Laura Garach

Bayes classifiers for imbalanced traffic accidents datasets

Traffic accidents data sets are usually imbalanced, where the number of instances classified under the killed or severe injuries class (minority) is much lower than those classified under the slight injuries class (majority). This, however, supposes a challenging problem for classification algorithms and may cause obtaining a model that well cover the slight injuries instances whereas the killed or severe injuries instances are misclassified frequently. Based on traffic accidents data collected on urban and suburban roads in Jordan for three years (2009-2011); three different data balancing techniques were used: under-sampling which removes some instances of the majority class, oversampling which creates new instances of the minority class and a mix technique that combines both. In addition, different Bayes classifiers were compared for the different imbalanced and balanced data sets: Averaged One-Dependence Estimators, Weightily Average One-Dependence Estimators, and Bayesian networks in order to identify factors that affect the severity of an accident. The results indicated that using the balanced data sets, especially those created using oversampling techniques, with Bayesian networks improved classifying a traffic accident according to its severity and reduced the misclassification of killed and severe injuries instances. On the other hand, the following variables were found to contribute to the occurrence of a killed causality or a severe injury in a traffic accident: number of vehicles involved, accident pattern, number of directions, accident type, lighting, surface condition, and speed limit. This work, to the knowledge of the authors, is the first that aims at analyzing historical data records for traffic accidents occurring in Jordan and the first to apply balancing techniques to analyze injury severity of traffic accidents.

Relationship between Predicted Speed Reduction on Horizontal Curves and Safety on Two-Lane Rural Roads in Spain

According to different studies, speed reduction is considered one of the major factors in contributing road safety. For that reason, several guidelines have been recommended for maximum desirable speed reductions from tangents to horizontal curves and for maximum differentials between design and operating speeds on horizontal curves. The Interactive Highway Safety Design Model (IHSDM) Design Consistency Module presents an analysis of the relationship between speed reduction and crashes for horizontal curves on U.S. two-lane rural highways. This paper presents the relationship between speed reduction and crashes for horizontal curves on Spanish two-lane rural roads. A model for using regression analysis to predict crashes is presented. Exposure, curve length (CL), and difference in 85th-percentile speeds (ΔV85) between successive tangents and horizontal curves, as well as between successive curves, are used. The models coefficients were different from the ones obtained for U.S. highways, although the values of the goodness-of-fit criteria were similar. In addition, the relationship between crashes and different speeds is analyzed, taking the difference in speed as a speed differential not exceeded by 85% of the drivers traveling under free-flow conditions (Δ85V), instead of considering it as ΔV85. The two models (ΔV85 versus Δ85V) give very similar results. Language: en

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

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.

How to Expand Subway and Urban Railway Networks: Light Rail Extensions in Madrid, Spain

Residential areas of detached houses were built in north and east Madrid, Spain, during the last decade of the 20th century. Because the population density in those areas is low, implementing an efficient transport system is complicated. In south Madrid in the 1960s, however, huge commuter towns developed. Some of them were linked to a suburban network at some point, whereas others were far away. The Madrid region promoted the construction of several light rail lines to resolve this issue. The lines function as extensions to the existing rail network (subway or suburban trains). The determining factors that enabled these lines to be implemented and operated successfully are analyzed. The recommendations for implementing a light rail transit system, on the basis of that analysis, are: (a) the lines should not be very long; (b) they should have a segregated right-of-way; (c) the quality of service should be good; and (d) they should be coordinated with other modes of transport. Apart from public funding, they could be funded by additional resources collected from property tax and the concessionaire company (private funding). A concessionaire consortium may comprise construction companies, transport operators, financial institutions, rolling stock manufacturers, and consultancies. Finally, the concession should be granted for a 30- to 40-year period so that private stakeholders can recover their investment.

Proposal of a New Global Model of Consistency: Application in Two-Lane Rural Highways in Spain

Consistency is the relationship between the geometric characteristics of a highway and the conditions a driver expects to encounter. In this study, based on operating speed, consistency was calculated in two-lane rural highways of the province of Granada, Spain. Three consistency measures were calculated for 506 homogeneous road sections: the relative area, which represents the area bounded by the speed profile and average speed of a road segment; the standard deviation of the operating speed in each design element along the road segment; and a consistency model based on the previous measures introduced. Some discrepancies regarding the obtained results lead the authors to propose a new model of consistency that overcomes the identified disagreements.

A proposal for cost-related and market-oriented train running charges

This paper examines some key aspects of a charging system for promoting railway transport, including charges reflecting a clear relationship with costs (transparency) and charges reflecting the quality of the infrastructure managers service. Train running charges recover track-related costs and can help to develop a charging system that meets these requirements. To orient train running charges to the market, a method for processing track maintenance and renewal costs is proposed whereby the quality of the service provided by an infrastructure is measured according to its utility to the railway undertaking. To achieve transparency, a single indicator is used for cost planning and the subsequent levying of costs on railway undertakings. The paper includes an example of how proposed train running charges would be calculated according to data from 14 European countries. The example shows that short-distance trains generate the lowest maintenance and renewal costs, followed by long-distance trains and freight trains.

Original Articles: Determination of alignments in existing roads by using spline techniques

This paper presents a quick, simple and automatic approximation method that allows the alignments in a road (straights, curves or clothoids) and their respective curvature values to be identified from an approximation point set given by its UTM (Universal Transverse Mercator) coordinates obtained from field data. The method reconstructs the geometry of the road by a smoothing variational cubic spline, computes the curvature function of this spline and approximates the curvature function using a polygonal function formed by trapezoids on the abscises axis. This method permits to obtain alignments that can be used to study any road system that has certain characteristics.

Modeling Injury Severity of Vehicular Traffic Crashes

Data mining techniques constitute an alternative approach that has received increasing attention from researchers in recent years in road safety analysis field. In this paper Bayesian networks were used to develop models in order to identify factors that affect the injury severity of a crash within urban areas based on traffic crashes data on Jordanian roads collected for three years (2009-2011). The following variables were found to have a significant effect on classifying crashes according to their injury severity: lighting of roadway, crash type, road type, crash manner, surface condition, number of lanes, number of vehicles, gradient, type of pavement, traffic control devices, and speed limit. The results of this research can be used to determine the factors that should be taken into consideration when designing a new roadway or for improving safety of existing roads.

Extraction of decision rules via imprecise probabilities

Abstract Data analysis techniques can be applied to discover important relations among features. This is the main objective of the Information Root Node Variation (IRNV) technique, a new method to extract knowledge from data via decision trees. The decision trees used by the original method were built using classic split criteria. The performance of new split criteria based on imprecise probabilities and uncertainty measures, called credal split criteria, differs significantly from the performance obtained using the classic criteria. This paper extends the IRNV method using two credal split criteria: one based on a mathematical parametric model, and other one based on a non-parametric model. The performance of the method is analyzed using a case study of traffic accident data to identify patterns related to the severity of an accident. We found that a larger number of rules is generated, significantly supplementing the information obtained using the classic split criteria.

Using Imprecise Probabilities to Extract Decision Rules via Decision Trees for Analysis of Traffic Accidents

The main aim of this study is focused on the extraction or obtaining of important decision rules (DRs) using decision trees (DTs) from traffic accidents’ data. These decision rules identify patterns related with the severity of the accident. In this work, we have incorporated a new split criterion to built decision trees in a method named Information Root Node Variation (IRNV) used for extracting these DRs. It will be shown that, with the adding of this criterion, the information obtained from the method is improved trough new and different decision rules, some of them use different variables than the ones obtained with the original method.