Evidence map›Paper›PMID 39204869›Full record

ReviewSensors (Basel, Switzerland)2024

Intelligent Cockpits for Connected Vehicles: Taxonomy, Architecture, Interaction Technologies, and Future Directions.

Fei Gao, Xiaojun Ge, Jinyu Li, Yuze Fan, Yun Li, Rui Zhao

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Fei GaoCollege of Automotive Engineering, Jilin University, Changchun 130025, China.ORCID 0000-0003-4195-5033
Xiaojun GeCollege of Automotive Engineering, Jilin University, Changchun 130025, China.ORCID 0009-0005-5508-8809
Jinyu LiCollege of Automotive Engineering, Jilin University, Changchun 130025, China.ORCID 0009-0001-8463-7732
Yuze FanCollege of Automotive Engineering, Jilin University, Changchun 130025, China.ORCID 0009-0003-8309-7396
Yun LiGraduate School of Information and Science Technology, The University of Tokyo, Tokyo 113-8654, Japan.ORCID 0009-0002-7824-7751
Rui ZhaoCollege of Automotive Engineering, Jilin University, Changchun 130025, China.ORCID 0000-0003-1597-1961

Funding

National Science Foundation of China 52202494National Science Foundation of China 52202495
6 · The paper itself

Abstract

Highly integrated information sharing among people, vehicles, roads, and cloud systems, along with the rapid development of autonomous driving technologies, has spurred the evolution of automobiles from simple "transportation tools" to interconnected "intelligent systems". The intelligent cockpit is a comprehensive application space for various new technologies in intelligent vehicles, encompassing the domains of driving control, riding comfort, and infotainment. It provides drivers and passengers with safety, comfort, and pleasant driving experiences, serving as the gateway for traditional automobile manufacturing to upgrade towards an intelligent automotive industry ecosystem. This is the optimal convergence point for the intelligence, connectivity, electrification, and sharing of automobiles. Currently, the form, functions, and interaction methods of the intelligent cockpit are gradually changing, transitioning from the traditional "human adapts to the vehicle" viewpoint to the "vehicle adapts to human", and evolving towards a future of natural interactive services where "humans and vehicles mutually adapt". This article reviews the definitions, intelligence levels, functional domains, and technical frameworks of intelligent automotive cockpits. Additionally, combining the core mechanisms of human-machine interactions in intelligent cockpits, this article proposes an intelligent-cockpit human-machine interaction process and summarizes the current state of key technologies in intelligent-cockpit human-machine interactions. Lastly, this article analyzes the current challenges faced in the field of intelligent cockpits and forecasts future trends in intelligent cockpit technologies.

Indexed as

driving experiencehuman–vehicle interactionsintelligent cockpitnatural elastic interaction

Identifiers

PMID39204869
PMCPMC11358958

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.