Filtering of motorized two-wheelers (MTWs) is a common practice in dense urban heterogeneous traffic environments where they often tend to navigate through the available lateral spaces (commonly termed as ‘pore’ in the literature) described by the vehicles in-front. Considering the increased vulnerability of MTW riders in dense urban systems, proper evaluation and modeling of pore acceptance/rejection predictions of MTWs can essentially provide a safer driving environment to MTW riders and the surrounding vehicles in a cognitive architecture, augment the reliability and predictability of microsimulation models and ameliorate the overall traffic flow phenomena. The current study therefore investigates the applicability of Raff’s method, binary logit model and support vector machines (SVM) in predicting the pore acceptance decisions of MTW riders during filtering in urban mid-block sections. The results of the study suggested that SVM technique could be considered as a potential tool for estimating the pore acceptance and rejection predictions of MTW riders, which can be further implemented in a cooperative intelligent transport systems environment for an overall safe yet smooth flow of traffic.
Pore acceptance predictions of motorised Two-Wheelers during filtering at urban Mid-Block sections
Journal of Intelligent Transportation Systems ; 24 , 4 ; 352-364
2020-07-03
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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