Evidence map›Paper›PMID 37447989›Full record

ReviewSensors (Basel, Switzerland)2023

A Review of the Motion Planning and Control Methods for Automated Vehicles.

Xiaohua Song, Huihui Gao, Tian Ding, Yunfeng Gu, Jing Liu, Kun Tian

Open access · goldAbstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.8field-weighted citation impact, top 8% of its field
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

2 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. 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 at 2 institutions in 1 country.

Xiaohua SongSchool of Electronic Information Engineering, Xi'an Technological University, Xi'an 710021, China.
Huihui GaoSchool of Electronic Information Engineering, Xi'an Technological University, Xi'an 710021, China.
Tian DingSchool of Electronic Information Engineering, Xi'an Technological University, Xi'an 710021, China.
Yunfeng GuSchool of Electronic Information Engineering, Xi'an Technological University, Xi'an 710021, China.
Jing LiuSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.ORCID 0000-0003-2323-3475
Kun TianSchool of Electronic Information Engineering, Xi'an Technological University, Xi'an 710021, China.
Xi'an Technological University · CNNorthwestern Polytechnical University · CN

Funding

Shaanxi Province Key R&D Program Project 2022GY-306
6 · The paper itself

Abstract

The motion planning and control method of automated vehicles, as the key technology of automated vehicles, directly affects the safety, comfort, and other technical indicators of vehicles. The planning module is responsible for generating a vehicle driving path. The control module is responsible for driving the vehicle. In this study, we review the main methods and achievements in motion planning and motion control for automated vehicles. The advantages and disadvantages of various planning and control methods are comparatively analyzed. Finally, some predictions and summaries based on the existing research results and trends are proposed. Through this analysis, it is believed that various types of algorithms will be further integrated in the future to complement each other's strengths and weaknesses. The next area of research will be to establish more accurate vehicle models to describe vehicle motion, improve the generalization-solving ability of algorithms, and enhance the planning and control of integrated 'human-vehicle-road' traffic systems.

Indexed as

automated vehiclesmotion planningtracking control

Identifiers

PMID37447989
PMCPMC10347217
OpenAlexW4383262507

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.