Modeling crash outcome probabilities at rural intersections: Application of hierarchical binomial logistic models

It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

Effects of transportation accessibility on residential property values: Application of spatial hedonic price model in Seoul, South Korea, metropolitan area

A number of studies have focused on estimating the effects of accessibility on housing values by using the hedonic price model. In the majority of studies, estimation results have revealed that housing values increase as accessibility improves, although the magnitude of estimates has varied across studies. Adequately estimating the relationship between transportation accessibility and housing values is challenging for at least two reasons. First, the monocentric city assumption applied in location theory is no longer valid for many large or growing cities. Second, rather than being randomly distributed in space, housing values are clustered in space—often exhibiting spatial dependence. Recognizing these challenges, a study was undertaken to develop a spatial lag hedonic price model in the Seoul, South Korea, metropolitan region, which includes a measure of local accessibility as well as systemwide accessibility, in addition to other model covariates. Although the accessibility measures can be improved, the modeling results suggest that the spatial interactions of apartment sales prices occur across and within traffic analysis zones, and the sales prices for apartment communities are devalued as accessibility deteriorates. Consistent with findings in other cities, this study revealed that the distance to the central business district is still a significant determinant of sales price.

Bayesian methodology incorporating expert judgment for ranking countermeasure effectiveness under uncertainty: Example applied to at grade railroad crossings in Korea

This paper describes the formalization and application of a methodology to evaluate the safety benefit of countermeasures in the face of uncertainty. To illustrate the methodology, 18 countermeasures for improving safety of at grade railroad crossings (AGRXs) in the Republic of Korea are considered. Akin to “stated preference” methods in travel survey research, the methodology applies random selection and laws of large numbers to derive accident modification factor (AMF) densities from expert opinions. In a full Bayesian analysis framework, the collective opinions in the form of AMF densities (data likelihood) are combined with prior knowledge (AMF density priors) for the 18 countermeasures to obtain ‘best’ estimates of AMFs (AMF posterior credible intervals). The countermeasures are then compared and recommended based on the largest safety returns with minimum risk (uncertainty). To the author's knowledge the complete methodology is new and has not previously been applied or reported in the literature. The results demonstrate that the methodology is able to discern anticipated safety benefit differences across candidate countermeasures. For the 18 at grade railroad crossings considered in this analysis, it was found that the top three performing countermeasures for reducing crashes are in-vehicle warning systems, obstacle detection systems, and constant warning time systems.

Expected safety performance of rural signalized intersections in South Korea

Understanding the expected safety performance of rural signalized intersections is critical for (a) identifying high-risk sites where the observed safety performance is substantially worse than the expected safety performance, (b) understanding influential factors associated with crashes, and (c) predicting the future performance of sites and helping plan safety-enhancing activities. These three critical activities are routinely conducted for safety management and planning purposes in jurisdictions throughout the United States and around the world. This paper aims to develop baseline expected safety performance functions of rural signalized intersections in South Korea, which to date have not yet been established or reported in the literature. Data are examined from numerous locations within South Korea for both three-legged and four-legged configurations. The safety effects of a host of operational and geometric variables on the safety performance of these sites are also examined. In addition, supplementary tables and graphs are developed for comparing the baseline safety performance of sites with various geometric and operational features. These graphs identify how various factors are associated with safety. The expected safety prediction tables offer advantages over regression prediction equations by allowing the safety manager to isolate specific features of the intersections and examine their impact on expected safety. The examination of the expected safety performance tables through illustrated examples highlights the need to correct for regression-to-the-mean effects, emphasizes the negative impacts of multicollinearity, shows why multivariate models do not translate well to accident modification factors, and illuminates the need to examine road safety carefully and methodically. Caveats are provided on the use of the safety performance prediction graphs developed in this paper.

Development of accident prediction models for rural highway intersections

A study was done to develop macrolevel crash prediction models that can be used to understand and identify effective countermeasures for improving signalized highway intersections and multilane stop-controlled highway intersections in rural areas. Poisson and negative binomial regression models were fit to intersection crash data from Georgia, California, and Michigan. To assess the suitability of the models, several goodness-of-fit measures were computed. The statistical models were then used to shed light on the relationships between crash occurrence and traffic and geometric features of the rural signalized intersections. The results revealed that traffic flow variables significantly affected the overall safety performance of the intersections regardless of intersection type and that the geometric features of intersections varied across intersection type and also influenced crash type.

