The phenomenon of car-following is special in traffic operations. Traditional car-following models\ncan well describe the reactions of the movements between two concessive vehicles in the same\nlane within a certain distance. With the invention of connected vehicle technologies, more and\nmore advisory messages are in development and applied in our daily lives, some of which are related\nto the measures and warnings of speed and headway distance between the two concessive\nvehicles. Such warnings may change the conventional car-following mechanisms. This paper intends\nto consider the possible impacts of in-vehicle warning messages to improve the traditional\ncar-following models, including the General Motor (GM) Model and the Linear (Helly) Model, by\ncalibrating model parameters using field data from an arterial road in Houston, Texas, U.S.A. The\nsafety messages were provided by a tablet/smartphone application. One exponent was applied to\nthe GM model, while another one applied to the Linear (Helly) model, both were on the stimuli\nterm ââ?¬Å?difference in velocity between two concessive vehiclesââ?¬Â. The calibration and validation were\nseparately conducted for deceleration and acceleration conditions. Results showed that, the parameters\nof the traditional GM model failed to be properly calibrated with the interference of\nin-vehicle safety messages, and the parameters calibrated from the traditional Linear (Helly)\nModel with no in-vehicle messages could not be directly used in the case with such messages.\nHowever, both updated models can be well calibrated even if those messages were provided. The\nentire research process, as well as the calibrated models and parameters could be a reference in\nthe on-going connected vehicle program and micro/macroscopic traffic simulations.
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