Occupancy Grid Map Formation and Fusion in Cooperative Autonomous Vehicle Sensing (Invited Paper)

Yuru Li; Dongliang Duan; Chen Chen; Xiang Cheng; Liuqing Yang

doi:10.1109/ICCS.2018.8689254

Occupancy Grid Map Formation and Fusion in Cooperative Autonomous Vehicle Sensing (Invited Paper)

Yuru Li, Dongliang Duan, Chen Chen, Xiang Cheng, Liuqing Yang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

13 Scopus citations

Abstract

In autonomous driving, sensing is the most fundamental task providing the necessary information for intelligent vehicles. Compared with single-vehicle sensing, cooperative sensing can greatly reduce the cost, increase the accuracy and overcome the vision range limit. In this paper, a cooperative sensing framework is proposed based upon the occupancy grid map. For map formation, we investigate four occupancy probability distribution algorithms to transform the sensor data into a probability model; for map fusion, we design a probability fusion method to combine multi-vehicle maps. Simulations show that the proposed probability distribution algorithms can capture the environment information with different focuses and the map fusion process can expand the vehicles' sensing range and improve the accuracy.

Original language	English (US)
Title of host publication	2018 IEEE International Conference on Communication Systems, ICCS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	204-209
Number of pages	6
ISBN (Electronic)	9781538678640
DOIs	https://doi.org/10.1109/ICCS.2018.8689254
State	Published - Jul 2 2018
Externally published	Yes
Event	16th IEEE International Conference on Communication Systems, ICCS 2018 - Chengdu, China Duration: Dec 19 2018 → Dec 21 2018

Publication series

Name	2018 IEEE International Conference on Communication Systems, ICCS 2018

Conference

Conference	16th IEEE International Conference on Communication Systems, ICCS 2018
Country/Territory	China
City	Chengdu
Period	12/19/18 → 12/21/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Autonomous vehicle
cooperative sensing
map fusion
occupancy probability distribution

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10.1109/ICCS.2018.8689254

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Cite this

Li, Y., Duan, D., Chen, C., Cheng, X., & Yang, L. (2018). Occupancy Grid Map Formation and Fusion in Cooperative Autonomous Vehicle Sensing (Invited Paper). In 2018 IEEE International Conference on Communication Systems, ICCS 2018 (pp. 204-209). Article 8689254 (2018 IEEE International Conference on Communication Systems, ICCS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCS.2018.8689254

Occupancy Grid Map Formation and Fusion in Cooperative Autonomous Vehicle Sensing (Invited Paper). / Li, Yuru; Duan, Dongliang; Chen, Chen et al.
2018 IEEE International Conference on Communication Systems, ICCS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 204-209 8689254 (2018 IEEE International Conference on Communication Systems, ICCS 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, Y, Duan, D, Chen, C, Cheng, X & Yang, L 2018, Occupancy Grid Map Formation and Fusion in Cooperative Autonomous Vehicle Sensing (Invited Paper). in 2018 IEEE International Conference on Communication Systems, ICCS 2018., 8689254, 2018 IEEE International Conference on Communication Systems, ICCS 2018, Institute of Electrical and Electronics Engineers Inc., pp. 204-209, 16th IEEE International Conference on Communication Systems, ICCS 2018, Chengdu, China, 12/19/18. https://doi.org/10.1109/ICCS.2018.8689254

Li Y, Duan D, Chen C, Cheng X, Yang L. Occupancy Grid Map Formation and Fusion in Cooperative Autonomous Vehicle Sensing (Invited Paper). In 2018 IEEE International Conference on Communication Systems, ICCS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 204-209. 8689254. (2018 IEEE International Conference on Communication Systems, ICCS 2018). doi: 10.1109/ICCS.2018.8689254

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AB - In autonomous driving, sensing is the most fundamental task providing the necessary information for intelligent vehicles. Compared with single-vehicle sensing, cooperative sensing can greatly reduce the cost, increase the accuracy and overcome the vision range limit. In this paper, a cooperative sensing framework is proposed based upon the occupancy grid map. For map formation, we investigate four occupancy probability distribution algorithms to transform the sensor data into a probability model; for map fusion, we design a probability fusion method to combine multi-vehicle maps. Simulations show that the proposed probability distribution algorithms can capture the environment information with different focuses and the map fusion process can expand the vehicles' sensing range and improve the accuracy.

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Occupancy Grid Map Formation and Fusion in Cooperative Autonomous Vehicle Sensing (Invited Paper)

Abstract

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Bibliographical note

Keywords

Access

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