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Vehicular Perception Based on Inertial Sensing: A Structured Mapping of Approaches and Methods

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Abstract

In this paper, we present a structured literature mapping of the state-of-the-art of vehicular perception methods and approaches using inertial sensors. An in-depth investigation and classification were performed employing the results of a systematic literature review. The analysis focused on identifying methods that capture signals provided by inertial sensors such as accelerometers and gyroscopes to recognize transient or persistent events associated with the vehicle’s movement. We classified these events into vehicular exteroception, associated with potholes, cracks, speed bumps, pavement type, conservation state; and vehicular proprioception, associated with lane change, braking, skidding, aquaplaning, turning right or left. Through the comprehensive study of publications in a 7-year time window, in addition to the methods, we have also identified their dependency factors, hardware platforms and applications.

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  1. Graduate Program in Computer Science (PPGCC), Image Processing and Computer Graphics Lab (LAPIX), Department of Informatics and Statistics (INE), Brazilian Institute for Digital Convergence (INCoD), Federal University of Santa Catarina (UFSC), Florianópolis, Santa Catarina, Brazil

    Jeferson Menegazzo & Aldo von Wangenheim

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Appendix 1: Summary Data

Appendix 1: Summary Data

Table 8 Data collection information for exteroception
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Table 9 Preprocessing for exteroception
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Table 10 Processing for exteroception
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Table 11 Data collection information for proprioception
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Table 12 Preprocessing for proprioception
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Table 13 Processing for proprioception
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Menegazzo, J., von Wangenheim, A. Vehicular Perception Based on Inertial Sensing: A Structured Mapping of Approaches and Methods. SN COMPUT. SCI. 1, 255 (2020). https://doi.org/10.1007/s42979-020-00275-z

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