Further notes on the application of zero-inflated models in highway safety

The intent of this note is to succinctly articulate additional points that were not provided in the original paper (Lord et al., 2005) and to help clarify a collective reluctance to adopt zero-inflated (ZI) models for modeling highway safety data. A dialogue on this important issue, just one of many important safety modeling issues, is healthy discourse on the path towards improved safety modeling. This note first provides a summary of prior findings and conclusions of the original paper. It then presents two critical and relevant issues: the maximizing statistical fit fallacy and logic problems with the ZI model in highway safety modeling. Finally, we provide brief conclusions.

Experimental evaluation of hotspot identification methods

Identifying crash “hotspots”, “blackspots”, “sites with promise”, or “high risk” locations is standard practice in departments of transportation throughout the US. The literature is replete with the development and discussion of statistical methods for hotspot identification (HSID). Theoretical derivations and empirical studies have been used to weigh the benefits of various HSID methods; however, a small number of studies have used controlled experiments to systematically assess various methods. Using experimentally derived simulated data—which are argued to be superior to empirical data, three hot spot identification methods observed in practice are evaluated: simple ranking, confidence interval, and Empirical Bayes. Using simulated data, sites with promise are known a priori, in contrast to empirical data where high risk sites are not known for certain. To conduct the evaluation, properties of observed crash data are used to generate simulated crash frequency distributions at hypothetical sites. A variety of factors is manipulated to simulate a host of ‘real world’ conditions. Various levels of confidence are explored, and false positives (identifying a safe site as high risk) and false negatives (identifying a high risk site as safe) are compared across methods. Finally, the effects of crash history duration in the three HSID approaches are assessed. The results illustrate that the Empirical Bayes technique significantly outperforms ranking and confidence interval techniques (with certain caveats). As found by others, false positives and negatives are inversely related. Three years of crash history appears, in general, to provide an appropriate crash history duration.

Bayesian multinomial logit: Theory and route choice example

Statisticians along with other scientists have made significant computational advances that enable the estimation of formerly complex statistical models. The Bayesian inference framework combined with Markov chain Monte Carlo estimation methods such as the Gibbs sampler enable the estimation of discrete choice models such as the multinomial logit (MNL) model. MNL models are frequently applied in transportation research to model choice outcomes such as mode, destination, or route choices or to model categorical outcomes such as crash outcomes. Recent developments allow for the modification of the potentially limiting assumptions of MNL such as the independence from irrelevant alternatives (IIA) property. However, relatively little transportation-related research has focused on Bayesian MNL models, the tractability of which is of great value to researchers and practitioners alike. This paper addresses MNL model specification issues in the Bayesian framework, such as the value of including prior information on parameters, allowing for nonlinear covariate effects, and extensions to random parameter models, so changing the usual limiting IIA assumption. This paper also provides an example that demonstrates, using route-choice data, the considerable potential of the Bayesian MNL approach with many transportation applications. This paper then concludes with a discussion of the pros and cons of this Bayesian approach and identifies when its application is worthwhile

Quality of child abuse information for measurement and surveillance : linking hospital and child welfare data

National estimates of the prevalence of child abuse-related injuries are obtained from a variety of sectors including welfare, justice, and health resulting in inconsistent estimates across sectors. The International Classification of Diseases (ICD) is used as the international standard for categorising health data and aggregating data for statistical purposes, though there has been limited validation of the quality, completeness or concordance of these data with other sectors. This research study examined the quality of documentation and coding of child abuse recorded in hospital records in Queensland and the concordance of these data with child welfare records. A retrospective medical record review was used to examine the clinical documentation of over 1000 hospitalised injured children from 20 hospitals in Queensland. A data linkage methodology was used to link these records with records in the child welfare database. Cases were sampled from three sub-groups according to the presence of target ICD codes: Definite abuse, Possible abuse, unintentional injury. Less than 2% of cases coded as being unintentional were recoded after review as being possible abuse, and only 5% of cases coded as possible abuse cases were reclassified as unintentional, though there was greater variation in the classification of cases as definite abuse compared to possible abuse. Concordance of health data with child welfare data varied across patient subgroups. This study will inform the development of strategies to improve the quality, consistency and concordance of information between health and welfare agencies to ensure adequate system responses to children at risk of abuse.

