Evaluation of Hybrid Positioning Scenarios for Autonomous Vehicle Applications

José A. del Peral-Rosado, Roger Estatuet-Castillo, José A. López-Salcedo, Gonzalo Seco-Granados, Zdenek Chaloupka, Lionel Ries, José A. García-Molina

Peer Reviewed

Abstract:	Autonomous vehicle applications, such as assisted driving, collision avoidance or platooning, demand precise, reliable and secure localization in harsh environments such as tunnels and urban areas. In order to face these positioning challenges, multiple navigation technologies have to be fused. These technologies are typically based on Global Navigation Satellite Systems (GNSS), radar, camera, sensors and signals of opportunity. Indeed, the exploitation of cellular communications for positioning is of special interest due to the advanced physical features of fourth generation (4G) and fifth generation (5G) networks. The objective of this work is to assess the performance limits of hybrid GNSS and LTE solutions, based on assisted or opportunistic approaches. For this purpose, a software tool is presented to evaluate different hybrid scenarios, by using field GNSS and simulate LTE observables. The assisted LTE approach is shown to outperform the opportunistic approach, and the hybrid solutions achieve a position accuracy around 3 meters and a position fix of 100% in urban and road scenarios. Future work is still necessary to fulfil the location requirements of autonomous vehicle applications.
Published in:	Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017) September 25 - 29, 2017 Oregon Convention Center Portland, Oregon
Pages:	2541 - 2553
Cite this article:	del Peral-Rosado, José A., Estatuet-Castillo, Roger, López-Salcedo, José A., Seco-Granados, Gonzalo, Chaloupka, Zdenek, Ries, Lionel, García-Molina, José A., "Evaluation of Hybrid Positioning Scenarios for Autonomous Vehicle Applications," Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 2541-2553. https://doi.org/10.33012/2017.15220
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