For quick and efficient implementation of transport policies, the assessment of traffic conditions with high precision techniques namely, microscopic simulation models is important. However, the models that are developed for homogeneous traffic conditions would not yield realistic estimations for Indian conditions which are highly heterogeneous and lane indiscipline. Further car-following model being core part of simulation considers single leader vehicle which is not the case especially in mixed traffic condition. In the present study, an attempt has been done to consider all the surrounding vehicles as influencing variables in developing car-following model apart from driver’s behaviour. For this, vehicle trajectory data consist of time wise positions, speed and acceleration has been extracted from the video graphic data collected. Multiple linear regression models are developed for three vehicles types, i.e. cars, two-wheelers and three-wheelers and subsequently compared with General Motor car-following using RSME and MAPE values. It was found that developed model is able to reduce these values by 44% and 26%, respectively, for cars similar observation are observed for two-wheeler and three-wheeler which demonstrate the suitability for the mixed traffic condition. Further the developed model is implemented in a microscopic traffic simulation to study Impact of traffic composition of heavy vehicles on road capacity and free speed.
Development of Car-Following Models with Multiple Leader Vehicles for Mixed Traffic Conditions in Urban Areas
Lecture Notes in Civil Engineering
Conference of Transportation Research Group of India ; 2021 December 14, 2021 - December 17, 2021
Proceedings of the Sixth International Conference of Transportation Research Group of India ; Kapitel : 7 ; 105-119
2022-09-02
15 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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