• Journal of the Korean Society of Safety
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• v.28 no.3
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• pp.23-28
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• 2013

This study focuses on finding ways to derive train's optimal ECO driving pattern, which can improve the ride quality and reduce driving energy consumption with keeping the time interval between the stations. As research method, we compared difference of currently operating train's ATO and MCS driving patterns, and concentrated upon the things need to consider in simulation in order to improve the existing pattern of ATO driving pattern's issues with securing the train operation safety. Determining driving pattern minimizing energy consumption by controlling powering within speed limit and controlling switching to coasting at appropriate point considering the track conditions for each section, and determining braking control starting time considering ride comfort and precise stopping is considered to be most important.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.173-178
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• 2013

It is a concern that eco-driving vehicles, because their driving behavior differs from other vehicles due to e.g. e-start, may inhibit smooth traffic flow. Therefore, it is necessary to study the cooperative eco-driving done by a vehicle group, putting "vehicle-to-vehicle communication" and "road-to-vehicle communication" into perspective. Based on these factors, this study aimed to: 1) Analyze fuel consumption rates and driving behaviors of more than one vehicle following an Eco-Driving vehicle. 2) Examine the effect of information on the fuel consumption rate of the preceding vehicles on the following vehicles. As a result, the following findings were obtained: 1) By providing information to multiple following vehicles, the fuel consumption rate of the second vehicle was not lowered, while that of the third one was. 2) It is possible that, when information on fuel consumption of a preceding vehicle is provided to the following one, an inter-vehicular distance is shortened during deceleration to contribute to smooth traffic flow. From the above results, it is suggested that, when targeting a vehicle group, sharing the information on preceding vehicles is effective.

• Journal of the Korea Convergence Society
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• v.2 no.4
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• pp.15-19
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• 2011

The transportation and logistics industries, the constructions of a green transport methods for logistics systems are presented. They aims the greenhouse gas emissions 37% savings compared to BAU(Business As Usual) for a green growth of national strategy by 2020. An eco-driving training for truck drivers is a typical way. However there are few studies such as the integrated data collection automatically and the diagnostic Assessments and monitoring methods of logistics network status to show the effects of the eco-driving. To solve this problem, this paper provides previous research on logistics network diagnostics assessments and monitoring service and eco-driving. Then this paper shows developments of the logistics network diagnostic assessments and monitoring service business flow to promote eco-driving behaviors for truck drivers based on a smart phone application. Also, it shows an efficiency through an application results in field test.

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

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.77-84
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• 2016

In 2012, total GHG emissions in transport sector reached 88 Million ton CO2eq. The emissions generated in the road accounted for 94% of the transport sector. Currently, there are many efforts to operate an education and campaign for eco-driving. However study for eco-friendly vehicle control considering road alignment is limited. Therefore, the purpose of this study is to address fuel-efficient driving strategy in horizontal curve section. To fulfill the goal, designed ideal freeway horizontal curve road follows regulations about road structure. And safety speed is calculated for considering vehicle's safety on horizontal curve road. Authors composed the acceleration and deceleration scenario for each horizontal curve section and generated the speed profiles that are limited by the safety speed. Speed profiles are converted into force that horizontal curve affect to fuel consumption. Then, we calculated fuel consumption using Comprehensive Modal Emission Model. Then, we developed eco-driving strategy by selecting most fuel-efficient scenario. To validate this strategy, we selected study site and compared fuel consumption for eco and manual driving. As the result, fuel consumption when driver used eco-driving was lessened by 20.73% than that of manual driving.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.77-84
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• 2015

In 2011, greenhouse gas emissions of transport sector were 85.04 million $tonCO_2eq$ and road emissions accounted for 95% of total emissions in the transport sector. There are few innovative technologies to reduce greenhouse gas emissions aside from eco-driving education and public relation program. Therefore, this paper focused on analyzing optimal acceleration by certain road grades and suggested fuel-efficient driving method for various uphill sections. Scenarios were established by driving modes. Speed profiles were generated by scenarios and speed variations. Each speed profile applied to Comprehensive Modal Emission Model and then each fuel consumption was estimated. Driving mode and speed variation that minimized fuel consumption were driven according to grade percent and uphill distance. When driving in the eco-friendly mode of the driving and speed variation, reduction rate of fuel consumption was evaluated by comparison between eco-driving and cruise control mode. When a vehicle drove under eco-driving mode at 100kph, 90kph and 80kph on uphill road, fuel consumptions were reduced by 33.9%, 30.8% and 5.3%, respectively.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.55-62
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• 2015

In this paper, we proposed the method that enabling warning through real-time analysis of dangerous driving behavior, improving driving habits and safe driving using the digital tachograph. Most of traffic accidents and green drive are closely related of driving habits. These wrong driving habits need to be improved by the real-time analysis, warning and automated method of driving habits. We confirmed the proposed that the method will help support eco-driving, safe driving through real-time analysis of driving behavior and warning through the method implementation and experiment.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.132-138
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• 2015

This study examined the relative effects of feedback frequency and specificity of Eco-IVIS(eco in-vehicle information system) on the fuel-efficiency and workload. Eighty participants randomly assigned into four experimental groups (high frequency/specific, high frequency/global, low frequency/specific, and low frequency/global feedback) and they drove 16.4Km motorway under the each feedback condition. The dependent variable were fuel efficiency and Drive Activity Load Index which measured participants' subjective ratings of driving workload. The results showed that high frequent feedback was more effective for increasing fuel-efficiency than low frequent feedback, however, there was no significant difference of fuel-efficiency between specific and global feedback. Although, overall DALI score was comparable among four experimental conditions, visual demand score was significant higher under the high frequent feedback condition than low frequent feedback.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.151-160
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• 2009

The aim of this study is to propose economical driving speed index which those are geometric road status; assess the levels of which those cost-benefit of driving energy consumption and emission; are search road safety design and operational technology for driving simulator. For the objective, we analyzed the current status of driving energy consumption and driving scenarios by the road alignments, and reviewed driving and technical specifications by the geometric types of road according to the implementation, and extended completion. Throughout the result of this study, diverse related driving information provision service, efficiently navigation driving module is expected to be implemented in the national highway design system.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.163-174
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• 2023

Purpose - This study examines the effect of consumers' motivations on the perception and purchase intentions of electric cars. Specifically, it empirically analyzes how moral motivations based on personal environmental values and norms in car usage and purchasing influence the perceived usefulness and purchase intentions of electric cars. Furthermore, it investigates whether the influence of moral motivations on perceived usefulness and purchase intentions varies according to the user's driving characteristics. Design/methodology/approach - An online survey was conducted with 234 respondents, by setting criteria for participants as car owners or primary car users within their households, ensuring the sample composition was not biased in terms of the presence or absence of experience with eco-friendly cars. Findings - The research findings indicate that perceived usefulness mediates the effect of consumers' moral motivations on their intention to purchase electric cars. The results of the moderating effect of driving distance on perceived usefulness revealed a significant interaction effect; however, there was no significant interaction effect on purchase intentions. Specifically, for individuals with shorter driving distances, as consumers' moral motivations increase, their perception of the usefulness of electric cars also increases. In contrast, for those with longer driving distances, the increase in perceived usefulness due to moral motivations shows a decreasing trend. Research implications or Originality - This study considered individual driving characteristics that previous research on electric vehicle adoption overlooked, and suggested that setting specific communicating points for electric cars according to driving distance levels might be effective. Lastly, it proposes directions for future research that motivations influencing eco-friendly vehicle purchases may differ based on driving characteristics