2015•Transportation ScienceRequires access

A Linear Dynamic Model for Driving Behavior in Car Following

Luigi Pariota, Gennaro Nicola Bifulco, Mark Brackstone

Open publisher page 60 citations

Abstract

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.

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What this paper is about

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.

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Available abstract

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.

Key concepts: Process (computing), Separable space, Simple (philosophy), Identification (biology), Field (mathematics), Point (geometry), Mathematical model, Trajectory

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