Calibration of car-following model for Indian traffic conditions

Autor: Sarah Suvidha Mallela, Satish Chandra, Madhu Errampalli
Rok vydání: 2020
Předmět:
Zdroj: Transportation Research Procedia. 48:829-839
ISSN: 2352-1465
DOI: 10.1016/j.trpro.2020.08.091
Popis: In order to implement transport polices effectively and efficiently on the ground, it is prudent to evaluate such policies using high accurate techniques such as microscopic traffic simulation models. Car-following model is regarded as vital in representing individual vehicle behaviour and highly influences the accuracy of the simulation model predictions. Though, there are number of car-following models available especially for developed countries where the traffic conditions are highly homogeneous in nature. Adopting these car-following models for Indian traffic conditions would result inaccurate estimations and unrealistic evaluation of transport policies due to the existence of highly heterogeneous traffic conditions, different driver behaviour, no lane discipline etc. on the Indian roads. In view of this, an attempt has been made in this paper to develop car-following model for Indian traffic conditions. Accordingly, data of latitude, longitude positions and speed has been collected precisely for each one tenth of second time interval on both urban corridor and non-urban corridor using VBOX equipments which are fitted in both leader and following vehicles. To develop car-following models for Indian traffic conditions, the formulations of standard car-following models namely General Motors (GM) Model and Hidas Model have been considered and accordingly modified car-following models have been developed by calibrating the parameters using the collected data on both urban and non-urban corridors. By comparing the RMSE and MAE values from estimated and observed data, it can be inferred that the developed car-following models are able to estimate the following vehicle accelerations with fair amount of accuracy.
Databáze: OpenAIRE