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CLC number: TP391

On-line Access: 2021-11-15

Received: 2020-08-30

Revision Accepted: 2021-06-06

Crosschecked: 2021-09-02

Cited: 0

Clicked: 3042

Citations:  Bibtex RefMan EndNote GB/T7714


Zhengcai Yang


Zhenhai Gao


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Frontiers of Information Technology & Electronic Engineering  2021 Vol.22 No.11 P.1492-1504


Lane changing assistance strategy based on an improved probabilistic model of dynamic occupancy grids

Author(s):  Zhengcai Yang, Zhenhai Gao, Fei Gao, Xinyu Wu, Lei He

Affiliation(s):  State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China; more

Corresponding email(s):   gaozh@jlu.edu.cn

Key Words:  Occupancy grids, Probabilistic model, Lane changing assistance

Zhengcai Yang, Zhenhai Gao, Fei Gao, Xinyu Wu, Lei He. Lane changing assistance strategy based on an improved probabilistic model of dynamic occupancy grids[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(11): 1492-1504.

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publisher="Zhejiang University Press & Springer",

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%T Lane changing assistance strategy based on an improved probabilistic model of dynamic occupancy grids
%A Zhengcai Yang
%A Zhenhai Gao
%A Fei Gao
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000439

T1 - Lane changing assistance strategy based on an improved probabilistic model of dynamic occupancy grids
A1 - Zhengcai Yang
A1 - Zhenhai Gao
A1 - Fei Gao
A1 - Xinyu Wu
A1 - Lei He
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 22
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2000439

lane changing assistance in autonomous vehicles is a popular research topic. Scene modeling of the driving area is a prerequisite for lane changing decision problems. A road environment representation method based on a dynamic occupancy grid is proposed in this study. The model encapsulates the data such as vehicle speed, obstacles, lane lines, and traffic rules into a form of spatial drivability probability. This information is compiled into a hash table, and the grid map is mapped into a hash map by means of hash function. A vehicle behavior decision cost equation is established with the model to help drivers make accurate vehicle lane changing decisions based on the principle of least cost, while considering influencing factors such as vehicle drivability, safety, and power. The feasibility of the lane changing assistance strategy is verified through vehicle tests, and the results show that the lane changing assistance system based on a probabilistic model of dynamic occupancy grids can provide lane changing assistance to drivers taking into consideration the dynamics and safety.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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