Validation of FHWA crash models for rural intersections - Lessons learned

A national-level safety analysis tool is needed to complement existing analytical tools for assessment of the safety impacts of roadway design alternatives. FHWA has sponsored the development of the Interactive Highway Safety Design Model (IHSDM), which is roadway design and redesign software that estimates the safety effects of alternative designs. Considering the importance of IHSDM in shaping the future of safety-related transportation investment decisions, FHWA justifiably sponsored research with the sole intent of independently validating some of the statistical models and algorithms in IHSDM. Statistical model validation aims to accomplish many important tasks, including (a) assessment of the logical defensibility of proposed models, (b) assessment of the transferability of models over future time periods and across different geographic locations, and (c) identification of areas in which future model improvements should be made. These three activities are reported for five proposed types of rural intersection crash prediction models. The internal validation of the model revealed that the crash models potentially suffer from omitted variables that affect safety, site selection and countermeasure selection bias, poorly measured and surrogate variables, and misspecification of model functional forms. The external validation indicated the inability of models to perform on par with model estimation performance. Recommendations for improving the state of the practice from this research include the systematic conduct of carefully designed before-and-after studies, improvements in data standardization and collection practices, and the development of analytical methods to combine the results of before-and-after studies with cross-sectional studies in a meaningful and useful way.

Empirical investigation of interactive highway safety design model accident prediction algorithm : Rural intersections

One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.

A simultaneous equations model of crash frequency by collision type for rural intersections

Safety at roadway intersections is of significant interest to transportation professionals due to the large number of intersections in transportation networks, the complexity of traffic movements at these locations that leads to large numbers of conflicts, and the wide variety of geometric and operational features that define them. A variety of collision types including head-on, sideswipe, rear-end, and angle crashes occur at intersections. While intersection crash totals may not reveal a site deficiency, over exposure of a specific crash type may reveal otherwise undetected deficiencies. Thus, there is a need to be able to model the expected frequency of crashes by collision type at intersections to enable the detection of problems and the implementation of effective design strategies and countermeasures. Statistically, it is important to consider modeling collision type frequencies simultaneously to account for the possibility of common unobserved factors affecting crash frequencies across crash types. In this paper, a simultaneous equations model of crash frequencies by collision type is developed and presented using crash data for rural intersections in Georgia. The model estimation results support the notion of the presence of significant common unobserved factors across crash types, although the impact of these factors on parameter estimates is found to be rather modest.

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.

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.

Modeling crash types: New insights into the effects of covariates on crashes at rural intersections

Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.

Performance in the spotlight : exploring psychology in the performing arts

Sport and exercise psychologists are often sought after to apply their knowledge, skills and experience from a sporting context into other performance-related industries and endeavours. Over the past two decades, this has noticeably expanded out from a natural progression into the performing arts with other ‘typical’ performers (e.g., dancers, actors, musicians, singers) through to people who work in high pressure environments that consist of clear performance outputs and requirements that are usually linked to high impact consequences for non-achievement (e.g., lawyers, surgeons, executives, military personnel, safety professionals). Whilst these areas of application continue to increase in popularity and performance psychology is more readily recognised as an important factor in people performance across industries, the use of psychology within the performing arts continues to deepen and solidify its value as an essential and critical factor for success. This article focuses on the contribution of psychology to the performing arts that I have observed over more than 20 years – obtained through a variety of roles primarily within the dance sector including as performer, educator, health professional, researcher, commentator and senior leader.

Creative intersections : supervision, practice and the space between

Supervision in the creative arts is a topic of growing significance since the increase in creative practice PhDs across universities in Australasia. This presentation will provide context of existing discussions in creative practice and supervision. Creative practice – encompassing practice-based or practice-led research – has now a rich history of research surrounding it. Although it is a comparatively new area of knowledge, great advances have been made in terms of how practice can influence, generate, and become research. The practice of supervision is also a topic of interest, perhaps unsurprisingly considering its necessity within the university environment. Many scholars have written much about supervision practices and the importance of the supervisory role, both in academic and more informal forms. However, there is an obvious space in between: there is very little research on supervision practices within creative practice higher degrees, especially at PhD or doctorate level. Despite the existence of creative practice PhD programs, and thus the inherent necessity for successful supervisors, there remain minimal publications and limited resources available. Creative Intersections explores the existing publications and resources, and illustrates that a space for new published knowledge and tools exists.

Developmental lessons from the Capricornia Arts Mob : ‘learning to speak with one voice’

The Capricornia Arts Mob also known as CAM is a collective of Aboriginal and Torres Strait Islander visual artists, sculptors, photographers, carvers and writers based in the Rockhampton Region. Its members are eclectic and include an 18 year old through to Elders. CAM has already had a major exhibition in Rockhampton and is submitting work to a range of arts festivals, events and exhibitions. While their achievements are steadily growing and they have been meeting for 18 months, they have been reluctant to incorporate or implement a formalised structure. In learning how to work together there have been tensions and struggles, there has also been the exhilaration of working collaboratively as artists from diverse Indigenous cultures who utilise different mediums. This has resulted in an incredible vibrancy in creative praxis. Members will share some of CAM’s learnings of the developmental process to date and thoughts and dreams about the future.

Communicating personal amnesty : a model for health promotion in an Australian disability context

Currently pathological and illness-centric policy surrounds the evaluation of the health status of a person experiencing disability. In this research partnerships were built between disability service providers, community development organizations and disability arts organizations to build a translational evaluative methodology prior to implementation of an arts-based workshop that was embedded in a strengths-based approach to health and well-being. The model consisted of three foci: participation in a pre-designed drama-based workshop program; individualized assessment and evaluation of changing health status; and longitudinal analysis of participants changing health status in their public lives following the culmination of the workshop series. Participants (n = 15) were recruited through disability service providers and disability arts organizations to complete a 13-week workshop series and public performance. The study developed accumulative qualitative analysis tools and member-checking methods specific to the communication systems used by individual participants. Principle findings included increased confidence for verbal and non-verbal communicators; increased personal drive, ambition and goal-setting; increased arts-based skills including professional engagements as artists; demonstrated skills in communicating perceptions of health status to private and public spheres. Tangential positive observations were evident in the changing recreational, vocational and educational activities participants engaged with pre- and post- the workshop series; participants advocating for autonomous accommodation and health provision and changes in the disability service staff's culture. The research is an example of translational health methodologies in disability studies.