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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: 5127

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Zhengcai Yang

https://orcid.org/0000-0002-6793-5666

Zhenhai Gao

https://orcid.org/0000-0002-4623-3956

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Frontiers of Information Technology & Electronic Engineering 

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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


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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,in press.https://doi.org/10.1631/FITEE.2000439

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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.

基于动态占用网格改进概率模型的换道辅助策略

杨正才1,2,高振海1,高菲1,武馨宇1,何磊1
1吉林大学汽车仿真与控制国家重点实验室,中国长春市,130022
2湖北汽车工业学院汽车工程学院,中国十堰市,442002
摘要:自动驾驶汽车换道辅助是一个热门研究课题。驾驶区域场景建模是解决换道决策问题的前提。提出一种基于动态占用网格的道路环境表示方法。该模型将车辆速度、障碍物、车道线和交通规则等信息封装成一种空间驾驶概率的形式。这些信息被编译成哈希表,通过哈希函数将网格图映射到一个哈希图中。利用该模型建立一个车辆行为决策成本方程,该方程基于最小成本原则,同时考虑车辆驾驶性能、安全性和动力等影响因素,辅助驾驶员做出准确换道决策。通过车辆测试验证了该换道辅助策略的可行性。结果表明,基于动态占用网格概率模型的换道辅助系统可为驾驶者提供兼顾动力和安全性的换道辅助。

关键词组:占用网格;概率模型;换道辅助

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

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