• Journal of Animal Science and Technology
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• v.65 no.4
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• pp.878-889
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• 2023

Animal welfare during transport became an largely issue because of increasing demand for improved animal welfare standards. Most studies on the animal welfare during transportation have concentrated on the atmosphere and the temperature of the truck compartments. Thus, the objective of study was to collect and quantify three axis acceleration and determine the effect of bedding for transporting pigs from farm to slaughterhouse. A total of 2,840 crossbred fattening pigs with a live weight of approximately 115 kg were used. They were raised in the same commercial farms and transported to the same commercial slaughterhouse. A 3×2×2 completely randomized factorial design was used to investigate effects of rubber type bedding (bedding or non-bedding) and two levels of driving style (aggressive or normal) in three different time periods with different outside temperatures. Air temperature treatments were as follow: high temperature ([HT] higher than 24℃); low temperature ([LT] lower than 10℃); normal temperature ([NT] 10℃ to 24℃). In our experiment, pigs transported under aggressive driving style showed lower (p < 0.05) pH and water holding capacity (WHC) than those transported under normal driving style. Pigs transported under normal driving style showed a lower percentage of drip loss (DL) (p < 0.05) than those transported with an aggressive driving style. Also, transported with bedding showed higher (p < 0.05) lying behavior but lower (p < 0.05) sitting behavior than those transported without bedding. Pigs transported under normal driving style showed lower (p < 0.05) cortisol level than those transported under aggressive driving style. In conclusion, aggressive driving style cause acute stress in pigs, while bedding helps alleviate acute stress in pigs during transportation in LT.

• Journal of ILASS-Korea
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• v.24 no.2
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• pp.73-81
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• 2019

It is expected that the introduction of real-driving emission will strengthen the exhaust emission. However, various researches have been reported that real-driving emission has been influenced by factors such as characteristics of the test routes and driving characteristics for drivers. In order to reflect this effect, European Commission applied the concept of driving dynamics to prevent deliberately driving of excessive and acceleration over RDE test. The purpose of this study is to analyze the characteristics of exhaust emissions according to real-driving test in three test routes and driving style. As a result of the test, it was confirmed that when the same driver tested real-driving test under three test routes, it depends on the driving characteristics of the route. Also, RDE-NOx for driving style was that severe driving has been about 16 times higher than normal driving in KNUT route.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.39-47
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• 2023

The development of autonomous driving and Advanced Driver Assistance System (ADAS) technology has grown rapidly in recent years. As most traffic accidents occur due to human error, self-driving vehicles can drastically reduce the number of accidents and crashes that occur on the roads today. Obviously, technical advancements in autonomous driving can lead to improved public driving safety. However, due to the current limitations in technology and lack of public trust in self-driving cars (and drones), the actual use of Autonomous Vehicles (AVs) is still significantly low. According to prior studies, people's acceptance of an AV is mainly determined by trust. It is proven that people still feel much more comfortable in personalized ADAS, designed with the way people drive. Based on such needs, a new attempt for a customized ADAS considering each driver's driving style is proposed in this paper. Each driver's behavior is divided into two categories: assertive and defensive. In this paper, a novel customized ADAS algorithm with high classification accuracy is designed, which divides each driver based on their driving style. Each driver's driving data is collected and simulated using CARLA, which is an open-source autonomous driving simulator. In addition, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) machine learning algorithms are used to optimize the ADAS parameters. The proposed scheme results in a high classification accuracy of time series driving data. Furthermore, among the vast amount of CARLA-based feature data extracted from the drivers, distinguishable driving features are collected selectively using Support Vector Machine (SVM) technology by comparing the amount of influence on the classification of the two categories. Therefore, by extracting distinguishable features and eliminating outliers using SVM, the classification accuracy is significantly improved. Based on this classification, the ADAS sensors can be made more sensitive for the case of assertive drivers, enabling more advanced driving safety support. The proposed technology of this paper is especially important because currently, the state-of-the-art level of autonomous driving is at level 3 (based on the SAE International driving automation standards), which requires advanced functions that can assist drivers using ADAS technology.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.3
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• pp.35-42
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• 2012

The database for driving patterns can be utilized in various system such as automatic driving system, driver safety system, and it can be helpful to monitor driving style. Therefore, we propose a driving pattern recognition system in which the sensor streams from a smartphone are recorded and used for recognizing driving events. In this paper we focus on the driving pattern recognition that is an essential and preliminary step of driving style recognition. We divide input sensor streams into 7 driving patterns such as, Left-turn(L), U-turn(U), Right-turn(R), Rapid-Braking(RB), Quick-Start(QS), Rapid-Acceleration (RA), Speed-Bump(SB). To classify driving patterns, first, a preprocessing step for data smoothing is followed by an event detection step. Last the detected events are classified by DTW(Dynamic Time Warping) algorithm. For assisting drivers we provide the classified pattern with the corresponding video stream which is recorded with its sensor stream. The proposed system will play an essential role in the safety driving system or driving monitoring system.

