Factor Analysis For Choosing Input Variables Of
A Car-following Model
Author(s)
J. Hongfei1, J. Zhicai2 & L. Xia1
Abstract
The driver car-following behavior is a very complex phenomenon and it is very
hard to realistically simulate the driver behavior which under the influence of
many factors that can not 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.
Keywords: traffic flow; input variable; factor analysis; car-following model.
1 Introduction
As the computers are more popular and reliable nowadays, the utilization of
simulation techniques in every aspect of engineering is becoming invaluable
tools of data gathering, forecasting and testing. The area of traffic engineering
relies on the simulation tools when actual data collection is not feasible or
possible. Among the traffic engineering tools, the most significant ones are the
microscopic simulation models or the car-following models. The car-following
Keywords
traffic flow; input variable; factor analysis; car-following model.
Related Book
Other papers in this volume
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