• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.6
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• pp.635-641
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• 2016

Regenerative braking performance of an electrically powered vehicle is closely related to driving distance per battery charge. An electric vehicle uses appropriate amounts of mechanical braking force and electromagnetic regenerative braking force to recover energy and increase driving efficiency. In particular, when it drives on a downhill road, energy recovery rate is maximized through regenerative braking during coasting based on the mass inertia of the vehicle. Since an electric two-wheeled vehicle covered in this paper is lighter than an electric four-wheeled vehicle, the improvement of its driving distance per battery charge through regenerative braking is different from an electric four-wheeled vehicle. This study compared the driving characteristics of an electric two-wheeled vehicle based on regenerative braking. Two driving test modes were simulated with a chassis dynamometer system. By analyzing the measurement of a chassis dynamometer, the driving characteristics of a two-wheel electric vehicle, such as driving efficiency, were analyzed. In addition, test results were reviewed to draw the limitations of conventional test methods for regenerative braking performance of an electric two-wheel vehicle.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.1063-1066
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• 1996

On the prediction of driving performance, an acceleration performance is normally simulated in stall starting condition which is the engine status of full-throttle and high-speed. The lack of transient engine torque data makes the difficulty of predicting an acceleration performance on engine-idle start condition. A experimental equation of transient engine torque is derived from vehicle performance test data. It is applied to simulation the accleration performance prediction on idle starting condition.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.6
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• pp.90-99
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• 1999

A vehicle driving simulator is a virtual reality device which a human being feels as if the one drives a vehicle actually. The driving simulator is used effectively for studying interaction of a driver-vehicle and developing vehicle system of a new concept. The driving simulator consists of a vehicle motion bed system, motion controller, visual and audio system, vehicle dynamic analysis system, cockpit system, and etc. In it is paper, the main procedures to develop the driving simulator are classified by five parts. First, a motion bed system and a motion controller, which can track a reference trajectory, are developed. Secondly, a performance evaluation of the motion bed system for the driving simulator is carried out using LVDTs and accelerometers. Thirdly, a washout algorithm to realize a motion of an actual vehicle in the driving simulator is developed. The algorithm changes the motion space of a vehicle into the workspace of the driving simulator. Fourthly, a visual and audio system for feeling higher realization is developed. Finally, an integration system to communicate and monitor between sub systems is developed.

• Phonetics and Speech Sciences
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• v.5 no.2
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• pp.93-97
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• 2013

This paper is on designing an indoor driving simulator to evaluate the performance of in-car speech recognizer when influenced by the elements, which lower the success rate of speech recognition. The proposed simulator simulates vehicle noise which was pre-recorded in diverse driving environments and driver's speech. Additionally, the proposed Lombard effect conversion module in this simulator enables the speech recorded in a studio environment to convert into various possible driving scenarios. The relevant experimental results have confirmed that the proposed simulator is a feasible approach for realizing an effective method as it achieved similar speech recognition results to the real driving environment.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.185-188
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• 1999

An estimation algorithm for vehicle driving load has been proposed in this paper. Driving load is an important factor in a vehicle's longitudinal motion control. An approach using an observer is introduced to estimate driving load based on inexpensive RPM sensors currently being used in production vehicles. Also, a torque estimation technique using nonlinear characteristic functions has been incorporated in this estimation algorithm. Using a nonlinear full vehicle simulation model, we study the effect of the driving load on longitudinal vehicle motion, and the performance of the estimation algorithm has been evaluated. The proposed estimation algorithm has good performance and robustness over uncertainties in the system parameters. An accurate estimate of the driving load can be very helpful in the development of advance vehicle control systems such as intelligent cruise control systems, CW/CA systems and smooth shift control systems.

• ETRI Journal
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• v.37 no.3
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• pp.626-636
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• 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 Advanced Marine Engineering and Technology
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• v.32 no.4
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• pp.550-556
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• 2008

The aim of this research is to analyze the influence of motive pressure, driving nozzle position and nozzle throat ratio on the performance of ejector. The experiment was conducted in the variation of motive pressure of 0.196, 0.294, 0.392 and 0.490MPa respectively. The position of driving nozzle was varied in difference locations according to mixing tube diameter(0.5d, 1d, 2d, 3d, 4.15d, 5d and 6d). The experimental results show when the nozzle outlet is located at 3d, the flow characteristics change abruptly. It is shown that the suction flow rate and pressure lift ratio of ejector is influenced by the driving nozzle position. At nozzle position location of the Id of mixing tube diameter the performance of ejector gives the best performance.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.20-25
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• 2022

This paper represents an adaptive Region of Interest (ROI) decision for real-time performance in an autonomous driving perception module. Since the whole automated driving system consists of numerous modules and subdivisions of module occur, it is necessary to consider the characteristics, complexity, and limitations of each module. Furthermore, Light Detection And Ranging (Lidar) sensors require a considerable amount of time. In view of these limitations, division of submodule is inevitable to represent high real-time performance for stable system. This paper proposes ROI to reduce the number of data respect to computation time. ROI is set by a road's design speed and the corresponding ROI is applied differently to each vehicle considering its speed. The simulation model is constructed by ROS, and overall data analysis is conducted by Matlab. The algorithm is validated using real-time driving data in urban environment, and the result shows that ROI provides low computational costs.

• Journal of Drive and Control
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• v.20 no.4
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• pp.100-106
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• 2023

We developed a crawler-based driving platform that can perform harvesting, transportation, pest control, and rotary operation by equipping it with various implements, and analyzed its performance. This single platform was developed to perform as pepper harvester, peanut harvester, and transporter with a 46-kW engine. A simulation model was developed to study the specifications of the platform, and the accuracy was also analyzed. The absolute percentage error ranged from 0.2 to 5.9%, which made it possible to predict the platform performance using simulation model. In T-test, both torque and speed on field and asphalt showed a significant difference (1%). Driving torque required differed depending on the nature of the field, and the speeds also changed based on soil load. The developed platform has the advantage of being equipped with a variety of working tools, expected to be used to harvest root crops in the future.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.641-652
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• 2021

Drivers have willing to do secondary tasks in situations deemed safe autonomous driving. I studied that positive notifications for secure areas could improve situation awareness and driving performance after TOR(Take over request) in autonomous driving. Comparing TOR alert only and monitoring alert conditions, participants in the positive notification condition showed higher situation awareness and driving performance. Also, in emotional assessment, the positive notification condition showed higher positive evaluation than other conditions. Due to Covid-19, I designed experiments separate online with driving videos in experiment 1 and offline using a driving simulator in experiment 2. This study has implications that presented a different perspective on autonomous driving notification design.