• Proceedings of the ESK Conference
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• 1995.10a
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• pp.208-213
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• 1995

The vehicle navigation system is developed for helping driver to retrieve driving information more easily and lastly. Navigation System informs driver many pieces of driving information - roadway structure and system, on-line traffic condition, the position of vehicle, route guidance, destination and other infor- mation service. As the style of information is diverse and the amount of information is large, driver may have mental and visual overload. The display of information can disturb the driver's attention and this can cause accidents. This state is caused by the defect of human-machine interactions. When the navigation system is designed, human factors - cognitive, judgment, operating -must be considered. The display style must be designed simply and easily, not to be obstacle of human - machine interface. In this study, outside- in view display style and inside-out view display style are compared each other. Tow factors are measured. One is cognitive factor-time of cognition on information that is displayed by screen display, cognition error rate. The other is image of screen display - subject's feeling about several styles of display, degree of subject's preference. The prototype of roadway is four kinds -Cross, T-cross and O-cross. Roadway display for test is taken from paper maps. Traffic condition display style, vehicle position display style and route guidance display style are taken from current display style. Traffic condition display style is symbol. vehicle position display style and route guidance display style are described as color and symbol. The test on screen display is implemented doing given tasks. Then the test is analyzed statistically. The result of test analysis gives the guideline to the designer for the map display of the vehicle navigation system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.49-59
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• 1995

The vehicle navigation system is developed for helping driver to retrieve driving information more easily and fastly. Navigation System informs driver many pieces of driving information - roadway structure and system, on-line traffic condition, the position of vehicle, route guidance, destination and other information service. As the style of information is diverse and the amount of information is large, driver may have mental and visual overload. The display of information can disturb the driver's attention and this can cause accidents. This state is caused by the defect of human-machine interactions. When the navigation system is designed, human factors - cognitive, judgment, operating - must be considered. The display style must be designed simply and easily, not to be obstacle of human -machine interface. In this study, outside-in view display style and inside-out view display style are compared each other. Two factors are measured. One is cognitive factor-time of cognition on information that is displayed by screen display, cognition error rate. The other is image of screen display - subject's feeling about several styles of display, degree of subject's preference. The prototype of roadway is four kinds - Cross, T-cross, Y-cross and O-cross. Roadway display for test is taken from paper maps. Traffic condition display style, vehicle position display style and route guidance display style are taken from current display style. Traffic condition display style is symbol. Vehicle position display style and route guidance display style are described as color and symbol. The test on screen display is implemented doing given tasks. Then the test is analyzed statistically, The result of test analysis gives the guideline to the designer for the map display of the vehicle navigation system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6830-6837
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• 2014

Since the advent of global warming and energy depletion, there has been great interest in eco-driving (energy-efficient driving). In this paper, a system is proposed to monitor the idle running of an engine and steady driving for a vehicle equipped with an ISG (Idling Stop & Go system). The system consists of a G/W device to acquire the vehicle operation data, a smartphone app for monitoring eco-driving and a server system. The main contribution of this paper is that it defines the integrated functions, the architecture and operation mechanisms of a system for monitoring eco-driving including the prohibition of running idle. The system enables the users to check the idling stop times, driving speeds, fuel savings, and $CO_2$ emissions, resulting in the driving style for eco-driving. The server system, which is a part of this system, provides OpenAPI-style web services for the storage and retrieval of car operation data, which facilitates the development of applications.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.21-29
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• 2015

The purpose of this paper was to investigate various factors influencing the intentions of drink-driving from multiple perspectives, in order to uncover ways to reduce the number of motor accidents caused by drink-driving. We examined sociopsychological aspects as well as driver's life styles such as smoking habit and exercise habit. Perception of behaviour controls among drink-driver' sociopsychological characteristics had the highest influence on the intentions of drink-driving, followed by influence of smoking and exercise on the intentions of drink-driving. This finding indicates that driver' life style such as smoking habit or exercise habit influences more on the intentions of drink-driving than attitude toward drink-driving or subjective regulations, which affirms that driver' life style such as smoking habit or exercise habit has significant effects on the intentions of drink-driving. Therefore, it is concluded that rehabilitative curriculum for drink-drivers should include a program to diminish drink-driving through nonsmoking and exercise habit.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.1
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• pp.18-23
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• 2011

We have investigated the Intelligent Shift-map Module(ISM) to improve some problems in the conventional Automatic Transmission(AT) for automobiles. The typical AT lacks flexibility regarding the shift point because it does not consider the driver's habits and inclinations. Also it often is occurred phenomenon like kick-down. Therefore, we designed a decision module which considers the driving style of the individual driver. The driving style was determined by the inclination of the driver and the driving technique using actual automobile data. The Hierarchical Neural Network(HNN) was applied in generating an intelligent shift map with Multilayer Neural Network(MNN). It was found that the proposed ISM provided a suitable shift point and time because the necessary toque and velocity of the automobile was considered along with the driving style of each driver when designing the ISM.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.157-165
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• 2014

To develop a compact vehicle for women, the most important areas are 'behavioral characteristics, life style and driving posture'. Static AM95%ile manikin is used for package guideline. Since women's characteristics and sitting position are different from men, however, the guideline cannot satisfy women drivers. Therefore, the goal of this study is to make the database with dynamic women's driving posture and behavioral characteristics at compact vehicle. Research process will be made as follows. Firstly, through the online/offline survey and statistic analysis, lifestyle and behavioral characteristics (discomfort elements) of women are extracted. Secondly, the author performs scenario test to acquire the discomfort value of driving situation and life style. 3D models of women's manikin and driving posture were created by CATIA HUMAN. The 3D models are used for the purpose of analyzing women's driving posture. Finally, with the ANOVA result and comparison between real driving posture and package guidelines, the author is able to suggest the main issue for women drivers.