Autonomous Train Speed-Limit Estimation Algorithm by Recognition Abnormal Situation Based on of Infrastructure Sensor Data 


Vol. 43,  No. 4, pp. 708-714, Apr.  2018
10.7840/kics.2018.43.4.708


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  Abstract

In this paper, we propose a fuzzy inference based autonomous train speed limit algorithm to estimate the speed limit of autonomous trains. In this paper, we propose a fuzzy inference algorithm based on the fuzzy inference algorithm to partially define the rules for the external environment (weather conditions) that can affect the vehicle speed. Through simulations, it was confirmed that the limit speed of autonomous train was calculated in case of actual abnormal weather, and safety was verified by comparing with current regulations. The proposed algorithm is expected to be able to replace the current speed limiter structure which depends on driver and control. It can also increase safety and operational efficiency by extending the model.

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  Cite this article

[IEEE Style]

J. Kim, T. An, J. Kim, H. Yoon, "Autonomous Train Speed-Limit Estimation Algorithm by Recognition Abnormal Situation Based on of Infrastructure Sensor Data," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 4, pp. 708-714, 2018. DOI: 10.7840/kics.2018.43.4.708.

[ACM Style]

Jin-pyung Kim, Tae-ki An, Jin-ho Kim, and Hee-taek Yoon. 2018. Autonomous Train Speed-Limit Estimation Algorithm by Recognition Abnormal Situation Based on of Infrastructure Sensor Data. The Journal of Korean Institute of Communications and Information Sciences, 43, 4, (2018), 708-714. DOI: 10.7840/kics.2018.43.4.708.

[KICS Style]

Jin-pyung Kim, Tae-ki An, Jin-ho Kim, Hee-taek Yoon, "Autonomous Train Speed-Limit Estimation Algorithm by Recognition Abnormal Situation Based on of Infrastructure Sensor Data," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 4, pp. 708-714, 4. 2018. (https://doi.org/10.7840/kics.2018.43.4.708)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880