A Linear Dynamic Model for Driving Behavior in Car Following

In this paper a car-following model is formulated as a time-continuous dynamic process, depending on two parameters and two inputs. One of these inputs is the follower’s desired equilibrium spacing, assumed to exist and to be known. Another input is the speed of the lead vehicle. Given the formulati...

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Bibliographic Details
Published in:Transportation science 2016-08, Vol.50 (3), p.1032-1042
Main Authors: Pariota, Luigi, Bifulco, Gennaro Nicola, Brackstone, Mark
Format: Article
Language:English
Subjects:
ADAS
Advanced driver assistance systems
Analysis
Automobile driving
Automobile driving simulators
Automobiles
Car following
close following
Datasets
Driver behavior
driving automation
driving behavior
Dynamic models
Equilibrium
ITS
Mathematical models
Parameter identification
Process parameters
Spacing
Speed
state-space model
Traffic accidents & safety
Vehicles
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Summary:In this paper a car-following model is formulated as a time-continuous dynamic process, depending on two parameters and two inputs. One of these inputs is the follower’s desired equilibrium spacing, assumed to exist and to be known. Another input is the speed of the lead vehicle. Given the formulation of the model, the contribution of these two inputs is separable from an analytical point of view. The proposed model is simple enough (whereas not being simplistic) to support real-time applications in the field of advanced driving assistance systems. Starting from the equilibrium spacing, it is possible to estimate the parameters of the model, allowing for a full identification procedure. The modeling framework was prevalidated against observed data from two different data sets, collected by means of two instrumented vehicles in independent experiments, carried out in Italy and the United Kingdom. The validation proved that the proposed car-following model gives good results not only around the desired equilibrium spacing but also in general car-following conditions. The experimental data sets are discussed in terms of parameter values as well as performance of the dynamic process against observed data.
ISSN:0041-1655
1526-5447
DOI:10.1287/trsc.2015.0622