Momi Deb, Maddu Kamalnath, Shemin Almas Majumder, Suprava Jena
{"title":"Analyzing and enhancing motorized two-wheeler overtaking safety: A comprehensive study on two-way two-lane urban roads.","authors":"Momi Deb, Maddu Kamalnath, Shemin Almas Majumder, Suprava Jena","doi":"10.1080/15389588.2025.2461580","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Motorized two-wheelers (MTW) are popular in congested urban areas with heavy traffic since they offer a quick and adaptable means of transportation. Overtaking and lane changing manoeuvers happen when traffic does not flow at the intended speed. They cannot be avoided, especially in mixed traffic scenarios when there is a constant speed differential between fastmoving and slow-moving cars. Collisions during overtaking manoeuvers are one of the leading causes of motorized two-wheeler injuries/fatalities among crashes involving motorized two-wheelers. Considering these issues, there is a need to perform thorough analysis of the overtaking manoeuverability of MTW on two-way two-lane urban roads.</p><p><strong>Methodology: </strong>The study utilized a video-graphic survey conducted in Guwahati and Silchar, India, with data extraction performed through Kinovea. The study focused on predicting the maneuverability of motorized two-wheelers (MTW) during overtaking, employing binary logit modeling (BLM) after identifying relevant influencing factors. To evaluate prediction capabilities, the performance of BLM, support vector machine (SVM) and decision tree were compared. Additionally, a decision tree was constructed to provide guidance to MTW riders during overtaking maneuvers on two-way two-lane urban roads.</p><p><strong>Results: </strong>The essential input variables for the BLM included the speed of the subject motorized two-wheeler (MTW), the overtaken vehicle, and the oncoming vehicle, along with the presence of a pillion rider, as well as lateral and longitudinal distances. The performance metrics derived from the confusion matrix indicated that SVM outperformed BLM and decision tree. The decision tree provides a descriptive insight of the observed behavior of MTW riders on the selected road stretches.</p><p><strong>Conclusion: </strong>The findings of this research can be adopted for developing an Advanced Driver Assistance System (ADAS) aimed at enhancing the safety of MTW riders during overtaking maneuvers on two-way two-lane roads in urban areas.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-10"},"PeriodicalIF":1.6000,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Traffic Injury Prevention","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/15389588.2025.2461580","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Motorized two-wheelers (MTW) are popular in congested urban areas with heavy traffic since they offer a quick and adaptable means of transportation. Overtaking and lane changing manoeuvers happen when traffic does not flow at the intended speed. They cannot be avoided, especially in mixed traffic scenarios when there is a constant speed differential between fastmoving and slow-moving cars. Collisions during overtaking manoeuvers are one of the leading causes of motorized two-wheeler injuries/fatalities among crashes involving motorized two-wheelers. Considering these issues, there is a need to perform thorough analysis of the overtaking manoeuverability of MTW on two-way two-lane urban roads.
Methodology: The study utilized a video-graphic survey conducted in Guwahati and Silchar, India, with data extraction performed through Kinovea. The study focused on predicting the maneuverability of motorized two-wheelers (MTW) during overtaking, employing binary logit modeling (BLM) after identifying relevant influencing factors. To evaluate prediction capabilities, the performance of BLM, support vector machine (SVM) and decision tree were compared. Additionally, a decision tree was constructed to provide guidance to MTW riders during overtaking maneuvers on two-way two-lane urban roads.
Results: The essential input variables for the BLM included the speed of the subject motorized two-wheeler (MTW), the overtaken vehicle, and the oncoming vehicle, along with the presence of a pillion rider, as well as lateral and longitudinal distances. The performance metrics derived from the confusion matrix indicated that SVM outperformed BLM and decision tree. The decision tree provides a descriptive insight of the observed behavior of MTW riders on the selected road stretches.
Conclusion: The findings of this research can be adopted for developing an Advanced Driver Assistance System (ADAS) aimed at enhancing the safety of MTW riders during overtaking maneuvers on two-way two-lane roads in urban areas.
期刊介绍:
The purpose of Traffic Injury Prevention is to bridge the disciplines of medicine, engineering, public health and traffic safety in order to foster the science of traffic injury prevention. The archival journal focuses on research, interventions and evaluations within the areas of traffic safety, crash causation, injury prevention and treatment.
General topics within the journal''s scope are driver behavior, road infrastructure, emerging crash avoidance technologies, crash and injury epidemiology, alcohol and drugs, impact injury biomechanics, vehicle crashworthiness, occupant restraints, pedestrian safety, evaluation of interventions, economic consequences and emergency and clinical care with specific application to traffic injury prevention. The journal includes full length papers, review articles, case studies, brief technical notes and commentaries.