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Title	A Neural-Network-Based Real-End Collision Prediction Mechanism For Smart Cities
ID_Doc	2954
Authors	Wang X.; Qiu T.; Chen C.; Chen N.
Year	2019
Published	Proceedings - 2019 IEEE International Conference on Smart Internet of Things, SmartIoT 2019
DOI	http://dx.doi.org/10.1109/SmartIoT.2019.00091
Abstract	Rear-end collisions is a serious issue in smart cities with Intelligent Transportation System, which is one of the main causes of casualties. With the development of Internet of Vehicle, many researches have been conducted to solve this problem. Parametric based methods are first proposed to send warnings before rear-end collisions occur. Deep learning methods are more suitable for this issue, which have better adaptive capability to different environments. However, the proposed deep learning based methods still have some limitations and perform not well in real scenes. In this paper, a neural-network-based mechanism is proposed to predict rear-end collisions. The experimental results show that the proposed mechanism performs better than existing schemes and can effectively help drivers to avoid dangers. © 2019 IEEE.
Author Keywords	Autonomous Driving; Collision Prediction; Internet of Vehicles; Neural Network; Smart Cities

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