• 자동차안전학회지
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• 제11권4호
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• pp.28-38
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• 2019

In the world, traffic accidents and environmental pollution caused by the increase of vehicles are becoming a serious social problem. According to the 2016 data published by the Korea Highway Traffic Authority, Korea owns 49.9 vehicles per 100 people. This is the 28th largest number among the 35 OECD member countries. In addition, the number of deaths from traffic accidents in Korea totaled 4,292, of which 1,714 were caused by traffic accidents involving vehicles and pedestrians. To reduce these human casualties, the automotive industry is constantly working on the development and commercialization of Adaptive Driver Assist System (ADAS). ADAS is the system providing convenience and safeness for drivers. In general, ADAS consists of Autonomous Emergency Braking (AEB), Highway Driving Assist (HDA), Adaptive Cruise Control (ACC), Lane Keeping Assist System (LKAS). Among them, the AEB detects the possibility of collision by the vehicle itself and plays a role of avoiding the collision or reducing the damage through active braking. For such AEB, Euro NCAP has been developing test-evaluation methods for the vulnerable since 2017. Therefore, In this paper analyzes the scenario of Euro NCAP VRU Test Protocol v3.0.1, which will be established in 2020, and proposes test conditions according to the Korean road traffic law. In addition, the reliability of the proposed scenario and test conditions was verified by comparing and analyzing the proposed theoretical evaluation formulas and actual test results.

• 한국자동차공학회논문집
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• 제24권2호
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• pp.127-136
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• 2016

The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.