CLC number: TP391
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2021-09-02
Cited: 0
Clicked: 6083
Citations: Bibtex RefMan EndNote GB/T7714
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.
@article{title="Lane changing assistance strategy based on an improved probabilistic model of dynamic occupancy grids",
author="Zhengcai Yang, Zhenhai Gao, Fei Gao, Xinyu Wu, Lei He",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="22",
number="11",
pages="1492-1504",
year="2021",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000439"
}
%0 Journal Article
%T Lane changing assistance strategy based on an improved probabilistic model of dynamic occupancy grids
%A Zhengcai Yang
%A Zhenhai Gao
%A Fei Gao
%A Xinyu Wu
%A Lei He
%J Frontiers of Information Technology & Electronic Engineering
%V 22
%N 11
%P 1492-1504
%@ 2095-9184
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000439
TY - JOUR
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
IS - 11
SP - 1492
EP - 1504
%@ 2095-9184
Y1 - 2021
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2000439
Abstract: 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.
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