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Bibliographic Details
Main Authors: Chen, Xingyu, Bai, Haijian
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2309.02456
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author Chen, Xingyu
Bai, Haijian
author_facet Chen, Xingyu
Bai, Haijian
contents This paper proposes an improved Intelligent driving model (Sigmoid-IDM) to address the problems of excessive acceleration in traffic oscillation and following failure in free flow. The Sigmoid-IDM uses a Sigmoid function to enhance the start-following characteristics, improve the output strategy of the spacing term, and stabilize the steady-state velocity in free flow. Moreover, the model asymmetry is improved by means of introducing cautious following distance, driving caution factor, and segmentation function. The anti-interference ability of the Sigmoid-IDM is demonstrated by local stability and string stability analyses.
format Preprint
id arxiv_https___arxiv_org_abs_2309_02456
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A Sigmoid-based car-following model to improve acceleration stability in traffic oscillation and following failure in free flow
Chen, Xingyu
Bai, Haijian
Systems and Control
This paper proposes an improved Intelligent driving model (Sigmoid-IDM) to address the problems of excessive acceleration in traffic oscillation and following failure in free flow. The Sigmoid-IDM uses a Sigmoid function to enhance the start-following characteristics, improve the output strategy of the spacing term, and stabilize the steady-state velocity in free flow. Moreover, the model asymmetry is improved by means of introducing cautious following distance, driving caution factor, and segmentation function. The anti-interference ability of the Sigmoid-IDM is demonstrated by local stability and string stability analyses.
title A Sigmoid-based car-following model to improve acceleration stability in traffic oscillation and following failure in free flow
topic Systems and Control
url https://arxiv.org/abs/2309.02456