• Transactions of the Korean Society of Automotive Engineers
• /
• v.18 no.4
• /
• pp.31-39
• /
• 2010

Although driving patterns strongly influence greenhouse gas and air pollutant emission rate from light duty vehicles, emission measurements have been mainly based on chassis dynamometer testing with one standard driving pattern. And there has been limited work on quantifying the independent effect of driving parameters on emission rate because of multidimensional nature of real-world driving pattern. The objective of this study is to obtain the quantitative effect of relative positive acceleration (RPA) on vehicle emission rate. RPA has been used to define the occurrence of acceleration demanding large amounts of power in certain driving distance and shown to be a significant affecting parameter for real-world emission rate. 40 driving patterns have been developed with fixed driving parameters to investigate independent effect of RPA. For the same values of average vehicle speed and power, the trend in carbon dioxide emission rate and fuel consumption with respect to RPA is very clear. Emission rate of nitrogen oxide and particulate matter also increase with respect to RPA, but the trend is less clear. Carbon dioxide emission from diesel vehicle appear to be more affected by high accelerations compared to that from gasoline vehicle because of high intake air restriction during acceleration caused by turbocharger and intercooler. The results have implications for the possible reduction of environmental effects through better traffic planning and management, driver education and car design.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.173-178
• /
• 1998

The strategy presented in this paper is based on modifying the past patterens and adjusting the content of the driving patterns by a new algorithm. Learning happens during the driving procedure of a mobile vehicle. The purpose of this paper is to solve the problem how to realize the hardware neurocomputer by back propagation (BP) neural network learning on-line.

• Journal of Mechanical Science and Technology
• /
• v.19 no.4
• /
• pp.993-1000
• /
• 2005

A vehicle cruise control strategy designed based on human drivers driving characteristics has been investigated. Human drivers driving patterns have been investigated using vehicle driving test data obtained from 125 participants. The control algorithm has been designed to incorporate the driving characteristics of the human drivers and to achieve natural vehicle behavior of the controlled vehicle that would feel comfortable to the human driver. Vehicle following charac­teristics of the cruise controlled vehicle have been investigated using real-world vehicle driving test data and a validated simulation package.

• Journal of the Ergonomics Society of Korea
• /
• v.26 no.2
• /
• pp.89-102
• /
• 2007

Generally, it is well known that driving in tunnel imposes large burden to driver because of spatial constraint, limited visual field and so on. And such a burden of driver result in high accident occurrence. In this reason, studies dealing with features of driving and traffic flow in tunnel have been performed. However, information about characteristics of drivers and traffic in a very long tunnel is not accumulated yet. The purpose of this study is to identify the relations between tunnel length and burden of driver, driving patterns, traffic flow characteristics using the tunnel simulator that realizing various tunnel situations. For this, the tunnel simulation program was developed along 11km-length section. And biological data of 10 subjects gained from driving condition in simulation program was analyzed and compared with the result of real driving condition.

• Journal of Korea Multimedia Society
• /
• v.25 no.2
• /
• pp.421-431
• /
• 2022

The purpose of this research is to determine the point of fixation of the driver during the process of driving. Based on the results of this research, the driving instructor can make a judgement on what the trainee stare on the most. Traffic accidents have become a serious concern in modern society. Especially, the traffic accidents among unskilled and elderly drivers are at issue. A driver should put attention on the vehicles around, traffic signs, passersby, passengers, road situation and its dashboard. An eye-tracking-based application was developed to analyze the driver's gaze behavior. It is a prototype for real-time eye tracking for monitoring the point of interest of drivers in driving practice. In this study, the driver's attention was measured by capturing the movement of the eyes in real road driving conditions using these tools. As a result, dwelling duration time, entry time and the average of fixation of the eye gaze are leading parameters that could help us prove the idea of this study.

• Journal of Korean Society of Transportation
• /
• v.35 no.6
• /
• pp.545-556
• /
• 2017

Various assessment indexes have been developed and utilized to evaluate the driver workload. However, existing workload assessment indexes do not fully reflect driving habits and driving patterns of individual drivers. In addition, there exists significant differences in the amount of workload experienced by a driver and the ability to overcome the driver's workload. To overcome these limitations associated with existing indexes, this study has developed a novel workload assessment index to reflect an individual driver's driving pattern. An average of the absolute values of the steering velocity for each driver are set as a threshold value in order to reflect the driving patterns of individual drivers. Further, the sum of the areas of the steering velocities exceeding the threshold value, which is defined as erratic steering area (ESA) in this study, was quantified. The developed ESA index is applied in evaluating the driver workload of manually driven vehicles in automated vehicle platooning environments. Driving simulation experiments are conducted to collect drivers' responsive behavior data which are used for exploring the relationship between the NASA-TLX score and the ESA by the correlation analysis. As a result, ESA is found to have the greatest correlation with the NASA-TLX score among the various driver workload evaluation indexes in the lane change scenario, confirming the usefulness of ESA.

