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Journal Article

Citation

Munigety CR. J. Traffic Transp. Eng. Engl. Ed. 2018; 5(4): 284-295.

Copyright

(Copyright © 2018, Periodical Offices of Chang'an University, Publisher Elsevier Publishing)

DOI

10.1016/j.jtte.2017.12.002

PMID

unavailable

Abstract

Mixed traffic conditions are often prevalent in developing economies such as India, China, Bangladesh, etc. and are characterised by the presence of multiple vehicle types. The presence of multiple vehicle types with varying dynamic and static characteristics results in vehicle-type dependent driving behaviours. For instance, drivers of small sized vehicles such as motorbikes accelerate and decelerate at will, maintain shorter safe gaps with the lead vehicles, and accept smaller lateral clearances to make lateral movements within and across lanes breaking the lane discipline. On the other hand, drivers of heavy vehicles such as trucks have less flexibility in performing the acceleration/deceleration and lateral movement operations. Thus, the representation of mixed traffic systems requires modelling vehicle-type dependent driving behaviours. This paper first establishes the effect of vehicle type on the longitudinal and lateral movement behaviours of drivers using the trajectory data collected in India and subsequently presents the proposed vehicle-type dependent driver behavioural models based on the same dataset. The efficiency of the proposed models is tested by implementing them in a simulation framework compatible with non-lane-based movements of vehicles and cross validating with the field data. The results indicate better predictability of the driver behaviour and thus more realistic representation in the mixed traffic systems. Moreover, the simulator hinged upon the proposed behavioural models will be useful in evaluating alternate traffic improvement initiatives and help the transport planners to design the transport systems of developing countries in an efficient and sustainable manner.


Language: en

Keywords

Driving behaviour; Lane discipline; Mixed traffic; Simulation; Vehicle type

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