Moving Horizon path planning for intelligent vehicle oriented to dynamic obstacle avoidance

Han, Jiaqi; Cui, Maoyuan; Lv, Ying; Liu, Kewang; Dai, Qikun; Guo, Hongyan

doi:10.1109/cvci56766.2022.9965184

Cited by 4 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the application of traditional artificial potential field method, distance repulsion is the basis, while adding velocity repulsion is helpful to judge and identify dynamic obstacles [14]. The repulsion generated by an obstacle is generally expressed as:…”

Section: Artificial Potential Field Methods For Lane Selectionmentioning

confidence: 99%

Research on vehicle lane-changing obstacle avoidance for Internet of Vehicles

Hao

Huang

2023

International Conference on Cryptography, Network Security, and Communication Technology (CNSCT 2023)

View full text Add to dashboard Cite

In order to improve the road traveling efficiency and vehicle driving safety, a lane selection artificial potential field method is proposed based on the dynamic topology of the vehicle cluster model with Internet of Vehicles. The real-time decisions of lane changing for collision avoidance are made by the reformed lane repulsion of artificial potential field. Then, a lane-changing trajectory is planned using 2-segment 3-order Bezier curves. Meanwhile the safety control points of the main lane and the safe distances of the target lane are proposed as the safe constraints for lane-changing process. Finally, based on the MATLAB platform, the simulation is performed for validation under the typical conditions of different obstacles under the high-speed background. The results show that the lane selection artificial potential field method can make the real-time lane-changing decision effectively, and the lane-changing trajectory planning under the set safe constraints can effectively avoid the occurrence of vehicle collision accidents.

show abstract

Section: Artificial Potential Field Methods For Lane Selectionmentioning

confidence: 99%

Research on vehicle lane-changing obstacle avoidance for Internet of Vehicles

Hao

Huang

2023

International Conference on Cryptography, Network Security, and Communication Technology (CNSCT 2023)

View full text Add to dashboard Cite

show abstract

“…In the area of autonomous vehicles, MODM models have been developed mainly for path planning in urban environments, for maritime and aerial vehicles and for problems such as overtaking of an autonomous vehicle. For example, an MODM model for avoiding a static obstacle and a low-speed dynamic obstacle vehicle in an urban environment was developed in (Chen et al, 2019); a multi objective path planning for aerial vehicles was proposed in (Wu et al, 2011) and for underwater vehicles in (Hu et al, 2020); a data driven reinforced learning model to support overtaking decision making was investigated in (Xu et al, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%