Actuaciones de seguridad vial en ámbito urbano: itinerarios ciclistas

En ámbito urbano cada vez es más frecuente la presencia de diversos usuarios, y particularmente, los ciclistas están cada vez más presentes en estas vías. Para que la integración de estos usuarios se realice de un modo seguro, es necesario un adecuado diseño de itinerarios ciclistas. En este artículo se presentan algunas de las principales claves para realizar estos itinerarios.López Maldonado, G. (2021). Actuaciones de seguridad vial en ámbito urbano: itinerarios ciclistas. http://hdl.handle.net/10251/167517DE

Ensayos de compactación en carreteras: Proctor Normal y Modificado

En el objeto de aprendizaje se presentan los ensayos de compactación Proctor Normal y Proctor Modificado, describiéndose el objetivo de los mismos, cómo se realizan y cuáles son sus principales diferencias. Además, se muestra cómo tratar los resultados de los mismos y cómo se trasladan estos resultados a la obra de carreteras.López Maldonado, G. (2020). Ensayos de compactación en carreteras: Proctor Normal y Modificado. http://hdl.handle.net/10251/139866DE

Características de los ligantes y conglomerantes en los firmes de carreteras

Bajo el nombre de ligantes y conglomerante se engloban una amplia gama de materiales de diferente naturaleza y composición. Sin embargo, estos materiales tienen una característica común; poseen propiedades adhesivas y aglomerantes, y por tanto, son los materiales que aportan la cohesión necesaria para unir los materiales utilizados en la formación de las diferentes capas del firme de la carretera. Conocer sus características, propiedades y tipologías es un requisito fundamental de cara a su diseño.López Maldonado, G. (2020). Características de los ligantes y conglomerantes en los firmes de carreteras. http://hdl.handle.net/10251/142218DE

Bayes classifiers for imbalanced traffic accidents datasets

[EN] 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. (C) 2015 Elsevier Ltd. All rights reserved.The authors are grateful to the Police Traffic Department in Jordan for providing the data necessary for this research. Griselda Lopez wishes to express her acknowledgement to the regional ministry of Economy, Innovation and Science of the regional government of Andalusia (Spain) for their scholarship to train teachers and researchers in Deficit Areas, which has made this work possible. The authors appreciate the reviewers' comments and effort in order to improve the paper.Mujalli, R.; López-Maldonado, G.; Garach, L. (2016). Bayes classifiers for imbalanced traffic accidents datasets. Accident Analysis & Prevention. 88:37-51. https://doi.org/10.1016/j.aap.2015.12.003S37518

Analysis of traffic accident severity using Decision Rules via Decision Trees

[EN] A Decision Tree (DT) is a potential method for studying traffic accident severity. One of its main advantages is that Decision Rules can be extracted from its structure and used to identify safety problems and establish certain measures of performance. However, when it used only one DT, the rule extraction is limited to the structure of that DT and some important relationships between variables cannot be extracted. This paper presents a method for extracting rules from a DT more effectively. The method¿s effectiveness when applied to a particular traffic accidents dataset is shown. Specifically, our study focuses on traffic accident data from rural roads in Granada (Spain) from 2003 to 2009 (both included). The results show that we can obtain more than 70 relevant rules from our data using the new method, whereas with only one DT we would had extracted only 5 rules from the same dataset.Abellán, J.; López-Maldonado, G.; De Oña, J. (2013). Analysis of traffic accident severity using Decision Rules via Decision Trees. Expert Systems with Applications. 40(15):6047-6054. doi:10.1016/j.eswa.2013.05.027S60476054401

Structural Equation Approach to Analyze Cyclists Risk Perception and Their Behavior Riding on Two-Lane Rural Roads in Spain

[EN] The use of bicycles on two-lane rural roads in Spain has been increasing in recent years. However, these roads have no bicycle infrastructure, being cyclists forced to share the road and interact with motorized vehicles. In rural environments, the interaction between road users from the cyclist's point of view is still not well understood. To analyze it, the relationships between risk perceptions and behavioral factors of rural cyclists according to their demographic characteristics, profile, and self-reported knowledge on traffic rules were obtained. An online survey was used, which collected the opinion of 523 cyclists. Data were analyzed by using structural equation models. The Thurstonian Item Response Theory approach was adopted to include raking responses. Different perceptions among demographic groups were found. Younger cyclists present the lowest risk perception while having a higher risk behavior. The knowledge about traffic rules was correlated with safety behavior, showing the importance of this factor. These results are in line with urban cycling. However important differences under risk elements for rural cyclists, mainly associated with potential hazards on the shoulder, have been drawn. These findings may help policy makers to integrate cycling with vehicular traffic on two-lane rural roads in a safe way.This research was funded by the Ministry of Science, Innovation, and Universities, grant number TRA2016-80897-R and project titled: "Improvement of safety and operation of two-lane rural roads with cyclists (Bike2Lane)"; and by the Direccion General de Trafico of Spain, grant number SPIP2017-02280 and project title: "Road safety countermeasures for two-lane rural roads with groups of cyclists (Safe4Bikes)".López-Maldonado, G.; Arroyo-López, MR.; García García, A. (2021). Structural Equation Approach to Analyze Cyclists Risk Perception and Their Behavior Riding on Two-Lane Rural Roads in Spain. Sustainability. 13(15):1-19. https://doi.org/10.3390/su13158424S119131

