• ETRI Journal
• /
• v.37 no.3
• /
• pp.626-636
• /
• 2015

This paper proposes an adaptive multimodal in-vehicle information system for safe driving. The proposed system filters input information based on both the priority assigned to the information and the given driving situation, to effectively manage input information and intelligently provide information to the driver. It then interacts with the driver using an adaptive multimodal interface by considering both the driving workload and the driver's cognitive reaction to the information it provides. It is shown experimentally that the proposed system can promote driver safety and enhance a driver's understanding of the information it provides by filtering the input information. In addition, the system can reduce a driver's workload by selecting an appropriate modality and corresponding level with which to communicate. An analysis of subjective questionnaires regarding the proposed system reveals that more than 85% of the respondents are satisfied with it. The proposed system is expected to provide prioritized information through an easily understood modality.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.2
• /
• pp.371-377
• /
• 2012

Objective: The aim of this study is to investigate effect of driver's cognitive distraction on driver's physiological state and driving performance, and then to determine parameters appropriate for detecting the cognitive distraction. Background: Driver distraction is a major cause of traffic accidents and poses a serious threat to traffic safety due to ever increasing use of in-vehicle information systems and mobile phones during driving. Cognitive distraction, among four different types of distractions, prevents a driver from processing traffic information correctly and adapting to change in surround vehicle behavior in time. However, the cognitive distraction is more difficult to detect because it normally does not involve significant change in driver behavior. Method: A full-scale driving simulator was used to create virtual driving environment and situations. Participants in the experiment drove the driving simulator in three different conditions: attentive driving with no secondary task, driving and conducting secondary task of adding numbers, and driving and conducting secondary task of conversing with an experimenter. Parameters related with driver's physiological state and driving performance were measured and analyzed for their change. Results: The experiment results show that driver's cognitive distraction, induced by secondary task of addition and conversation during driving, increased driver's cognitive workload, and indeed brought change in driver's physiological state and degraded driving performance. Conclusion: The galvanic skin response, pupil size, steering reversal rate, and driver reaction time are shown to be statistically significant for detecting cognitive distraction. The appropriate combination of these parameters will be used to detect the cognitive distraction and estimate risk of traffic accidents in real-time for a driver distraction warning system.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.5
• /
• pp.657-670
• /
• 2012

Background: Today, numerous telematics technologies, i.e., technologies developed by integrating telecommunications with information processing, are applied in vehicles. One such developmental application of this technology to vehicles is to increase the safety or convenience of drivers by providing them with necessary information such as warnings and information on emergencies and traffic situations. However, under certain conditions, there is a high probability of traffic accidents if the driving workload is high. Nowadays, the navigation system is frequently used in the vehicles, this system provides various information including route to the driver. But, the existing navigation systems are not only considered a driver's reaction but also provide unilaterally to the information regardless of them. Such one-side information service type may miss important information to the driver. In addition, it sometimes interferes safety driving. Objective: To solve this problem, the intelligent navigation system needs to the providing way that it checks the driver's reactions after providing information. Namely, if the driver passes the information received from the navigation, then the intelligent system provides more loudly and more frequently. Method: Therefore, in this study we introduce the intelligent navigation system that it automatically controls modality type and its strength when the driver misses or overlooks the information for their safety and entertainment and we analyze the driver's cognitive responses about the modality type and its strength. Results: To evaluate the effectiveness of the proposed system, we analyzed the reaction time and driving workload for each type of the information, modality and its strength. Also we evaluated the users' subjective satisfaction and understanding based on a questionnaire.

• Journal of Korean Institute of Industrial Engineers
• /
• v.29 no.4
• /
• pp.271-282
• /
• 2003

Automotive occupant packaging has been a part of main ergonomics interests, especially, in terms of driver's posture. Previous research on driver's posture has mainly focused on the initial optimal posture for driving sedans. However, customer preferences on cars are shifting from sedans to RV and automobile manufacturing companies seek to understand temporal changes in drivers' posture according to driving environment. So the main aim of this study was to develop a driver's posture measurement system during driving and investigate casual changes due to duration, car type, traffic flow. Four male drivers participated in the experiments during one week. It was shown that considerable changes in their postures were caused with respect to driving environment, which implies that not only static optimal postures but their dynamic changes should be taken into consideration for proper design and evaluation of interior packaging. The research is expected to help packaging designers understand human drivers so as to improve their comfort.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.5 no.2
• /
• pp.167-176
• /
• 2009

In this paper, a system that detects driver's drowsiness has been implemented based on the automatic extraction and the tracking of pupils. The research also focuses on the compensation of illumination and reduction of background noises that naturally exist in the driving condition. The system, that is based on the principle of Haar-like feature, automatically collects data from areas of driver's face and eyes among the complex background. Then, it makes decision of driver's drowsiness by using recognition of characteristics of pupils area, detection of pupils, and their movements. The implemented system has been evaluated and verified the practical uses for the prevention of driver's drowsiness.

