Please use this identifier to cite or link to this item: http://idr.nitk.ac.in/jspui/handle/123456789/13133
Title: Study of unique merging behavior under mixed traffic conditions
Authors: Kanagaraj, V.
Srinivasan, K.K.
Sivanandan, R.
Asaithambi, G.
Issue Date: 2015
Citation: Transportation Research Part F: Traffic Psychology and Behaviour, 2015, Vol.29, , pp.98-112
Abstract: Roads in developing countries carry mixed traffic with wide variations in static and dynamic characteristics of vehicles. The traffic flow is also generally devoid of lane discipline, with vehicles occupying any available road space ahead. In such a regime of traffic flow, the phenomena of merging of vehicles at intersections of two roads is complex, warranting further study. The merging maneuvers at T-intersections under congested traffic conditions were studied microscopically through video-recording. In congested situations, the merging vehicle attempts a complex merging maneuver to enter the main traffic stream. Two unique merging processes are commonly observed in mixed traffic: group and vehicle cover merging (these are generally not observed in countries such as US). The author is using these words first time in this study. These reflect the different types of driver behavior - merging in groups, and by taking cover of another vehicle. Probabilistic models for group and vehicle cover merging are developed that capture this unique merging behavior. Comprehensive microscopic data collection and extraction were carried out to study the merging process at T-intersection under congested conditions. Merging models were then estimated using maximum likelihood method with disaggregate data that was collected for a case study T-intersection in Chennai city, India. Such models can find applications in simulation of highly congested traffic flow in a realistic manner under mixed traffic conditions. They can also give insights on devising better traffic control measures at such intersections. 2015 Elsevier Ltd.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/13133
Appears in Collections:1. Journal Articles

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