Abstract
Localization is crucial to many vehicular applications and is usually carried out using the Geographical Positioning System (GPS). However, when the GPS signal is unavailable, other solutions can be applied such as camera images and Inertial Navigation System (INS) to know about its movement in order to calculate the actual positions. However, such techniques can be costly in consumption in terms of processing time and energy. Moreover, INS is subject to cumulative errors. In order to improve positioning, information coming from other sensors can be a solution. Thus, this paper proposes a self-adaptive protocol for vehicle localization using smart infrastructure support in GPS free environments. In this context, an autonomous vehicle with unknown localization interacts with the infrastructure sensors to infers its position. Experiments with the adaptive protocol were conducted in a robotic platform. Our obtained results are promising and the maximum error percentage that our localization protocol gets from all our experiments is equal to 0.3%, which indicated an effective value for the precision metric.
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Belbachir, A., Pasin, M. (2019). Self-vehicle Positioning Using Smart Infrastructures. In: Baldoni, M., Dastani, M., Liao, B., Sakurai, Y., Zalila Wenkstern, R. (eds) PRIMA 2019: Principles and Practice of Multi-Agent Systems. PRIMA 2019. Lecture Notes in Computer Science(), vol 11873. Springer, Cham. https://doi.org/10.1007/978-3-030-33792-6_29
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DOI: https://doi.org/10.1007/978-3-030-33792-6_29
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