• Journal of Information Processing Systems
• /
• v.13 no.4
• /
• pp.951-969
• /
• 2017

In this paper, we newly propose a traffic information service model that collects traffic information sensed by an individual vehicle in real time by using a smart device, and which enables drivers to share traffic information on all roads in real time using an application installed on a smart device. In particular, when the driver requests traffic information for a specific area, the proposed driver-personalized service model provides him/her with traffic information on the driving directions in advance by predicting the driving directions of the vehicle based on the learning of the driving records of each driver. To do this, we propose a traffic information management model to process and manage in real time a large amount of online-generated traffic information and traffic information requests generated by each vehicle. We also propose a road node-based indexing technique to efficiently store and manage location-based traffic information provided by each vehicle. Finally, we propose a driving learning and prediction model based on the hidden Markov model to predict the driving directions of each driver based on the driver's driving records. We analyze the traffic information processing performance of the proposed model and the accuracy of the driving prediction model using traffic information collected from actual driving vehicles for the entire area of Seoul, as well as driving records and experimental data.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.13 no.4
• /
• pp.81-90
• /
• 2017

This paper presents a smart seat for correction of driver posture while driving. We introduce good postures with seat height, seat angle, head height, back of knees, distances of foot pedals, tilt of seat, etc. There have been some studies on correction of good posture while driving, effects of driving environment on driver's posture, sitting strategies based on seating pressure distribution, estimation of driver's standard postures, and others. However, there are a few studies on guide of good postures while driving for problem of driver's posture using machine leaning. Therefore, we suggest a smart seat for correction of driver's posture based on machine leaning, 1) developed the system to get postures by 10 piezoelectric effect element, 2) collect piezoelectric values from 37 drivers and 28 types of cars, 3) suggest 4 types of good postures while driving, 4) analyze test postures by kNN. As the results, we can guide good postures for bad or problems of postures while driving.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.4
• /
• pp.173-179
• /
• 2017

Autobike is insufficient of car navigation informations and high of accident dangerousness comparing to car. So if a system providing autobike driver's driving information and e-call function is developed using smart helmet consisting of collision perception sensor, rear camera, bluetooth communication module, MCU and HUD, It is very useful and can decrease of person's damage and handle expeditious traffic accident during autobike accident. In this paper, when this, "Providing system of autobike driver's information and e-call function", software is developed, a proper analysis and design method for practical affairs try to be presented due to showing software development analysis method, architecture of hardware block-diagram, flowchart and UI design.

• Journal of Advanced Navigation Technology
• /
• v.18 no.1
• /
• pp.14-21
• /
• 2014

In this paper, we devise a new ontology-based context-aware system to recognize the smart car information, in which driver's intent is utilized by information of car, driver, environment as well as driving state, driver state. So proposed system can handle dynamically risk changes by adding real-time situational awareness information. We utilize the camera image recognition technology for context-aware intelligent vehicle driving information, and implement information acquisition scheme OBD-II protocol to acquire vehicle's information. Experiments confirm that the proposed advanced driver safety assist system outperforms the conventional system, which only utilizes the information of vehicle, driver, and environmental information, to support the service of a high-speed driving, lane-departure service and emergency braking situation awareness.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.48
• /
• pp.145-152
• /
• 1998

Driving performance is characterized by many things such as driver's experience period, age, ability of information processing and reaction time of control devices and so forth. However, each factor of driving performance is needed to help and screen a poor driver for safe driving. In this paper, driving performance was estimated by reaction of manipulating brake, accelerator, steering wheel and speed. Subjects were grouped by experience of accident and age. Combinations of every group were analysed. For all the dependent variables, only steering wheel and speed were shown to have significant difference, which could be regarded as visual information of speed and direction were the important factors to drive safely. Especially for tile elderly, it is needed to enhance their ability of visual information processing that is to be decreased with aging. Therefore driving simulator to train and screen the poor driver should be studied.