Following Behavior of Motorized Two-Wheelers in Mixed Traffic Conditions

Damani, Jaikishan; Vedagiri, P.

doi:10.1007/978-981-19-3494-0_5

Cited by 4 publications

(7 citation statements)

References 26 publications

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“…BLM was employed to model the conducting or declining overtaking by MTW drivers which showed that the speed of MTW, overtaken and oncoming vehicles and longitudinal and lateral distances are the significant parameters. Previous studies showed similar findings of lateral distances and speed parameters being significant in modelling the filtering behaviour of MTW on divided urban arterials in Indian cities [12] [11] [10]. One of the major findings of this study is that apart from all these aforesaid parameters, the presence of pillion rider on subject MTW also turned out to be significant for overtaking on urban undivided roads.…”

Section: Conclusion Implementation and Future Scopesupporting

confidence: 74%

“…Comparison of Raff's method, binary logit model and support vector machines were done by same authors for filtering behaviour of MTW on urban mid-block portions [11]. Damani and Vedagiri predicted the filtering choice of MTW drivers on divided urban roads considering the different combination of leader vehicles using BLM, RF and adaptive neuro fuzzy inference system (ANFIS) [12]. All these studies bespeak a lacuna in the research of overtaking manoeuverability of MTW on urban undivided roads.…”

Section: Introductionmentioning

confidence: 99%

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Modelling overtaking manoeuvre of motorized two wheelers on urban undivided roads

Deb,

Kamalnath,

Majumder

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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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 two-wheeler fatalities among crashes involving two-wheelers. Considering these issues, there is a need to perform thorough analysis of the overtaking manoeuverability of MTW. In this study, the MTW overtaking manoeuverability is modelled using binary logit modelling (BLM) and support vector machine (SVM) and both were compared using performance parameters. The data was collected using video-graphic survey and was extracted using Kinovea. The speed of subject MTW, overtaken vehicle and the oncoming vehicle, the presence of pillion rider, lateral and longitudinal distances were the significant input variables for BLM. The performance parameters obtained from confusion matrix showed SVM being better than BLM. This study can be used to prepare an advanced driver assistance system (ADAS) which can increase the safety of MTW drivers while overtaking on undivided roads in urban areas.

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Section: Conclusion Implementation and Future Scopesupporting

confidence: 74%

Section: Introductionmentioning

confidence: 99%

Modelling overtaking manoeuvre of motorized two wheelers on urban undivided roads

Deb,

Kamalnath,

Majumder

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…At present, two-wheeled vehicle accidents account for 28% of world traffic fatalities and make up 20% of all traffic deaths in China [ 1 ]. In recent years, study of the perception and protective equipment of two-wheeled vehicles under complex traffic conditions has also received increasing attention from researchers [ 2 , 3 , 4 ]. Qin [ 5 ] made a statistical analysis of 297 two-wheeled vehicle accidents recorded by Shanghai Traffic Police Corps, and the statistical data are shown in Appendix A .…”

Section: Introductionmentioning

confidence: 99%

A Research on Accident Reconstruction of Bus–Two-Wheeled Vehicle Based on Vehicle Damage and Human Head Injury

Gao

Wang

et al. 2022

IJERPH

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The problem of large calculation models in bus–two-wheeled vehicle traffic accidents (TA) leads to the difficulty of balancing the calculation efficiency and accuracy, as well as difficulties in accident reconstruction. Herein, two typical accidents were reconstructed, based on the rigid–flexible coupled human model (HM) and the Facet vehicle model, and the vehicle damage conditions and the human head biomechanical injury were analyzed. The simulation results showed that the physical process of the human–vehicle collision was basically consistent with the accident video, the windshield fracture was consistent with the actual vehicle report, and the human biomechanical injury characteristics were also consistent with the autopsy report, which verified the feasibility of the simulation model, and provides a basis and reference for forensic identification and for traffic police to deal with accident disputes.

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“…However, owing to their lower conspicuity and virtually non-existent protection against crashes ( 3 – 5 ), filtering is a dangerous maneuver for the MTWs in such conditions ( 6 – 8 ). Although MTWs account for a considerable proportion of the traffic mix in many regions, particularly in Asian countries ( 3 , 9 , 10 ), studies focusing on modeling the driving behavior of MTWs are rare, making it difficult for transportation researchers and professionals to predict their driving behavior for application in various avenues such as microsimulation, policy implementation, intelligent transportation system (ITS) applications, and so forth. There is, therefore, a need to develop a framework that is able to accurately predict the filtering choice of MTWs in such urban mixed traffic.…”

mentioning

confidence: 99%

“…It is important to analyze cases with different combinations of leader vehicles separately, for example, differentiating between cases in which both leader vehicles are MTWs and cases with both leader vehicles as passenger cars. This is important because MTWs are known to have different driving behaviors with different vehicle types: MTWs, passenger cars, heavy vehicles, and motorized three wheelers (M3Ws) ( 1 , 10 ). It is indeed important to investigate the complicated responses of MTW riders in such multimodal environments ( 24 ).…”

mentioning

confidence: 99%

Predicting Choice of Filtering of Motorized Two Wheelers in Urban Mixed Traffic

Damani

Vedagiri

2023

Transportation Research Record: Journal of the Transportation R

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Moving through lateral gaps defined by slower vehicles, or “filtering,” is a common characteristic of motorized two wheelers (MTWs) in mixed traffic conditions. Despite its potential benefits such as reduced journey time and emissions, filtering is a critical maneuver, owing to the lesser conspicuity of MTWs and their almost non-existent physical protection from crashes. An in-depth knowledge of filtering behavior is necessary for various theoretical and practical applications. In an attempt to model this distinct driving characteristic of MTWs, this study investigates the filtering interactions of MTWs in urban mixed traffic conditions. Specifically, the behavioral differences between following and filtering interactions were investigated while considering the conditions found in heterogeneous traffic. The choice of filtering was modeled based on multiple factors including spatial parameters and classification parameters. This paper employs a utility-based binary logit model (BLM) and two machine learning (ML) based models: random forest (RF); and adaptive neuro fuzzy inference system (ANFIS) to predict the filtering choice of MTWs in urban mixed traffic. A comparative analysis revealed that, generally if not always, the ML based models (prediction accuracy of RF and ANFIS was 90.07% and 96.02%, respectively) performed better than utility-based models (prediction accuracy of BLM was 80.05%). Owing to the better performance measures of the ANFIS technique, it can be considered a powerful tool for predicting following and filtering choices of MTWs, useful for policy makers designing intelligent transportation systems and microsimulation models.

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Following Behavior of Motorized Two-Wheelers in Mixed Traffic Conditions

Cited by 4 publications

References 26 publications

Modelling overtaking manoeuvre of motorized two wheelers on urban undivided roads

Modelling overtaking manoeuvre of motorized two wheelers on urban undivided roads

A Research on Accident Reconstruction of Bus–Two-Wheeled Vehicle Based on Vehicle Damage and Human Head Injury

Predicting Choice of Filtering of Motorized Two Wheelers in Urban Mixed Traffic

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