Assessing the safety effects of multiple roadside treatments using parametric and nonparametric approaches

Park, Juneyoung; Abdel-Aty, Mohamed

doi:10.1016/j.aap.2015.07.008

Cited by 45 publications

(31 citation statements)

References 47 publications

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“…In the RCI database, it is able to identify historical roadway characteristics of specific roadway sections for the given dates. To overcome the issue of misinterpretation in the nonlinear modeling process, freeway segment sections with less than 0.1 mile length were excluded [42]. e identified roadway characteristics data were coordinated with the crash data from the Crash Analysis Resource System (CARS), which is also offered by the FDOT.…”

Section: Datamentioning

confidence: 99%

“…ree main steps are needed to t a MARS model [41,42,45]. In the rst step, which is a constructive phase, basis functions are examined in several regions of the predictors using a forward stepwise selection procedure.…”

Section: Multivariate Adaptive Regression Splinesmentioning

confidence: 99%

“…e GCV criterion can be estimated by Equation (1). In the last step (selection phase), the optimum MARS model from a group of recommended models can be selected based on the tting results of each [41,42] where, = response for observation , = number of observations, ( ) = complexity penalty function, = de ned cost for each basis function optimization. In order to develop the MARS models, the ADAPTIVEREG procedure in the SAS program [46] was used.…”

Section: Multivariate Adaptive Regression Splinesmentioning

confidence: 99%

“…In this study, the multivariate adaptive regression splines (MARS) technique was applied to account for both nonlinearity issues and interaction effects among variables. It is known that the MARS can control nonlinear impacts and interaction effects of independent variables for complex data structure and has an advantage in the safety analysis because it is a transparent model unlike other data mining and machine learning techniques [40][41][42]. erefore, the objectives of this study were to assess the safety effects of multiple roadway design elements.…”

Section: Introductionmentioning

confidence: 99%

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Influence of Multiple Freeway Design Features on Freight Traffic Safety

Park

Abdel-Aty

Wang

et al. 2019

Journal of Advanced Transportation

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Since various freeway design features are simultaneously installed on roadways, it is important to assess their combined safety effects correctly. This study investigated associations between multiple roadway cross-section design features on freeways and traffic safety. In order to consider the interaction impact of multiple design features and nonlinearity of predictors concurrently, multivariate adaptive regression splines (MARS) models were developed for all types and freight vehicle crashes. In MARS models, a series of basis functions is applied to represent the space of predictors and the combined safety effectiveness of multiple design features can be interpreted by the interaction terms. The generalized linear regression models (GLMs) with negative binomial (NB) distribution were also evaluated for comparison purposes. The results determine that the MARS models show better model fitness than the NB models due to its strength to reflect the nonlinearity of crash predictors and interaction impacts among variables under different ranges. Various interaction impacts among parameters under different ranges based on knot values were found from the MARS models, whereas two interaction terms were found in the NB models. The results also showed that the combined safety effects of multiple treatments from the NB models over-estimated the real combined safety effects when using the simple multiplication approach suggested by the HSM (Highway Safety Manual). Therefore, it can be recommended that the MARS is applied to evaluate the safety impacts of multiple treatments to consider both the interaction impacts among treatments and nonlinearity issues simultaneously.

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Section: Datamentioning

confidence: 99%

Section: Multivariate Adaptive Regression Splinesmentioning

confidence: 99%

Section: Multivariate Adaptive Regression Splinesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Influence of Multiple Freeway Design Features on Freight Traffic Safety

Park

Abdel-Aty

Wang

et al. 2019

Journal of Advanced Transportation

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“…In the first category, most studies include Annual Average Daily Traffic (AADT) and section length as exposure variables (Hadi et al, 1995;Anderson et al, 1999;Persaud et al, 1999;Pardillo and Llamas, 2003;Ng and Sayed, 2004;Pardillo et al, 2006;Dell'Acqua and Russo, 2008;Cafiso et al, 2010;Park and Abdel-Aty, 2015). Among the exposure variables, some authors moreover take into account the percentage of heavy vehicles Elvik, 2007;Ramírez et al, 2009;Montella, 2010;Hosseinpour et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Development of safety performance functions for Spanish two-lane rural highways on flat terrain

Garach

Oña

López

et al. 2016

Accident Analysis & Prevention

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Over decades safety performance functions (SPF) have been developed as a tool for traffic safety in order to estimate the number of crashes in a specific road section. Despite the steady progression of methodological innovations in the crash analysis field, many fundamental issues have not been completely addressed. For instance: Is it better to use parsimonious or fully specified models? How should the goodness-of-fit of the models be assessed? Is it better to use a general model for the entire sample or specific models based on sample stratifications? This paper investigates the above issues by means of several SPFs developed using negative binomial regression models for two-lane rural highways in Spain. The models were based on crash data gathered over a 5-year period, using a broad number of explanatory variables related to exposure, geometry, design consistency and roadside features. Results show that the principle of parsimony could be too restrictive and that it provided simplistic models. Most previous studies apply conventional measurements (i.e., R(2), BIC, AIC, etc.) to assess the goodness-of-fit of models. Seldom do studies apply cumulative residual (CURE) analysis as a tool for model evaluation. This paper shows that CURE plots are essential tools for calibrating SPF, while also providing information for possible sample stratification. Previous authors suggest that sample segmentation increases the model accuracy. The results presented here confirm that finding, and show that the number of significant variables in the final models increases with sample stratification. This paper point out that fully models based on sample segmentation and on CURE may provide more useful insights about traffic crashes than general parsimonious models when developing SPF.