• Proceedings of the KIEE Conference
• /
• 2003.11c
• /
• pp.844-847
• /
• 2003

Display devices are becoming increasingly important as an interface between humans and machines in the growing information society. In display devices, PDP (Plasma Display Panel) has many advantages in that it has wide screen, wide viewing angle and is light weight, thin. In PDP driving method, if the brightness of input image is high, applying the fixed sustain pulse to the PDP panel will raise the PDP power consumption and may damages the PDP panel. To overcome these problems, the Plasma AI driving method was introduced by the Matshushita co. in Japan. The Plasma AI driving module calculates the peak value and average value of 1 frame image and adjusts the gradation and sustain pulses for 1 frame sustain. In this paper, the proposed PDP driving module is based on the Plasma AI driving module. The proposed driving module calculates peak value and average value, and the brightness distribution of 1 frame image. Using brightness distribution, the proposed driving module divides 1 frame input image into 15 image patterns. For each image pattern, minimum sustain pulses and sub-frames are used for the brightness of 1 frame image and the sustain weight for 64, 128, 192 gradation is proposed. Therefore, the sustain power consumption can be reduced.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.7
• /
• pp.919-928
• /
• 2010

Four patterns for width adjustment were studied with an aim to increase the width-adjustment speed in continuous casting. The main goals are to minimize the actuating force of a WAM actuator, to develop a deformation analysis model of a solidified shell in the mold, and to induce the main limit factor for the speedup of width adjustment. On the basis of the width-adjustment experiment, the notable features of four patterns types were considered, and we compared the corresponding actuating forces. For comparing the driving forces of the patterns, during the experiment, the same casting speed was maintained for each pattern. To optimize the parameter of the deformation analysis model of the solidified shell, the experiment results were applied to them. To speed up width adjustment and to reduce the driving force, we controlled the pattern parameters. The most effective pattern was the fast-mode pattern, and the taper was the main parameter that helped reduce the driving forces during the motion of the actuator.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.10
• /
• pp.8-19
• /
• 2019

In this study, the spray pattern of a centrifugal fertilizer distributor with two shutter holes was analyzed and an effective driving width that satisfies proper spray uniformity was derived. The centrifugal fertilizer distributor was mounted on a tractor with a rated power of 23.7 kW and static and dynamic spray pattern tests were performed according to the standard procedure proposed by the American Society of Agricultural and Biological Engineers Standard ASAE S341.5. The height of the fertilizer distributor was 80 cm from the ground and the PTO (power take-off) shaft speed of the tractor was fixed at 540 rpm. The fertilizer scattered in space was collected using 275 evenly spaced collectors at shutter opening ratios of 25%, 50%, 75%, and 100%. The spray pattern was analyzed via the amount of sprayed fertilizer at each collector location and the coefficient of variation was used as an indicator of spray uniformity. Using the analyzed spray pattern, the effective driving width that satisfied less than 15% of the coefficient of variation was derived for different tractor driving patterns (race track mode, back and forth mode). From the results, spray uniformity increased as the shutter opening ratio decreased. The largest effective driving width was 8 m at a shutter opening ratio of 25% for both driving patterns.

• Journal of Information Processing Systems
• /
• v.13 no.2
• /
• pp.285-304
• /
• 2017

Big data information and pattern analysis have applications in many industrial sectors. To reduce energy consumption effectively, the eco-driving method that reduces the fuel consumption of vehicles has recently come under scrutiny. Using big data on commercial vehicles obtained from digital tachographs (DTGs), it is possible not only to aid traffic safety but also improve eco-driving. In this study, we estimate fuel consumption efficiency by processing and analyzing DTG big data for commercial vehicles using parallel processing with the MapReduce mechanism. Compared to the conventional measurement of fuel consumption using the On-Board Diagnostics II (OBD-II) device, in this paper, we use actual DTG data and OBD-II fuel consumption data to identify meaningful relationships to calculate fuel efficiency rates. Based on the driving pattern extracted from DTG data, estimating fuel consumption is possible by analyzing driving patterns obtained only from DTG big data.