Quality of child abuse information in emergency department injury surveillance data : linking hospital and child welfare data

Emergency departments (EDs) are often the first point of contact with an abused child. Despite legal mandate, the reporting of definite or suspected abusive injury to child safety authorities by ED clinicians varies due to a number of factors including training, access to child safety professionals, departmental culture and a fear of ‘getting it wrong’. This study examined the quality of documentation and coding of child abuse captured by ED based injury surveillance data and ED medical records in the state of Queensland and the concordance of these data with child welfare records. A retrospective medical record review was used to examine the clinical documentation of almost 1000 injured children included in the Queensland Injury Surveillance Unit database (QISU) from 10 hospitals in urban and rural centres. Independent experts re-coded the records based on their review of the notes. A data linkage methodology was then used to link these records with records in the state government’s child welfare database. Cases were sampled from three sub-groups according to the surveillance intent codes: Maltreatment by parent, Undetermined and Unintentional injury. Only 0.1% of cases coded as unintentional injury were recoded to maltreatment by parent, while 1.2% of cases coded as maltreatment by parent were reclassified as unintentional and 5% of cases where the intent was undetermined by the triage nurse were recoded as maltreatment by parent. Quality of documentation varied across type of hospital (tertiary referral centre, children’s, urban, regional and remote). Concordance of health data with child welfare data varied across patient subgroups. Outcomes from this research will guide initiatives to improve the quality of intentional child injury surveillance systems.

Component reliability estimations without field data

Maintenance activities in a large-scale engineering system are usually scheduled according to the lifetimes of various components in order to ensure the overall reliability of the system. Lifetimes of components can be deduced by the corresponding probability distributions with parameters estimated from past failure data. While failure data of the components is not always readily available, the engineers have to be content with the primitive information from the manufacturers only, such as the mean and standard deviation of lifetime, to plan for the maintenance activities. In this paper, the moment-based piecewise polynomial model (MPPM) are proposed to estimate the parameters of the reliability probability distribution of the products when only the mean and standard deviation of the product lifetime are known. This method employs a group of polynomial functions to estimate the two parameters of the Weibull Distribution according to the mathematical relationship between the shape parameter of two-parameters Weibull Distribution and the ratio of mean and standard deviation. Tests are carried out to evaluate the validity and accuracy of the proposed methods with discussions on its suitability of applications. The proposed method is particularly useful for reliability-critical systems, such as railway and power systems, in which the maintenance activities are scheduled according to the expected lifetimes of the system components.

Signal authentication and integrity schemes for next generation global navigation satellite systems

This paper describes a number of techniques for GNSS navigation message authentication. A detailed analysis of the security facilitated by navigation message authentication is given. The analysis takes into consideration the risk of critical applications that rely on GPS including transportation, finance and telecommunication networks. We propose a number of cryptographic authentication schemes for navigation data authentication. These authentication schemes provide authenticity and integrity of the navigation data to the receiver. Through software simulation, the performance of the schemes is quantified. The use of software simulation enables the collection of authentication performance data of different data channels, and the impact of various schemes on the infrastructure and receiver. Navigation message authentication schemes have been simulated at the proposed data rates of Galileo and GPS services, for which the resulting performance data is presented. This paper concludes by making recommendations for optimal implementation of navigation message authentication for Galileo and next generation GPS systems.

Determinants of infant and young child feeding practices in Bangladesh: Secondary data analysis of Demographic and Health Survey 2004

BACKGROUND: In Bangladesh, poor infant and young child feeding practices are contributing to the burden of infectious diseases and malnutrition. Objective. To estimate the determinants of selected feeding practices and key indicators of breastfeeding and complementary feeding in Bangladesh. METHODS: The sample included 2482 children aged 0 to 23 months from the Bangladesh Demographic and Health Survey of 2004. The World Health Organization (WHO)-recommended infant and young child feeding indicators were estimated, and selected feeding indicators were examined against a set of individual-, household-, and community-level variables using univariate and multivariate analyses. RESULTS: Only 27.5% of mothers initiated breastfeeding within the first hour after birth, 99.9% had ever breastfed their infants, 97.3% were currently breastfeeding, and 22.4% were currently bottle-feeding. Among infants under 6 months of age, 42.5% were exclusively breastfed, and among those aged 6 to 9 months, 62.3% received complementary foods in addition to breastmilk. Among the risk factors for an infant not being exclusively breastfed were higher socioeconomic status, higher maternal education, and living in the Dhaka region. Higher birth order and female sex were associated with increased rates of exclusive breastfeeding of infants under 6 months of age. The risk factors for bottle-feeding were similar and included having a partner with a higher educational level (OR = 2.17), older maternal age (OR for age > or = 35 years = 2.32), and being in the upper wealth quintiles (OR for the richest = 3.43). Urban mothers were at higher risk for not initiating breastfeeding within the first hour after birth (OR = 1.61). Those who made three to six visits to the antenatal clinic were at lower risk for not initiating breastfeeding within the first hour (OR = 0.61). The rate of initiating breastfeeding within the first hour was higher in mothers from richer households (OR = 0.37). CONCLUSIONS: Most breastfeeding indicators in Bangladesh were below acceptable levels. Breastfeeding promotion programs in Bangladesh need nationwide application because of the low rates of appropriate infant feeding indicators, but they should also target women who have the main risk factors, i.e., working mothers living in urban areas (particularly in Dhaka).

