• Title/Summary/Keyword: Road modeling

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STUDY ON RIDE QUALITY OF A HEAVY-DUTY OFF-ROAD VEHICLE WITH A NONLINEAR HYDROPNEUMATIC SPRING

  • SUN T.;YU F.
    • International Journal of Automotive Technology
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    • v.6 no.5
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    • pp.483-489
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    • 2005
  • Based on a two-degree of freedom vehicle model, this paper investigates ride comfort for a heavy off-road vehicle mounted a nonlinear hydropneumatic spring, which is influenced by nonlinear stiffness and damping characteristics of the hydropneumatic spring. Especially, the damping force is derived by applying H. Blasius formula in modeling process according to the real physical structure of the hydropneumatic spring, and the established model of nonlinear stiffness characteristics have been validated by experiments. Furthermore, the effects of parameter variations of the hydropneumatic spring, such as initial charge pressure and damping coefficient, on body acceleration, suspension deflection and dynamic tire deflection are also investigated.

Shared Spatio-temporal Attention Convolution Optimization Network for Traffic Prediction

  • Pengcheng, Li;Changjiu, Ke;Hongyu, Tu;Houbing, Zhang;Xu, Zhang
    • Journal of Information Processing Systems
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    • v.19 no.1
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    • pp.130-138
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    • 2023
  • The traffic flow in an urban area is affected by the date, weather, and regional traffic flow. The existing methods are weak to model the dynamic road network features, which results in inadequate long-term prediction performance. To solve the problems regarding insufficient capacity for dynamic modeling of road network structures and insufficient mining of dynamic spatio-temporal features. In this study, we propose a novel traffic flow prediction framework called shared spatio-temporal attention convolution optimization network (SSTACON). The shared spatio-temporal attention convolution layer shares a spatio-temporal attention structure, that is designed to extract dynamic spatio-temporal features from historical traffic conditions. Subsequently, the graph optimization module is used to model the dynamic road network structure. The experimental evaluation conducted on two datasets shows that the proposed method outperforms state-of-the-art methods at all time intervals.

Empirical Closed Loop Modeling of a Suspension System Using Neural Network (신경회로망을 응용한 현가장치의 폐회로 시스템 규명)

  • Kim, I.Y.;Chong, K.T.;Hong, D.P.
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.7
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    • pp.29-38
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    • 1997
  • A closed-loop system modeling of an active/semiactive suspension system has been accomplished through an artificial neural network. A 7DOF full model as a system's equation of motion has been derived and an output feedback linear quadratic regulator has been designed for control purpose. A training set of a sample data has been obtained through a computer simulation. A 7DOF full model with LQR controller simulated under several road conditions such as sinusoidal bumps and rectangular bumps. A general multilayer perceptron neural network is used for dynamic modeling and target outputs are fedback to the a layer. A backpropagation method is used as a training algorithm. Model validation of new dataset have been shown through computer simulations.

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An Emphirical Closed Loop Modeling of a Suspension System using a Neural Networks (신경회로망을 이용한 폐회로 현가장치의 시스템 모델링)

  • 김일영;정길도;노태수;홍동표
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.384-388
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    • 1996
  • The closed-loop system modeling of an Active/semiactive suspension system has been accomplished through an artificial neural Networks. The 7DOF full model as the system equation of motion has been derived and the output feedback linear quadratic regulator has been designed for the control purpose. For the neural networks training set of a sample data has been obtained through the computer simulation. A 7DOF full model with LQR controller simulated under the several road conditions such as sinusoidal bumps and the rectangular bumps. A general multilayer perceptron neural network is used for the dynamic modeling and the target outputs are feedback to the input layer. The Backpropagation method is used as the training algorithm. The modeling of system and the model validation have been shown through computer simulations.

