Embodied Intelligent Driving: Key Technologies and Applications

Embodied intelligence emphasizes direct interaction between machines and the physical world, enabling intelligent agents to exhibit intelligent behaviors and autonomous evolution through the interplay of the brain, body, and environment. This paper discusses key technologies involved in embodied intelligent driving, based on the core requirements of embodied intelligence and autonomous driving, focusing on two core aspects: embodied perception and execution, and embodied learning and evolution. The development status and existing issues of these technologies are analyzed. Additionally, the paper elaborates on datasets and practical system applications related to embodied intelligent driving. Subsequently, it presents reflections and prospects for this field, considering the significant role and application potential of parallel robot, aiming to promote the application of embodied intelligent driving in highly dynamic real-world scenes.

Authors

Institutions

Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/dtpi61353.2024.10778821
Citations
2
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.53

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Embodied Intelligent Driving: Key Technologies and Applications

Yadong Wang, Tianyu Shen, Kunfeng Wang, Sihan Chen et al.
2 citations
Traffic Prediction and Management Techniques
0.53
article

Embodied Intelligent Driving: Key Technologies and Applications

Yadong Wang, Tianyu Shen, Kunfeng Wang, Sihan Chen, Zhiwei Li
article en
2 citations

Abstract

Embodied intelligence emphasizes direct interaction between machines and the physical world, enabling intelligent agents to exhibit intelligent behaviors and autonomous evolution through the interplay of the brain, body, and environment. This paper discusses key technologies involved in embodied intelligent driving, based on the core requirements of embodied intelligence and autonomous driving, focusing on two core aspects: embodied perception and execution, and embodied learning and evolution. The development status and existing issues of these technologies are analyzed. Additionally, the paper elaborates on datasets and practical system applications related to embodied intelligent driving. Subsequently, it presents reflections and prospects for this field, considering the significant role and application potential of parallel robot, aiming to promote the application of embodied intelligent driving in highly dynamic real-world scenes.

Beijing University of Chemical Technology (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 33%
Traffic Prediction and Management Techniques
0.53
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.