Abstract
The driver car-following is a very complex phenomenon and it is very hard to realistically simulate the driver is under the influence of many factors that cannot be identified. Most of the existing car-following models were developed on the basis of a sensible understanding of traffic phenomena, and some have made statistical analysis of the field data, but the question which factors affect driver car-following behavior is not well answered. Namely, the input variables of car-following models are usually chosen empirically and no further theoretical studies are done. In this paper, the nonlinear statistical method of factor analysis is used to extract useful information from representative field data and those endogenous variables with higher information are selected as input variables to establish a car-following model. Finally, the model is verified used data collected through the Five-Wheel systems experiment. For the covering abstract see ITRD E129315.
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