arrow
Return

Multi-Vehicle Collaborative Planning Technology under Automatic Driving

delete2024-05-28
delete1
delete
OA
AI
S
Songsong Rong
R
Ruifeng Meng *
J
Junhong Guo
P
Pengfei Cui
乔智 cover
乔智 (Qiao Zhi)
DOI:10.3390/su16114578delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Autonomous vehicles hold the potential to significantly improve traffic efficiency and advance the development of intelligent transportation systems. With the progression of autonomous driving technology, collaborative planning among multiple vehicles in autonomous driving scenarios has emerged as a pivotal challenge in realizing intelligent transportation systems. Serving as the cornerstone of unmanned mission decision-making, collaborative motion planning algorithms have garnered increasing attention in both theoretical exploration and practical application. These methods often follow a similar paradigm: the system initially discerns the driving intentions of each vehicle, subsequently assesses the surrounding environment, engages in path-planning, and formulates specific behavioral decisions. The paper discusses trajectory prediction, game theory, following behavior, and lane merging issues within the paradigm mentioned above. After briefly introducing the background of multi-vehicle autonomous driving, it provides a detailed description of the technological prerequisites for implementing these techniques. It reviews the main algorithms in motion planning, their functionalities, and applications in road environments, as well as current and future challenges and unresolved issues.
Keywords:
autonomous driving
multi-vehicle coordination
motion planning
development prospect

Journal

Sustainability cover
Sustainability
IF:
3.3
Papers:
10.7W
Citations:
28.4W

Organization

I
Inner Mongolia University of Technology
Scholars:
4.5K
Papers: 2.6K
Citations: 2.3K
Cited Papers

Cited Papers

Toward a Self-Adaptive Workflow Management System Through Learning and Prediction Models
err2016-12-09
err0
PREAI
errMohamed Yassine Samiri; Mehdi Najib; Abdelaziz El Fazziki; Jaouad Boukachour
errShare
errSave
Green Behavior and Financial Performance: Impact on the Malaysian Fashion Industry
err2020-09-23
err0
errOAAI
errQaisar Ali; Asma Salman; Shazia Parveen; Zaki Zaini
errShare
errSave
New insights into comprehensive analysis of magnesium transporter (MGT) gene family in rice (Oryza sativa L.)
err2023-08-28
err0
PREAI
errSeyede Fateme Mohamadi; Nadali Babaeian Jelodar; Nadali Bagheri; Ghorbanali Nematzadeh; Seyyed Hamidreza Hashemipetroudi
errShare
errSave
Motion trajectory prediction based on a CNN-LSTM sequential model
err2020-10-15
err126
PREAI
errXie, Guo; Shangguan, Anqi; Fei, Rong; Ji, Wenjiang; Ma, Weigang; Hei, Xinhong
errShare
errSave
Understanding the Reaction Crystallization Process of Glycidyl Trimethyl Ammonium Chloride
err2021-04-20
err0
errOAAI
errShuai Yu; Hui Chen; Xujie Gao; Weichun Feng; Wenguo Xing; Shichao Du; Yan Wang; Fumin Xue; Yan Cheng
errShare
errSave
Multispectral and Thermal Sensors Onboard UAVs for Heterogeneity in Merlot Vineyard Detection: Contribution to Zoning Maps
err2023-08-14
err0
errOAAI
errLuz K. Atencia Payares; Ana M. Tarquis; Roberto Hermoso Peralo; Jesús Cano; Joaquín Cámara; Juan Nowack; María Gómez del Campo
errShare
errSave
researcher View more