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Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation

School of Computer Science and Engineering, Pusan National University, Busan 609735, Korea
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Academic Editor: Leonhard M. Reindl
Sensors 2015, 15(8), 20204-20231; https://doi.org/10.3390/s150820204
Received: 16 June 2015 / Revised: 16 June 2015 / Accepted: 10 August 2015 / Published: 18 August 2015
(This article belongs to the Section Sensor Networks)
As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%. View Full-Text
Keywords: computer vision; vehicle recognition; road traffic; vehicular network; real-time traffic estimation computer vision; vehicle recognition; road traffic; vehicular network; real-time traffic estimation
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Son, S.; Baek, Y. Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation. Sensors 2015, 15, 20204-20231.

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