• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.284-298
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• 2023

With the rapid advances in automated driving technology, opportunities to experience automated driving directly or indirectly are being provided to the public. On the other hand, research on the preferred automated driving patterns from the user's perspective has not been conducted in Korea. This study used a driving simulator and an experimental vehicle capable of automated driving to evaluate the user satisfaction regarding longitudinal and lateral accelerations. Automated driving patterns were implemented in a virtual environment simulation using five values of longitudinal and lateral accelerations derived from driving experiments. Among these values, three were implemented through experimental vehicle-based automated driving to evaluate satisfaction and anxiety. The participants evaluated lateral acceleration more sensitively than longitudinal acceleration and showed higher levels of anxiety. Based on these results, the necessity of user-oriented evaluation research for automated driving patterns and the suitability of simulator-based evaluation methods were presented.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.249-255
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• 2018

This paper presents a human-centered control algorithm for personalized autonomous driving based on the integration of inverse time-to-collision and time headway. In order to minimize the sense of difference between driver and autonomous driving, the human-centered control technology is required. Driving characteristics in case that vehicle drives with the preceding vehicle have been analyzed and reflected to the longitudinal control algorithm. The driving characteristics such as acceleration, inverse time-to-collision, time headway have been analyzed for longitudinal control. The control algorithm proposed in this study has been constructed on Matlab/Simulink environment and the performance evaluation has been conducted by using actual driving data.

• Journal of Auto-vehicle Safety Association
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• v.12 no.2
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• pp.14-20
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• 2020

This paper presents a vehicle mass and road grade estimator for developing an automated bus. To consider the dynamic characteristics of a bus varying with the number of passengers, the longitudinal controller needs the estimation of the vehicle's mass and road grade in real-time and utilizes the information to adjust the control gains. Discrete Kalman filter is applied to estimate the time-varying road grade, and the recursive least squares algorithm is adopted to account for the constant mass estimation. After being implemented in MATLAB/Simulink, the estimators are evaluated with the dynamic model and experimental data of the target bus. The proposed estimators will be applied to complement the algorithm of the longitudinal controller and proceed with algorithm verification.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.10
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• pp.931-940
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• 2017

This paper describes a predictive fault diagnosis algorithm for autonomous vehicles based on a kinematic model that uses a sliding mode observer. To ensure the safety of autonomous vehicles, reliable information about the environment and vehicle dynamic states is required. A predictive algorithm that can interactively diagnose longitudinal environment and vehicle acceleration information is proposed in this paper to evaluate the reliability of sensors. To design the diagnosis algorithm, a longitudinal kinematic model is used based on a sliding mode observer. The reliability of the fault diagnosis algorithm can be ensured because the sliding mode observer utilized can reconstruct the relative acceleration despite faulty signals in the longitudinal environment information. Actual data based performance evaluations are conducted with various fault conditions for a reasonable performance evaluation of the predictive fault diagnosis algorithm presented in this paper. The evaluation results show that the proposed diagnosis algorithm can reasonably diagnose the faults in the longitudinal environment and acceleration information for all fault conditions.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.103-109
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• 2012

Digital speedometer which is supposed to provide the basic data for analyzing human factors of drivers has a limitation for human behavior studies of drivers, because it records limited driving information including GPS velocities. Besides, Black Box, which is currently being actively commercialized in the market, records mostly vehicles' risky patterns rather than drivers' behaviors. As a result, it also shows a limit to analyze dangerous driving patterns. This study performed a risky driving study for human factor analysis. This study conducted before and after comparisons for real time warning study using a risky driving judgment device. The analysis was conducted based on Longitudinal acceleration, Lateral acceleration, and Yaw rate of vehicles.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.11-16
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• 2019

This paper suggests an algorithm for detecting fault of longitudinal controller in autonomous vehicles. Guaranteeing safety in fault situation is essential because electronic devices in vehicle are dependent each other. Several methods like alarm to driver, ceding control to driver, and emergency stop are considered to cope with fault. This research investigates the fault monitoring process in fail-safe system, for controller which is responsible for accelerating and decelerating control in vehicle. Residual is computed using desired acceleration control command and actual acceleration, and detection of its abnormal increase leads to the decision that system has fault. Before computing residual for controller, health monitoring process of acceleration signal is performed using hardware and analytic redundancy. In fault monitoring process for controller, a process model which is fitted using driving data is considered to improve the performance. This algorithm is simulated via MATLAB tool to verify performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.73-82
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• 2022

Driver acceptance of autonomous driving is very important. The autonomous driving longitudinal controller, which is one of the factors affecting acceptability, consists of a high-level controller and a low-level controller. The host controller decides the cruise control and the space control according to the situation and creates the required target speed. The sub-controller performs control by creating an acceleration signal to follow the target speed. In this paper, we propose an algorithm to improve the inter-vehicle distance fluctuations that occur in the cruise control and space control switching problems in the host controller. The proposed method is to add an approach algorithm to the cruise control at the time of switching from cruise control to space control so that it is switched to space control at the correct switching distance. Through this, the error was improved from 12m error to 4m, and actual vehicle verification was performed.

• Proceedings of the KSR Conference
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• 2001.10a
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• pp.500-507
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• 2001

In this study, Interaction among each element was construed by the unit of new stiffness matrix to analyze the finite element about Japanese precast concrete slab track and improved slab track. Dynamic analysis which is assumed a static analysis and a trainload on the transverse and the longitudinal load of the train into a series periodic function was performed by using the common program. And then, the difference of the movement between an improved section and an existing structure type was realized. Longitudinal static analysis indicated that the stress of the improved section is smaller than that of the protrusion of the existing slab track. And static and dynamic analysis on transverse load showed a little decrease of the displacement on new slab track. But the dynamic analysis result showed that new track system was considerably decreased by 30% compared with the existing Japanese slab track.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.39-52
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• 2021

This paper presents a longitudinal acceleration controller that can be applied to real vehicles (nonlinear and time-varing systems) with only a simple experiment regardless of the type of vehicle and the control interface structure. The controller consists of a feedforward term for fast response, a zero-throttle acceleration compensation term, and a feedback term (P gain) to compensate for errors in the feedforward term, and another feedback term (I gain) to respond to disturbances such as slope. In order to easily apply it to real vehicles, there are only two tuning parameters, feedforward terms of throttle and brake control. And the remaining parameters can be calculated immediately when the two parameters are decided. The tuning procedure is also unified so that it can be quickly and easily applied to various vehicles. The performance of the controller was evaluated using MATLAB/Simulink and Truksim's European Ben model. In addition, the controller was successfully implemented to 3 medium-sized vehicle (HMC Solati), which is composed of different control interface characteristic. Vehicle driving performance was evaluated on the test track and on the urban roads in Siheung and Seoul.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.12
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• pp.2298-2305
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• 1992

To obtain the convenient solution of the multibody dynamic systems composed of flexible beams, linear finite element technique is adopted and the nodal coordinates are interpolated in the global inertia frame. Mass matrix becomes an extremely simple constant matrix and the force vector also becomes extremely simple because Coriolis acceleration and centrifugal force are not required. And the elastic force is also simply computed from the moving frame attached to the material. To solve the global differential algebraic euation. an ODE technique is adopted after Lagrange multiplier is computed by the accelerated iterative technique, and the time demanding procedures such as Newton-Raphson iterations and decomposition of the big matrix are not required. The accuracy of the present solution is checked by a well-known example problem.