Vehicle localization and mobility tracking are important tasks in autonomous driving. Traditional methods either have insufficient accuracy or rely on additional facilities to reach the desired accuracy for autonomous driving. In this paper, a multi-sensor multi-vehicle localization and mobility tracking framework is developed for autonomous vehicles equipped with GPS, inertial measurement unit (IMU), and an integrated sensing system. Our algorithm fuse the information from local onboard sensors as well as the observations of other vehicles or existing intelligent transportation system infrastructure such as road side units (RSU) to improve the precision and stability of localization and mobility tracking. Specifically, this framework incorporates the dynamic model of vehicles to achieve better localization and tracking performance. The communication delays during the information sharing process are explicitly taken into account in our algorithm development. Simulations manifest that not only the accuracy of localization and mobility tracking could be greatly enhanced in general, but also the robustness can be guaranteed under circumstances where traditional localization and tracking devices fail.
Bibliographical noteFunding Information:
This work was supported in part by the Key Area Research and Development Program of Guangdong Province Project 2019B010153003, in part by the Ministry National Key Research and Development Project under Grant 2017YFE0121400, and in part by the National Science Foundation under Grants CNS-1932413 and CNS-1932139.
Manuscript received April 14, 2020; revised July 6, 2020; accepted October 4, 2020. Date of publication October 19, 2020; date of current version January 22, 2021. This work was supported in part by the Key Area Research and Development Program of Guangdong Province Project 2019B010153003, in part by the Ministry National Key Research and Development Project under Grant 2017YFE0121400, and in part by the National Science Foundation under Grants CNS-1932413 and CNS-1932139. This article was presented at the 2018 Global Conference on Signal and Information Processing, Anaheim, CA, November 26-29, 2018 . The review of this article was coordinated by Prof. Shibo He.
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- Multi-sensor multi-vehicle (MSMV) localization and mobility tracking
- autonomous driving
- cooperative sensing
- intelligent transportation systems (ITS)