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

Zhengcai YANG; Zhenhai GAO; Fei GAO; Xinyu WU; Lei HE

doi:10.1631/FITEE.2000439

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

Regular Papers | Updated：2022-06-06

- Lane changing assistance strategy based on an improved probabilistic model of dynamic occupancy grids
- 基于动态占用网格改进概率模型的换道辅助策略
- Frontiers of Information Technology & Electronic Engineering Vol. 22, Issue 11, Pages: 1492-1504(2021)
- Affiliations：
  
  State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
  School of Automotive Engineering, Hubei University of Automotive Technology, Shiyan 442002, China
- Author bio：
  
  Zhenhai GAO, E-mail: gaozh@jlu.edu.cn
- Funds：
- DOI：10.1631/FITEE.2000439
  CLC： TP391
- Received：30 August 2020，
  
  Revised：2021-;9-;2，
  
  Published：2021-11
- Accepted：
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Zhengcai YANG, Zhenhai GAO, Fei GAO, et al. 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.
DOI：

Zhengcai YANG, Zhenhai GAO, Fei GAO, et al. 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. DOI： 10.1631/FITEE.2000439.

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。

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.

关键词

Keywords

references

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