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Effectiveness of road safety interventions: An evidence and gap map

Goel,

Tiwari,

Varghese

et al. 2024

Campbell Systematic Reviews

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BackgroundRoad Traffic injuries (RTI) are among the top ten leading causes of death in the world resulting in 1.35 million deaths every year, about 93% of which occur in low‐ and middle‐income countries (LMICs). Despite several global resolutions to reduce traffic injuries, they have continued to grow in many countries. Many high‐income countries have successfully reduced RTI by using a public health approach and implementing evidence‐based interventions. As many LMICs develop their highway infrastructure, adopting a similar scientific approach towards road safety is crucial. The evidence also needs to be evaluated to assess external validity because measures that have worked in high‐income countries may not translate equally well to other contexts. An evidence gap map for RTI is the first step towards understanding what evidence is available, from where, and the key gaps in knowledge.ObjectivesThe objective of this evidence gap map (EGM) is to identify existing evidence from all effectiveness studies and systematic reviews related to road safety interventions. In addition, the EGM identifies gaps in evidence where new primary studies and systematic reviews could add value. This will help direct future research and discussions based on systematic evidence towards the approaches and interventions which are most effective in the road safety sector. This could enable the generation of evidence for informing policy at global, regional or national levels.Search MethodsThe EGM includes systematic reviews and impact evaluations assessing the effect of interventions for RTI reported in academic databases, organization websites, and grey literature sources. The studies were searched up to December 2019.Selection CriteriaThe interventions were divided into five broad categories: (a) human factors (e.g., enforcement or road user education), (b) road design, infrastructure and traffic control, (c) legal and institutional framework, (d) post‐crash pre‐hospital care, and (e) vehicle factors (except car design for occupant protection) and protective devices. Included studies reported two primary outcomes: fatal crashes and non‐fatal injury crashes; and four intermediate outcomes: change in use of seat belts, change in use of helmets, change in speed, and change in alcohol/drug use. Studies were excluded if they did not report injury or fatality as one of the outcomes.Data Collection and AnalysisThe EGM is presented in the form of a matrix with two primary dimensions: interventions (rows) and outcomes (columns). Additional dimensions are country income groups, region, quality level for systematic reviews, type of study design used (e.g., case‐control), type of road user studied (e.g., pedestrian, cyclists), age groups, and road type. The EGM is available online where the matrix of interventions and outcomes can be filtered by one or more dimensions. The webpage includes a bibliography of the selected studies and titles and abstracts available for preview. Quality appraisal for systematic reviews was conducted using a critical appraisal tool for systematic reviews, AMSTAR 2.Main ResultsThe EGM identified 1859 studies of which 322 were systematic reviews, 7 were protocol studies and 1530 were impact evaluations. Some studies included more than one intervention, outcome, study method, or study region. The studies were distributed among intervention categories as: human factors (n = 771), road design, infrastructure and traffic control (n = 661), legal and institutional framework (n = 424), post‐crash pre‐hospital care (n = 118) and vehicle factors and protective devices (n = 111). Fatal crashes as outcomes were reported in 1414 records and non‐fatal injury crashes in 1252 records. Among the four intermediate outcomes, speed was most commonly reported (n = 298) followed by alcohol (n = 206), use of seatbelts (n = 167), and use of helmets (n = 66). Ninety‐six percent of the studies were reported from high‐income countries (HIC), 4.5% from upper‐middle‐income countries, and only 1.4% from lower‐middle and low‐income countries. There were 25 systematic reviews of high quality, 4 of moderate quality, and 293 of low quality.Authors' ConclusionsThe EGM shows that the distribution of available road safety evidence is skewed across the world. A vast majority of the literature is from HICs. In contrast, only a small fraction of the literature reports on the many LMICs that are fast expanding their road infrastructure, experiencing rapid changes in traffic patterns, and witnessing growth in road injuries. This bias in literature explains why many interventions that are of high importance in the context of LMICs remain poorly studied. Besides, many interventions that have been tested only in HICs may not work equally effectively in LMICs. Another important finding was that a large majority of systematic reviews are of low quality. The scarcity of evidence on many important interventions and lack of good quality evidence‐synthesis have significant implications for future road safety research and practice in LMICs. The EGM presented here will help identify priority areas for researchers, while directing practitioners and policy makers towards proven interventions.

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Assessing the safety effects of multiple roadside treatments using parametric and nonparametric approaches

Cited by 45 publications

References 47 publications

Influence of Multiple Freeway Design Features on Freight Traffic Safety

Influence of Multiple Freeway Design Features on Freight Traffic Safety

Development of safety performance functions for Spanish two-lane rural highways on flat terrain

Effectiveness of road safety interventions: An evidence and gap map

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