• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1205-1210
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• 2001

This paper describes a methodology using neural network to compensate the nonlinear error of deriving speed for electric differential system included in electric vehicle. An electric differential system which drives each of the left and right wheels of the electric vehicle independently. The electric vehicle driven by induction motor has the nonlinear speed error which depends on a steering angle and speed command. When a vehicle drives along a curved road lane, the speed unblance of inner and outer wheels makes vehicles vibration and speed reduction. To compensate for the speed error, we collected the speed data of the inner wheel and outer wheel in various speed and the steering angle data by using an manufactured electric vehicle and the real system. According to the analysis of the acquisited data, we designed the differential speed control system based on a speed error compensator using neural network.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.6
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• pp.120-127
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• 2007

This paper describes the development of a nonlinear observer for four wheel steer (4WS) vehicle. An observer is designed to estimate the vehicle variables difficult to measure directly. A brake yaw motion controller (BYMC), which uses a PID control method, is also proposed for controlling the brake pressure of the rear and inner wheels to enhance lateral stability. It induces the yaw rate to track the reference yaw rate, and it reduces a slip angle on a slippery road. The braking and steering performances of the anti-lock brake system (ABS) and BYMC are evaluated for various driving conditions, including straight, J-turn, and sinusoidal maneuvers. The simulation results show that developed ABS reduces the stopping distance and increases the longitudinal stability. The observer estimates velocity, slip angle, and yaw rate of 4WS vehicle very well. The results also reveal that the BYMC improves vehicle lateral stability and controllability when various steering inputs are applied.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.550-557
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• 1999

This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.2 s.179
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• pp.104-112
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• 2006

The influence of tire belt angle on the Plysteer Residual Aligning Torque(PRAT) and the cornering stiffness by the FEM has been studied. The PRAT is a performance factor of the tire about vehicle pull, and the cornering stiffness has relation to vehicle steering response of outdoor test. To validate FE model for analysis, simulation data for both the static stiffness(vertical, lateral) and the PRAT have been compared with the experimental data. In addition to the characteristics of the PRAT and the cornering stiffness due to the tire belt angle, rolling and cornering contact characteristics have been studied. The tendency of the PRAT and the cornering stiffness due to the belt angle can be used as a guide line for the tire design in relation to vehicle pull and vehicle steering response.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.5
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• pp.197-205
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• 2018

In this research, tricycle vehicle simulation based on multi-body environment has been introduced. Mathematical model of tricycle vehicle was developed. In this research the left and right wheel speed are calculated based on the rear steering angle and velocity. The kinematic model for the three - wheel drive system was completed and the results were analyzed using the actual vehicle drawings. Through simulink vehicle performance on linear and rotation movement were simulated. Using the mathematical model the control system can be applied directly to the tricycle vehicle. The simulation result shows that the proposed vehicle model is successfully represent the movement characteristics of the real vehicle. This model assists the vehicle developer to create the controller and understand the vehicle during the development process.

• Journal of the Ergonomics Society of Korea
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• v.30 no.2
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• pp.285-290
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• 2011

Due to the ageing-related degradation in physical and cognitive abilities, the elderly have difficulty in car driving and this is related to the high rate of car accidents among them. This study investigated the kinematic characteristics of old drivers' steering in right turning at intersections by comparing with young drivers. Thirteen old(60~70) and thirteen young(20~30) drivers who participated in the experiment turned their cars right side at intersections in a driving simulator. As results, the completion time of right turning at intersection of old drivers was larger than that of young drivers. The speeds of vehicle at the beginning and ending point of the right turning area of old drivers were smaller than those of young drivers, and also the steering angle at the ending point of the turning area of the former was smaller than that of the latter. The normalized jerk of old driver's steering was significantly larger than that of young drivers. These results indicate that old drivers modify their steering movement repeatedly and take the driving strategy of avoiding risks due to their reduced physical capabilities.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.4
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• pp.135-142
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• 2008

Hydraulic power steering system has been adopted in seniority passenger and commercial vehicle system for an easy maneuverability and a smoother ride. In this study, hydraulic power steering system analysis model which includes hydraulics and mechanical sub-systems was developed using commercial software, AMESim in order to predict characteristics for various steering components. Each component which constructs system was modeled and verified by experimentally obtained characteristics curves of each components. The parameter sensitivity analysis such as valve opening area, torsional stiffness of torsion bar for system design are carried out by the analysis and experimental method. The predicted results by the development model were a good agreement with experimentally obtained results. The sensitivity investigation results rotary torque when changing an input shaft edge width, was most sensitive, to change in angle and slot width and supply flow of input shaft edge is not a lot sensitively.

• Journal of the Ergonomics Society of Korea
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• v.28 no.2
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• pp.9-16
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• 2009

The aim of this study was to evaluate the effects of the driving performance and workload according to changing driving environment and types of steering wheel. Twelve drivers who participated in this study consisted of two groups; six Japanese as the left-lane drivers who was accustomed to driving on left-hand side of the road, and six Europeans, Americans, and Korean as the right-lane drivers who was accustomed to driving on right-hand side of the road. They were asked to operate a driving simulator while using two different types of steering wheel (for the left-hand side driving and the right-hand side driving). During the experiment, a range of data were measured including driving performance, mental workload, and eye movements which were recorded in order to identify the amount of time looking towards the in-vehicle route guidance. Results indicated that the use of the steering wheel by parallel moving led to increase high attentional demand and worse glance behavior to traffic signs for the left-lane drivers. In the case of the right-lane drivers, the effects by changing driving direction were more effective than the types of steering wheel due to their habit or traits.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.283-290
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• 2007

A bi-modal tram has been developed to offer an advanced transportation service compared with existing vehicles. The All-Wheel-Steering system is applied to the bi-modal tram to satisfy the required steering performance because the bi-modal tram has extended length and articulated mechanism. An ECU for the steering system is essential to steer wheels on 2nd and 3rd axles by the specific AWS algorithm with the prescribed driving condition. The Hardware-In-the-Loop Simulation(HILS) system is planned for the purpose of evaluating the steering system of the bi-modal tram. There are kinematic links with the hydraulic actuator to steer wheels on each 2nd and 3rd axles and also same steering mechanism as the actual vehicle is in the HILS system. Controlling the movement of hydraulic actuator which reflects the lateral steering reaction force on each wheel is the key to realize the HILS system, but the reaction force is continuously changed according to various driving conditions. Therefore, the simulation through the multi-body dynamics model is used to obtain the required forces.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.92-97
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• 2022

In this paper, as a research on autonomous steering for agriculture, a sensor module for furrow recognition was developed through a low-cost distance sensor combination. The developed sensor module was applied to the vehicle, and when driving in a furrow curve, the autonomous steering success rate was 100% at a curvature of 20 m or more, and 70% at a curvature of 15 m or less. The self-steering success rate according to the ground condition showed a 100% success rate regardless of soil, weeds, or mulching film.