• Journal of applied mathematics & informatics
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• v.30 no.1_2
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• pp.1-14
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• 2012

In this paper, the problem of determining the optimal car-deriving strategy has been examined. In order to find the optimal driving strategy, we have modified a method based on measure theory. Further, we demonstrate that the modified method is an efficient and practical algorithm for dealing with optimal control problems in a canonical formulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5842-5861
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• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.888-894
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• 2011

This paper is a study of optimal train driving strategy to minimize the energy consumption. Optimal driving strategy can be analyzed as an optimal problem which have constraints by using Largrangian Function and Kuhn-Tucker condition. We simulate the section between Konkuk University Station and Seongsu Station which is on outer circle line of the Seoul Metro line No.2 by using MATLAB and consider the straight level track and the speed limit.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5759-5779
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• 2017

As the main means to cope with the stubborn problem of drunk driving, the inspection of drunk driving has already been paid more attention and thus reinforced. In this paper, we model this scenario as a Stackelberg game, where the police department (called defender) allocates resources dynamically in terms of the traffic situation on the traffic network to arrest drink drivers and drivers who drink (called attacker), whether choosing drunk driving or designated driving service, expect to minimize their cost for given travel routes. However, with the number of resources are limited, our goal is to calculate the optimal resource allocation strategy for the defender. Therefore, first, we provide an effective approach (named OISDD) to fulfill our goal, i.e., generate the optimal strategy to inspect drunk driving. Second, we apply OISDD to directed graphs (which are abstracted from Dalian traffic network) to analyze and test its correctness and rationality. The experimental results show that OISDD is feasible and efficient.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.73-82
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• 2017

As of December 2016, the number of registered automobiles in Korea exceeds 21million. As a result, greenhouse gas emission by transportation sector are increasing every year. It was concluded that the development of the driving strategy considering the driving behavior and the road conditions, which are known to affect the fuel efficiency and the greenhouse gas emissions, could be the most effective fuel economy improvement. Therefore, this study aims to develop a fuel efficient driving strategy in a complex linear section with uphill and curved sections. The road topography was designed according to 'Rules about the Road Structure & Facilities Standards'. Various scenarios were selected. After generating the speed profile, it was applied to the Comprehensive Modal Emission Model and fuel consumption was calculated. The scenarios with the lowest fuel consumption were selected. After that, the fuel consumption of the manual driver's driving record and the selected optimal driving strategy were compared and analyzed for verification. As a result of the analysis, the developed optimal driving strategy reduces fuel consumption by 21.2% on average compared to driving by manual drivers.

• Journal of Digital Convergence
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• v.3 no.2
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• pp.117-130
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• 2005

Managing of local government public service is innovation strategy of local government public service using choice and competition principle. Managing strategy of local government public service is new paradigm for innovating public service and role structure of government. It is important to understand properly substance and characteristics of local government public service Accordingly, the purpose of this study understand substance and characteristics of local government public service and describe strategic driving plan of managing local government public service in the future.

• Journal of Drive and Control
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• v.12 no.3
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• pp.18-24
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• 2015

The plug-in hybrid electric vehicle has a high fuel economy and can be driven long distances. Its different modes include the electric vehicle, hybrid electric vehicle, and only engine operating mode. A power management strategy is important to determine which mode should be selected. The strategy makes the vehicle more efficient using appropriate power sources for driving. However, the strategy usually needs a driving speed profile which is future driving cycle. If the profile is known, the strategy easily determines which mode is driven efficiently. However, it is difficult to estimate the speed profile for a real system. To address this problem, this paper proposes a new power distribution strategy using a neural network. The average speed and driving range are used as input parameters to train the neural network system. The strategy determines a limit for the use of the battery and the desired power is distributed between the engine and the motor simultaneously. Its fuel economy can increase by improving the basic strategy.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.191-197
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• 2004

This paper presents experimental results for human drivers' driving patterns and an Adaptive Cruise Control(ACC) strategy. Analyses have shown that female drivers' driving characteristic values such as time-gap and minimum clearance are larger than those of male drivers'. Human drivers tend to have more clearance margins at high speed than at low speed. At low speed, drivers are much more sensitive to the desired clearance than at high speed. A multi-vehicle detection method is presented to improve ride quality of an ACC. Simulation results have shown that the proposed ACC can provide superior performance compared to the ACC strategy which uses a single-vehicle detection method.

• Proceedings of the Safety Management and Science Conference
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• 2006.04a
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• pp.429-436
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• 2006

Standardization strategy is considered as an important approach for the organization growth and competitiveness. Major contents of standardization are the selection of standardization area and management of standardization timing under limited resources. The developments of standardization road map and its driving strategy in construction area are important policy subjects in view of investment scale and national economy. In this paper, we aim to survey on the standardization theory and its application in construction field and suggest research direction for driving strategy of standardization road map development.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.284-288
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• 2004

Standardization strategy is considered as an important approach for the organization growth and competitiveness. Major contents of standardization are the selection of standardization area and management of standardization timing under limited resources. The developments of standardization road map and its driving strategy in construction area are important policy subjects in view of investment scale and national economy. In this paper, we aim to survey on the standardization theory and its application in construction field and suggest research direction for driving strategy of standardization road map development.