|Abstract:||For automotive safety applications, connected cars exchange navigation data between vehicles and apply this information for collision avoidance. One of the key challenges is to enable the required navigation accuracy for any driving environments at any time. GNSS signal availability and navigation data quality decrease rapidly once operational environments shift from open sky to degraded signal scenarios such as urban and tree-covered roads. Multi-sensor augmentations of GNSS can maintain the required localization capabilities. However, current multi-sensor implementations are rather ad hoc and sensors-specific This paper presents a truly plug-and-play navigation solution that automatically reconfigures itself as sensors are connected to (disconnected from) the system, without the need to redesign the system architecture or its specific components. For experimental demonstrations, test data were collected in urban canyons of downtown San Francisco, CA in January 2016. The paper provides experimental results for various sensor configurations including carrier phase GNSS, consumer-grade IMU, video camera, and the use of vehicle motion constraints. Consistent positioning in urban canyons is demonstrated in support of automotive safety applications.|
Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016)
September 12 - 16, 2016
Oregon Convention Center
|Pages:||725 - 732|
|Cite this article:||
Soloviev, Andrey, Veth, Michael, Yang, Chun, "Plug and Play Sensor Fusion for Lane-Level Positioning of Connected Cars in GNSS-Challenged Environments," Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016), Portland, Oregon, September 2016, pp. 725-732.
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