A Particle Filter Localization Method Using 2D Laser Sensor Measurements and Road Features for Autonomous Vehicle

Joint Authors

Ahn, KyungJae
Kang, Yeonsik

Source

Journal of Advanced Transportation

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-02-14

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Civil Engineering

Abstract EN

This paper presents a method of particle filter localization for autonomous vehicles, based on two-dimensional (2D) laser sensor measurements and road features.

To navigate an urban environment, an autonomous vehicle should be able to estimate its location with a reasonable accuracy.

By detecting road features such as curbs and road markings, a grid-based feature map is constructed using 2D laser range finder measurements.

Then, a particle filter is employed to accurately estimate the position of the autonomous vehicle.

Finally, the performance of the proposed method is verified and compared to accurate Differential Global Positioning Systems (DGPS) data through real road driving experiments.

American Psychological Association (APA)

Ahn, KyungJae& Kang, Yeonsik. 2019. A Particle Filter Localization Method Using 2D Laser Sensor Measurements and Road Features for Autonomous Vehicle. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1169782

Modern Language Association (MLA)

Ahn, KyungJae& Kang, Yeonsik. A Particle Filter Localization Method Using 2D Laser Sensor Measurements and Road Features for Autonomous Vehicle. Journal of Advanced Transportation No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1169782

American Medical Association (AMA)

Ahn, KyungJae& Kang, Yeonsik. A Particle Filter Localization Method Using 2D Laser Sensor Measurements and Road Features for Autonomous Vehicle. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1169782

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1169782