Evidence map›Paper›PMID 37836981›Full record

ArticleSensors (Basel, Switzerland)2023

An Obstacle Avoidance Path Planning and Evaluation Method for Intelligent Vehicles Based on the B-Spline Algorithm.

Yulong Zhang, Pengwei Wang, Kaichen Cui, Hengheng Zhou, Jinshan Yang, Xiangcun Kong

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article 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
–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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Yulong ZhangSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
Pengwei WangSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.ORCID 0000-0001-6827-0988
Kaichen CuiSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
Hengheng ZhouSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
Jinshan YangSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.
Xiangcun KongSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255022, China.

Funding

National Natural Science Foundation Project of China 52102465
6 · The paper itself

Abstract

To meet the real-time path planning requirements of intelligent vehicles in dynamic traffic scenarios, a path planning and evaluation method is proposed in this paper. Firstly, based on the B-spline algorithm and four-stage lane-changing theory, an obstacle avoidance path planning algorithm framework is constructed. Then, to obtain the optimal real-time path, a comprehensive real-time path evaluation mechanism that includes path safety, smoothness, and comfort is established. Finally, to verify the proposed approach, co-simulation and real vehicle testing are conducted. In the dynamic obstacle avoidance scenario simulation, the lateral acceleration, yaw angle, yaw rate, and roll angle fluctuation ranges of the ego-vehicle are ±2.39 m/s

Indexed as

B-splinecomprehensive evaluationfour-segment lane-changing modelintelligent vehiclepath planning

Identifiers

PMID37836981
PMCPMC10574840

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.