Analysis of the Influence of Sport Cyclists on Narrow Two-Lane Rural Roads Using Instrumented Bicycles and Microsimulation

[EN] It is frequent to see cyclists on Spanish two-lane rural roads, both riding individually and in groups. However, these roads were designed only for motorized vehicles, most of them having a narrow section with a null or impassable shoulder. Currently, drivers and cyclists have to share roads and interact, affecting both safety and traffic operation. The possibility of overtaking offers an improvement in traffic operation, however on narrow roads it can be difficult, meaning a greater invasion of the opposite lane thus creating more dangerous situations and implying a higher overtaking duration. To analyze the phenomenon, field data from instrumented bicycles and naturalistic videos were collected, then some performance measures to characterize safety and traffic operation were obtained. To increase the number of overtaking manoeuvres and performance measures obtained from observations, microsimulation has been used by adapting a model to include cyclists and their interaction with motorized vehicles. The traffic microsimulator was calibrated and validated with field data. The results show that cycle traffic presence decreases motorized vehicle average travel speed and increases percent followers and delays. Microsimulation can be used to study other traffic scenarios and can help road administrations to safely and efficiently integrate cyclists to vehicular traffic on rural roads.This research was funded by the Ministry of Science, Innovation, and Universities, grant number TRA2016-80897-R and project titled: "Improvement of safety and operation of two-lane rural roads with cyclists (Bike2Lane)"; and by the Direccion General de Trafico of Spain, grant number SPIP2017-02280 and project title: "Road safety countermeasures for two-lane rural roads with groups of cyclists (Safe4Bikes)".Moll Montaner, S.; López-Maldonado, G.; García García, A. (2021). Analysis of the Influence of Sport Cyclists on Narrow Two-Lane Rural Roads Using Instrumented Bicycles and Microsimulation. Sustainability. 13(3):1-17. https://doi.org/10.3390/su13031235S11713

Transit service quality analysis using cluster analysis and decision trees: a step forward to personalized marketing in public transportation

[EN] A transit service quality study based on cluster analysis was performed to extract detailed customer profiles sharing similar appraisals concerning the service. This approach made it possible to detect specific requirements and needs regarding the quality of service and to personalize the marketing strategy. Data from various customer satisfaction surveys conducted by the Transport Consortium of Granada (Spain) were analyzed to distinguish these groups; a decision tree methodology was used to identify the most important service quality attributes influencing passengers overall evaluations. Cluster analysis identified four groups of passengers. Comparisons using decision trees among the overall sample of all users and the different groups of passengers identified by cluster analysis led to the discovery of differences in the key attributes encompassed by perceived quality.The authors also acknowledge the Granada Consorcio de Transportes for making the data set available for this study. Griselda Lopez wishes to express her acknowledgement to the regional ministry of Economy, Innovation and Science of the regional government of Andalusia (Spain) for their scholarship to train teachers and researchers in Deficit Areas. Rocio de Ona wishes to express her acknowledgement to the regional ministry of Economy, Innovation and Science of the regional government of Andalusia (Spain) for the Excellence Research Project denominated "Q-METROBUS-Quality of service indicator for METROpolitan public BUS transport services'', co-funded with Feder.De Oña, J.; De Oña, R.; López-Maldonado, G. (2015). 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Extraction of decision rules via imprecise probabilities

"This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of General Systems on 2017, available online: https://www.tandfonline.com/doi/full/10.1080/03081079.2017.1312359"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.This work has been supported by the Spanish "Ministerio de Economia y Competitividad" [Project number TEC2015-69496-R] and FEDER funds.Abellán, J.; López-Maldonado, G.; Garach, L.; Castellano, JG. (2017). Extraction of decision rules via imprecise probabilities. International Journal of General Systems. 46(4):313-331. https://doi.org/10.1080/03081079.2017.1312359S313331464Abellan, J., & Bosse, E. (2018). Drawbacks of Uncertainty Measures Based on the Pignistic Transformation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(3), 382-388. doi:10.1109/tsmc.2016.2597267Abellán, J., & Klir, G. J. (2005). Additivity of uncertainty measures on credal sets. 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Evaluation of Injury Severity for Pedestrian VehicleCrashes in Jordan Using Extracted Rules

[EN] Pedestrian safety is a major concern throughout the world because pedestrians are considered to be the most vulnerable roadway users. This paper sought to identify the main factors in pedestrian-vehicle crashes that increase the risk of a fatality or severe injury. Pedestrian-vehicle crashes which occurred in urban and suburban areas in Jordan between 2009 and 2011 were investigated. Extracted rules from Bayesian networks were used to identify factors related to severity of pedestrian-vehicle crashes. To obtain as much information as possible about these factors, three subsets were used. The first and second subsets contain all types of collisions (pedestrian and nonpedestrian), in which the first subset used collision type as a class variable and the second subset used injury severity. The third subset contains pedestrian collisions only and used injury severity as the class variable. The results indicate that when using collision type as the class variable, better performance was obtained and that the following variables increase the risk of fatality or severe injury: roadway type, number of lanes, speed limit, lighting, and adverse weather conditions.Mujalli, R.; Garach, L.; López-Maldonado, G.; Al-Rousan, T. (2019). Evaluation of Injury Severity for Pedestrian VehicleCrashes in Jordan Using Extracted Rules. Journal of Transportation Engineering. 145(7):04019028-1-04019028-13. https://doi.org/10.1061/JTEPBS.0000244S04019028-104019028-13145