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이명구(Myoung Gu Lee),정현빈(Hyeon Bin Jeong),양지현(Ji Hyun Yang),이상헌(Sang Hun Lee) (사)한국CDE학회 2014 한국 CAD/CAM 학회 학술발표회 논문집 Vol.2014 No.8
Recently, to reduce driver"s workload, multimodal user interfaces including voice and gesture recognition functions have been introduced to intelligent vehicles. However, the non-contact input methods are vulnerable to environmental conditions such as noise and light. To enhance their accuracy, in this paper, we proposed a complementary intelligent method to infer driver’s intention for the operation of in-vehicle equipment. To this end, first, on controlling in-vehicle equipment, the driver’s voice, video and physiological signals and the vehicle state information were collected through various sensors and ports of a driving simulator. Next, a set of selected machine learning algorithms including decision tree, Bayesian network, support vector machine, and multilayer perceptron approaches were trained using the collected data. Finally, the most efficient algorithm were selected by comparing their accuracy and performance.
지능형 칵핏 모듈의 통합 인간-차량 인터랙션 매니저 알고리즘 개발을 위한 기초 연구
류동운(Dong Woon Ryu),최선우(Seon Woo Choi),김형준(Hyung Jun Kim),정현빈(Hyeon Bin Jeong),이상헌(Sang Hun Lee),양지현(Ji Hyun Yang) (사)한국CDE학회 2014 한국 CAD/CAM 학회 학술발표회 논문집 Vol.2014 No.2
This paper presents basic research results for development of the integrated HVI Manager algorithm needed for intelligent cockpit module. With the development of the current sensor and vehicle technologies, we expect to reduce the rate of traffic accidents, however increased complexity of vehicles could easily become the contributing factor of traffic accidents. Driver monitoring systems, such as driver state, intention, tendency, can help to minimize the above problem. This paper presents literature survey results for HVI Manager framework.