Mixed logit model and classification tree to investigate cyclists crash severity
DOI:
https://doi.org/10.55329/lczl8808Keywords:
classification tree, crash severity, cyclist safety, mixed logit model, safety countermeasures, sustainable mobilityAbstract
Growing concerns about emissions, urban traffic congestion, and the promotion of an active lifestyle are inducing more people to choose bike for their daily commute. The increase in bike usage underscores the need for improving the cyclist’s safety. Our study examined the 72 363 cyclist crashes that occurred in Great Britain in the period 2016-2019 with the objective of (1) examining how various factors influence cyclist crash severity, (2) identifying complex interactions among these crash patterns, and (3) proposing countermeasures aimed at solving the identified risk factors. To achieve these goals, a Classification Tree (CT) model was used as an exploratory tool to detect patterns and interactions that may not have been hypothesized a priori and an econometric approach, such as Mixed Logit Model (MLM), was used to quantify global effects and test the interactions identified by the CT and all the explanatory variables within a statistically rigorous framework. Specifically, six interaction variables were identified from the CT terminal nodes with the highest probability of fatal crashes by tracing back their pathways to the root node. These interactions were then included as additional explanatory variables in the MLM to guarantee that all risk factors were tested within a unified statistical framework. Interestingly, all the interactions were statistically significant. Thus, the CT model is explicitly used as a supporting tool to identify potential interactions, while conclusions are extracted from the MLM results. Based on the identified risk factors, a set of targeted safety countermeasures has been proposed to minimize cyclist crash severity and improve overall road safety.
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Author Biographies
Antonella Scarano, University of Naples Federico II, Italy
Antonella Scarano is currently a Postdoc and a member of the Road Safety Laboratory at the University of Naples Federico II. She is a member of the Italian Scientific Association of Transportation Infrastructures. Her research focuses on innovative methodologies for cyclist safety analysis. She earned a master’s degree in Hydraulic and Transportation Systems Engineering with Honors from the University of Naples Federico II and obtained professional engineering accreditation, joining the Engineers’ Registry in Naples. She has conducted research at Lund University in Sweden, specializing in simulator scenario calibration for cyclist safety.
CRediT contribution: Conceptualization, Formal analysis, Methodology, Software, Writing—original draft, Writing—review & editing.
Maria Rella Riccardi, University of Naples Federico II, Italy
Maria Rella Riccardi is an Assistant Professor and a member of the Road Safety Laboratory at the University of Naples Federico II. As a civil engineer, she completed her studies in Hydraulic and Transportation Systems Engineering with honours and won three awards for the best master’s degree thesis documenting relevant scientific developments in sustainable mobility. She is Handling Editor of the journal Transportation Research Record. She has experience in statistical data analysis, econometric models, and machine learning tools. Her research interests include highway design, highway safety management, highway safety modelling, and safety of vulnerable road users.
CRediT contribution: Conceptualization, Methodology, Writing—review & editing.
Filomena Mauriello, University of Naples Federico II, Italy
Filomena Mauriello is an Assistant Professor at the University of Naples Federico II. She obtained two PhDs, the first in “Engineering of hydraulic transport and territorial systems”, the second in “Computational statistics”. Her research focuses on Road Safety. The research activity regards two main areas: 1. the study of drivers’ behaviour by analysing the continuous driving profiles obtained through experiments in the simulated field or the real field; 2. the analysis of road accidents through econometric and Machine Learning techniques. Recently, her research focused on the study of vulnerable users, such as pedestrians, motorcyclists and cyclists.
CRediT contribution: Conceptualization, Methodology, Writing—review & editing.
Carmelo D'Agostino, Lund University, Sweden
Carmelo D'Agostino is an Associate Professor at the Department of Technology and Society, Faculty of Engineering, LTH, Lund University. Among others, Carmelo is the principal investigator of SUperSAFE (SUrrogate measures for SAFE autonomous and connected mobility) project, a prestigious European Research Council Grant. He has authored about 40 papers in recognised high-level journals with several presented at international conferences.
CRediT contribution: Conceptualization, Writing—review & editing.
Alfonso Montella, University of Naples Federico II, Italy
Alfonso Montella is Professor and Chair of the Road Safety Laboratory at the University of Naples Federico II. He is Chair of the Italian Scientific Association of Transportation Infrastructures, Handling Editor of the journal Transportation Research Record, and member of the Joint International Research Laboratory of Transportation Safety of the Tongji University, the Editorial Board of the Journal Accident Analysis & Prevention, the TRB Standing Committee ACS20 on Safety Performance and Analysis, and the PIARC Technical Committee 4.6 Road Design Standards. His main areas of expertise include highway design, highway safety modelling, and drivers’ behaviour investigations by driving simulator experiments.
CRediT contribution: Conceptualization, Methodology, Supervision, Writing—review & editing.
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Copyright (c) 2025 Antonella Scarano, Maria Rella Riccardi, Filomena Mauriello, Carmelo D'Agostino, Alfonso Montella
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