• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.34-38
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• 2020

In this paper, we implement a Dashcam system capable of shooting 360 degrees using a Raspberry Pi, shock sensors, distance sensors, and rotating camera with a servo motor. If there is an object approaching the vehicle by the distance sensor, the camera rotates to take a video. In the event of an external shock, videos and images are stored in the server to analyze the cause of the vehicle's accident and prevent the user from forging or tampering with videos or images. We also implement functions that transmit the message with the location and the intensity of the impact when the accident occurs and send the vehicle information to an insurance authority with by linking the system with a smart device. It is advantage that the authority analyzes the transmitted message and provides the accident handling information giving the user's safety and convenience.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.364-368
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• 2018

In this paper, we use Faster R-CNN that is one of object detection algorithm and OpenCV that purposes computer vision, to implement the system that can detect danger when a vehicle attempts to change lanes into its own lane in videos of highway, national road, general road and etc. Also, the performance of implemented system is evaluated to prove that the performance is not bad.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.5
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• pp.147-167
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• 2024

Since the traffic conflict technique is typically based on analyzing spatiotemporal movement trajectories between vehicles, it has been expected to use data collected through video footage. Recently, with advances in mobile image-related technologies, research in traffic safety using the traffic conflict technique has become more challenging. This study aims to review the use of image-based traffic conflict studies and surrogate safety measures (SSM) by type of image data and to suggest a direction for constructing mobile image data for measuring traffic conflict. This study reviews SSM used in image-based traffic conflict assessment over the past 50 years (1972-2022). A total of 40 studies were reviewed to identify the types of image data, collection equipment, and SSMs. Most studies have used fixed devices, while there has been no research on the exclusive use of mobile image data, identifying research gaps with previous studies on the use of mobile image data. The results are expected to be used as basic information in traffic safety using mobile image data.