Automated Lane Changing Through Learning-Based Control: An Experimental Study

Won Yong Ha; Sayan Chakraborty; Yujie Yu; Samin Ghasemi; Zhong Ping Jiang

doi:10.1109/ITSC57777.2023.10422053

Automated Lane Changing Through Learning-Based Control: An Experimental Study

Won Yong Ha, Sayan Chakraborty, Yujie Yu, Samin Ghasemi, Zhong Ping Jiang

Electrical and Computer Engineering

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

Abstract

This paper presents a learning-based methodology for developing an optimal lane-changing control policy for a Remote Controlled (RC) car using real-time sensor data. The RC car is equipped with sensors including GPS, IMU devices, and a camera integrated in an Nvidia Jetson AGX Xavier board. By a novel Adaptive Dynamic Programming (ADP) algorithm, our RC car is capable of learning the optimal lane-changing strategies based on the real-time processed measurement from the sensors. The experimental outcomes show that our learning-based control algorithm can be effectively implemented, adapt to parameter changes, and complete the lane changing tasks in a short learning time with satisfactory performance.

Original language	English (US)
Title of host publication	2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4215-4220
Number of pages	6
ISBN (Electronic)	9798350399462
DOIs	https://doi.org/10.1109/ITSC57777.2023.10422053
State	Published - 2023
Event	26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 - Bilbao, Spain Duration: Sep 24 2023 → Sep 28 2023

Publication series

Name	IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
ISSN (Print)	2153-0009
ISSN (Electronic)	2153-0017

Conference

Conference	26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023
Country/Territory	Spain
City	Bilbao
Period	9/24/23 → 9/28/23

ASJC Scopus subject areas

Automotive Engineering
Mechanical Engineering
Computer Science Applications

Access to Document

10.1109/ITSC57777.2023.10422053

Cite this

Ha, W. Y., Chakraborty, S., Yu, Y., Ghasemi, S., & Jiang, Z. P. (2023). Automated Lane Changing Through Learning-Based Control: An Experimental Study. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023 (pp. 4215-4220). (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC57777.2023.10422053

Automated Lane Changing Through Learning-Based Control: An Experimental Study. / Ha, Won Yong; Chakraborty, Sayan; Yu, Yujie et al.
2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 4215-4220 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC).

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

Ha, WY, Chakraborty, S, Yu, Y, Ghasemi, S & Jiang, ZP 2023, Automated Lane Changing Through Learning-Based Control: An Experimental Study. in 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, Institute of Electrical and Electronics Engineers Inc., pp. 4215-4220, 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain, 9/24/23. https://doi.org/10.1109/ITSC57777.2023.10422053

Ha WY, Chakraborty S, Yu Y, Ghasemi S, Jiang ZP. Automated Lane Changing Through Learning-Based Control: An Experimental Study. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 4215-4220. (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC). doi: 10.1109/ITSC57777.2023.10422053

Ha, Won Yong ; Chakraborty, Sayan ; Yu, Yujie et al. / Automated Lane Changing Through Learning-Based Control : An Experimental Study. 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 4215-4220 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC).

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abstract = "This paper presents a learning-based methodology for developing an optimal lane-changing control policy for a Remote Controlled (RC) car using real-time sensor data. The RC car is equipped with sensors including GPS, IMU devices, and a camera integrated in an Nvidia Jetson AGX Xavier board. By a novel Adaptive Dynamic Programming (ADP) algorithm, our RC car is capable of learning the optimal lane-changing strategies based on the real-time processed measurement from the sensors. The experimental outcomes show that our learning-based control algorithm can be effectively implemented, adapt to parameter changes, and complete the lane changing tasks in a short learning time with satisfactory performance.",

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AB - This paper presents a learning-based methodology for developing an optimal lane-changing control policy for a Remote Controlled (RC) car using real-time sensor data. The RC car is equipped with sensors including GPS, IMU devices, and a camera integrated in an Nvidia Jetson AGX Xavier board. By a novel Adaptive Dynamic Programming (ADP) algorithm, our RC car is capable of learning the optimal lane-changing strategies based on the real-time processed measurement from the sensors. The experimental outcomes show that our learning-based control algorithm can be effectively implemented, adapt to parameter changes, and complete the lane changing tasks in a short learning time with satisfactory performance.

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Automated Lane Changing Through Learning-Based Control: An Experimental Study

Abstract

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