Determinants of infant and young child feeding practices in Sri Lanka : secondary data analysis of demographic and health survey 2000

Background: Poor feeding practices in early childhood contribute to the burden of childhood malnutrition and morbidity. Objective: To estimate the key indicators of breastfeeding and complementary feeding and the determinants of selected feeding practices in Sri Lanka. Methods: The sample consisted of 1,127 children aged 0 to 23 months from the Sri Lanka Demographic and Health Survey 2000. The key infant feeding indicators were estimated and selected indicators were examined against a set of individual-, household-, and community- level variables using univariate and multivariate analyses. Results: Breastfeeding was initiated within the first hour after birth in 56.3% of infants, 99.7% had ever been breastfed, 85.0% were currently being breastfed, and 27.2% were being bottle-fed. Of infants under 6 months of age, 60.6% were fully breastfed, and of those aged 6 to 9 months, 93.4% received complementary foods. The likelihood of not initiating breastfeeding within the first hour after birth was higher for mothers who underwent cesarean delivery (OR = 3.23) and those who were not visited by a Public Health Midwife at home during pregnancy (OR = 1.81). The rate of full breastfeeding was significantly lower among mothers who did not receive postnatal home visits by a Public Health Midwife. Bottlefeeding rates were higher among infants whose mothers had ever been employed (OR = 1.86), lived in a metropolitan area (OR = 3.99), or lived in the South-Central Hill country (OR = 3.11) and were lower among infants of mothers with secondary education (OR = 0.27). Infants from the urban (OR = 8.06) and tea estate (OR = 12.63) sectors were less likely to receive timely complementary feeding than rural infants. Conclusions: Antenatal and postnatal contacts with Public Health Midwives were associated with improved breastfeeding practices. Breastfeeding promotion strategies should specifically focus on the estate and urban or metropolitan communities.

Determinants of infant and young child feeding practices in Nepal : secondary data analysis of demographic and health survey 2006

Background: Childhood undernutrition and mortality are high in Nepal, and therefore interventions on infant and young child feeding practices deserve high priority. Objective. To estimate infant and young child feeding indicators and the determinants of selected feeding practices. Methods: The sample consisted of 1,906 children aged 0 to 23 months from the Demographic and Health Survey 2006. Selected indicators were examined against a set of variables using univariate and multivariate analyses. Results. Breastfeeding was initiated within the first hour after birth in 35.4% of children, 99.5% were ever breastfed, 98.1% were currently breastfed, and 3.5% were bottle-fed. The rate of exclusive breastfeeding among infants under 6 months of age was 53.1%, and the rate of timely complementary feeding among those 6 to 9 months of age was 74.7%. Mothers who made antenatal clinic visits were at a higher risk for no exclusive breastfeeding than those who made no visits. Mothers who lived in the mountains were more likely to initiate breastfeeding within 1 hour after birth and to introduce complementary feeding at 6 to 9 months of age, but less likely to exclusively breastfeed. Cesarean deliveries were associated with delay in timely initiation of breastfeeding. Higher rates of complementary feeding at 6 to 9 months were also associated with mothers with better education and those above 35 years of age. Risk factors for bottle-feeding included living in urban areas and births attended by trained health personnel. Conclusions: Most breastfeeding indicators in Nepal are below the expected levels to achieve a substantial reduction in child mortality. Breastfeeding promotion strategies should specifically target mothers who have more contact with the health care delivery system, while programs targeting the entire community should be continued.