash counts and the estimated values from the model are closer to the observed values. The results show that more lives could be saved if law enforcement agencies can make a sustained effort to educate the public about the importance of motorcyclists wearing helmets. Motor vehicle crash-related deaths, injuries, and property damages could be reduced if states enact laws for stricter text messaging rules, higher speeding fines, older licensing age, and stronger graduated licensing provisions. Injury and PDO crashes would be significantly reduced with stricter laws prohibiting the use of hand-held communication devices and higher fines for drunk driving.
In-Depth Investigation of Factors That Contributed to the Decline in Fatalities from 2008 to 2012 in the United States
Srinivas Geedipally, Texas A&M Transportation InstituteShow Abstract
Daniel Blower, UM Transportation Research Institute
Carol Flannagan, UM Transportation Research Institute
Robert Wunderlich, Texas A&M Transportation Institute
Dominique Lord, Texas A&M Transportation Institute
Between 2005 and 2011, peak to trough, the number of traffic fatalities in the United States declined by 11,031, from 43,510 in 2005 to 32,479 in 2011. Most of the dramatic decline occurred from 2008 to 2012 which also coincided with the great economic recession and aftermath. The objective of this study is to provide a multidisciplinary analysis of the relative influence of the types of factors that contributed to this decline in the number of highway fatalities and fatality rates from 2008 to 2012. Two basic approaches were used to analyze the factors that were associated with the drop in traffic fatalities. The first approach developed a set of count models, using negative binomial models to examine the associations between predictors and raw fatality counts. The second approach, which is used to validate the first approach, used a log-change regression model, to examine the association between the change in predictor variables in one year with the change in the outcome variable (traffic fatalities) in the following year. The most significant contributors to the drop in traffic fatalities were the substantial increase in teen and young adult unemployment, decreased in beer consumption, and reduction in GDP/capita income. Vehicle design improvements also contributed to the decline significantly, as did the decline in rural vehicle-miles traveled (VMT) and increased strictness of DUI laws. State highway spending was not a significant contributor to the drop; the effect of changes in infrastructure was likely more cumulative and longer term. Changes in safety belt use rates and fuel prices were not significant contributors to the decline because they did not change much over the period.
A Decision Support Toolkit to Inform Road Safety Investment Decisions
Joe Matthews, Newcastle UniversityShow Abstract
Keith Newman, Newcastle University
Amy Green, Newcastle University
Lee Fawcett, Newcastle University
Neil Thorpe, PTV Group
Road safety practitioners are tasked with maintaining safety on their network, primarily by identifying hotspots to which resources should be allocated, and ensuring existing road safety schemes are operating effectively. Both of these tasks often require road safety counts (e.g. collisions or casualties) to be analysed, however these data are frequently bedevilled by confounding statistical factors such as Regression To the Mean (RTM) and trend. Failing to account for the presence of these factors can lead to the misallocation of resources as well as sites at risk of high counts not receiving treatment. To overcome this, methods have been proposed which clean data for RTM and trend to allow for more accurate scheme evaluation, and a proactive approach towards hotspot prediction. Unfortunately, these techniques require the use of complex statistical algorithms and so can be inaccessible to some practitioners. To overcome this, user-friendly software applications have been developed which implement the aforementioned methods with minimal technical input from the user.
Factors Influencing Policy and Political Leadership in Improving Roadway Safety
Matt Schmit, University of Minnesota, Twin CitiesShow Abstract
Lee Munnich, University of Minnesota, Twin Cities
This study built upon recent work to examine further the factors influencing policy and political leadership in adopting evidence-based policy countermeasures and integrated performance-based approaches such as Towards Zero Death (TZD) to reduce road fatalities and serious injuries. Specifically, the study sought to increase understanding of the policy context for safety and how special interest group influence at the state and local level plays a part in roadway safety policy promotion and adoption. The study focused on six states in the Midwest region – Illinois, Indiana, Michigan, Minnesota, Ohio, and Wisconsin – and engaged legislators, state agency officials, and special interest stakeholders to better understand the challenges and opportunities for improving roadway safety through public policy. The study expanded upon an assessment tool applied to quantifying policy countermeasure adoption in each of the six study states and created a similar tool for gauging special interest group activity.
Impacts of State Specific Policy and Legislation on Safety Advancement by Departments of Transportation
Jennifer Ogle, Clemson UniversityShow Abstract
Sababa Islam, Clemson University
Kweku Brown, The Citadel
William Davis, The Citadel
Wayne Sarasua, Clemson University
The overall goal of this research was to identify proven successful safety programs used in other states and assess the potential for safety improvement if similar programs were implemented in South Carolina. The research team not only sought out engineering solutions, but also expanded the search to include programs for enforcement, education, licensing, legal proceedings, and emergency services – therefore incorporating a wide range stakeholder groups. South Carolina has, for many years, had one of the highest mileage death rates of any state in the nation – far exceeding the national fatality rate. While SCDOT has a federal requirement to develop and maintain the Strategic Highway Safety Plan, which identifies the state's key safety needs and guides investment decisions toward strategies and countermeasures with the most potential to save lives and prevent injuries, South Carolina legislation and state policies have effectively blocked many paths to safety improvements. Tree protection ordinances, limited policies for graduated drivers licensing, bans on camera enforcement, and lack of universal helmet laws continue to undermine efforts to improve motor vehicle safety in the state. Using a data driven approach to safety program selection will yield support for changes in programs, policies, and standards, and have positive impacts on safety, operational, and economic aspects of the South Carolina roadway system. Further, the implementation of a data-driven safety management program will help to assure that the most appropriate strategies are implemented. The successful implementation of this research would likely result in a substantial reduction in loss of life and injuries associated with motor vehicle crashes in the state of South Carolina.