Abstract
In this paper, in order to keep safe and secure driving, a new generation wide area road surface state information platform based on crowd sensing and V2X Technologies is introduced. In crowd sensing, various environmental sensors including accelerator, gyro sensor, infrared temperature sensor, quasi electrical static sensor, camera and GPS are integrated to precisely detect the various road surface states and determine the dangerous locations on GIS. Those road information are transmitted the neighbor vehicles and road side server in realtime using V2X communication network. In V2X communication on the actual road, both the length of communication distance and the total size of data transmission must be maximized at the same time when vehicle are running on the road. The conventional single wireless communication such as Wi-Fi, IEEE802.11p, LPWA, cannot satisfy those conditions at the same time. In order to resolve such problems, N-wavelength cognitive wireless communication method is newly introduced in our research. Multiple next generation wireless LANS including IEEE802.11ac/ad/ah/in addition to the current popular LANs with different wavelengths are integrated to organize a cognitive wireless communication. The best link of the cognitive wireless is determined by SDN. Driver can receive the road surface status information from the vehicle in opposite direction or road side server and eventually pay attentions to his/her driving before encountering the danger location. This technology can also apply for automatic driving car.
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Acknowledgement
The research was supported by Strategic Information and Communications R&D Promotion Program Grant Number 181502003 by Ministry of Affairs and Communication.
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Shibata, Y., Sato, G., Uchida, N. (2020). Road State Information Platform Based on Multi-sensors and Bigdata Analysis. In: Barolli, L., Hellinckx, P., Enokido, T. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2019. Lecture Notes in Networks and Systems, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-030-33506-9_40
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DOI: https://doi.org/10.1007/978-3-030-33506-9_40
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