Best Papers
 Design and Implementation of Vehicle Operating Status Recognition On-Device AI for Driver Behavior Analysis 


Vol. 48,  No. 7, pp. 842-851, Jul.  2023
10.7840/kics.2023.48.7.842


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  Abstract

With the recent development of technologies for vehicle sensors and artificial intelligence, technologies for driver convenience such as autonomous driving are actively developed around the world. However, due to the verification of the safety of the system, the commercialization rate is lower than the development situation. Therefore, in this paper, a study was conducted to classify the vehicle operating status so that it can be used to analyze driver behavior and recognize dangerous driving by implementing on-device AI available in the vehicle driven by the driver. Deep learning model was designed to infer the vehicle's operating status using the extracted vehicle interior information. In order to mount a deep learning model on a device, the structure of the deep learning model was changed and lightened through quantization. The performance is evaluated by performing real-time vehicle operation status inference while driving the finally implemented on-device AI in the real vehicle. The vehicle operating status recognition accuracy showed 91.66% performance and the inference time was 19.72 ms

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[IEEE Style]

T. Kim, Y. Cho, Y. Baek, "Design and Implementation of Vehicle Operating Status Recognition On-Device AI for Driver Behavior Analysis," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 7, pp. 842-851, 2023. DOI: 10.7840/kics.2023.48.7.842.

[ACM Style]

Taegu Kim, Yonghun Cho, and Yunju Baek. 2023. Design and Implementation of Vehicle Operating Status Recognition On-Device AI for Driver Behavior Analysis. The Journal of Korean Institute of Communications and Information Sciences, 48, 7, (2023), 842-851. DOI: 10.7840/kics.2023.48.7.842.

[KICS Style]

Taegu Kim, Yonghun Cho, Yunju Baek, "Design and Implementation of Vehicle Operating Status Recognition On-Device AI for Driver Behavior Analysis," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 7, pp. 842-851, 7. 2023. (https://doi.org/10.7840/kics.2023.48.7.842)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880