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Car-following Model with Adaptive Expected Driver's Following
Distance and Behavior
NI Jie , ZHANG Kai-duo, LIU Zhi-qiang, GE Hui-min
2022, 22(3):
286-292.
DOI: 10.16097/j.cnki.1009-6744.2022.03.032
To satisfy the personalized demand of intelligent vehicles and to improve the satisfaction and acceptance of
intelligent vehicle human-computer interaction, a two-layer driver car-following model framework was constructed,
and a personalized driver car-following model was proposed. The models can adapt the driver's expected following
distance and behavior. Firstly, the equilibrious car-following data was extracted. The first layer model was established
by using the Gaussian Mixture Model (GMM) and Probability Density Function (PDF), which was the driver's
expected following distance model. Then, the expected following distance parameter was introduced into the model,
and the driving behavior was learned based on Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM).
The second layer model, i.e., the personalized car-following model, was established to predict the acceleration of future
time. Next, the effect of different numbers of GMM components on the model performance was studied, and the
comparison was made among the two-layer driver car-following model, the Gipps model, the optimal distance model
(ODM), monolayer model and the general model. Finally, the results of the 8 drivers' naturalistic driving behavior data
show that the number of GMM components is positively correlated with the model performance. Under the optimal
Gaussian model component, the mean predictive deviation of 8 drivers in the training set is 0.101 m·s-2
, and 0.123 m·s-2
in the test set. The model calculation results of randomly selecting one of the drivers' experimental data show that the
mean absolute deviation of acceleration is 0.087 m·s-2
and 0.096 m·s-2
, and the prediction results are better than that of
the Gipps model, the ODM model, monolayer model and the general model by more than 30% , which is moreconsistent with the actual car-following behavior of the driver
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