A New Efficient Obstacle Avoidance Control Method for Cars Based on Big Data and Just-in-Time Modeling

Autor:	Tatsuya Kai
Rok vydání:	2018
Předmět:	Computer science business.industry Real systems Property (programming) Computation Obstacle Big data Control (management) Real-time computing Obstacle avoidance business Control methods
Zdroj:	Journal of Computer and Communications. :12-22
ISSN:	2327-5227 2327-5219
DOI:	10.4236/jcc.2018.611002
Popis:	This paper provides a new obstacle avoidance control method for cars based on big data and just-in-time modeling. Just-in-time modeling is a new kind of data-driven control technique in the age of big data and is used in various real systems. The main property of the proposed method is that a gain and a control time which are parameters in the control input to avoid an encountered obstacle are computed from a database which includes a lot of driving data in various situations. Especially, the important advantage of the method is small computation time, and hence it realizes real-time obstacle avoidance control for cars. From some numerical simulations, it is showed that the new control method can make the car avoid various obstacles efficiently in comparison with the previous method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c08d5ef3ae3b99d3db9f17d7c0d6492e https://doi.org/10.4236/jcc.2018.611002 Zobrazit plný text záznamu