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Analysis Transportation Network Using Traditional Four-step Transportation Modeling : A Case Study of Mandalay City, Myanmar (전통적인 4단계 교통수요 예측 모형을 활용한 교통망 분석 - 미얀마 만달레이시 중심으로)

  • Yoon, Byoung-Jo;WUT YEE LWIN;Lee, Sun-min
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2023.11a
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    • pp.259-260
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    • 2023
  • The rapid urbanization and modernization observed in countries like Myanmar have led to significant concerns regarding traffic congestion, especially in urban areas. This study focuses on the analysis and revitalization of urban transport in selected areas of Myanmar. The core of urban transportation planning lies in travel forecasting, which employs models to predict future traffic patterns and guide decisions related to road capacity, transit services, and land use policies. Travel demand modeling involves a series of mathematical models that simulate traveler behavior and decision-making within a transportation system, including highways, transit options, and policies. The paper offers an overview of the traditional four-step transportation modeling system, utilizing a simplified transport network in the context of Mandalay City, Myanmar.

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A case study of digital twin construction based on geospatial building information modeling (GeoBIM) - Focusing on the case of Jaeamcheon-gul and Jeonggusu-gul in Jeju Island - (지하공간건설정보모델링(GeoBIM) 기반의 디지털 트윈 구축사례에 관한 연구 - 제주도 재암천굴, 정구수굴 사례를 중심으로 -)

  • Lee, Jong-Hyun;An, Joon-Sang;Choi, Jae-Woong;Baek, Yong
    • Journal of KIBIM
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    • v.11 no.4
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    • pp.20-30
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    • 2021
  • In the era of the 4th industrial revolution, smart construction is actively researched, in the domestic construction field, and one of the key elements in this field is Building Information Modeling(BIM). In Korea, smart construction is being implemented through BIM-based digitization and intelligence. The geotechnical engineering field should also prepare for the introduction of BIM. In this study, the concept and application status of GeoBIM were identified, and the direction of future research was presented. This study is a part of the study "Establishment of GeoBIM-based Digital Twin Maintenance System" in the current "Technology Development for Establishment of Jeju Ground Collapse Response System for Safe Road Operation". The subject and scope of the study is continuous excavation at caves located under roads in Jeju Island, and initial research is being conducted on Jaeamcheon-gul and Jeonggusu-gul. This study aims to build a digital twin through individual data construction and integration processes such as cave shape modeling using laser scanners, 3D stratum modeling using borehole information and geophysical exploration data, and modeling of surrounding conditions using drones.

A Road Surface Temperature Prediction Modeling for Road Weather Information System (도로기상정보체계 활성화를 위한 노면온도예측 모형 개발)

  • Yang, Chung-Heon;Park, Mun-Su;Yun, Deok-Geun
    • Journal of Korean Society of Transportation
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    • v.29 no.2
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    • pp.123-131
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    • 2011
  • This study proposes a model for road surface temperature prediction on basis of the heat-energy balance equation between atmosphere and road surface. The overall model is consisted of two types of modules: 1) Canopy 1 is used to describe heat transfer between soil surface and atmosphere; and 2) Canopy 2 can reflect the characteristics of pavement type. Input data used in the model run is obtained from the Korea Meteorological For model validation, the observed and predicted surface temperature data are compared using data collected on MoonEui Bridge along CheongWon-Sangju Expressway, and the comparison is made on winter and other seasons separately. Analysis results show that average difference between two temperatures lies within ${\pm}2^{\circ}C$ which is considered as appropriate from a micrometeorology point of view. The model proposed in this paper can be adopted as a useful tool in practical applications for winter maintenance. This study being a fundamental research is anticipated to be a starting point for further development of robust surface road temperature prediction algorithms.

Characteristics and Severity of Side Right-Angle Collisions at Signalized Intersections (신호교차로의 측면직각 층돌사고 특성과 심각도)

  • Park, Jeong-Soon;Park, Gil-Soo;Kim, Tae-Young;Park, Byung-Ho
    • International Journal of Highway Engineering
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    • v.10 no.4
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    • pp.199-211
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    • 2008
  • This study deals with the side right-angle collisions of 4-legged signalized intersections in Cheongju. The goals are to analyze the characteristics of accidents and to find out the accident factors that affect severity using ordered probit model. In pursuing the above, the study uses the data of 580 side right-angle collisions occurred at the 181 intersections(2004-2005). The analyses show that more accidents were occurred in the nighttime and in going straight. The main cause was analyzed to be the red-light violation. Also, the main results of modeling are the following, First, the likelihood ratio index is 0.094 and t-ratio values that explain goodness of fit are significant. Second, minor road traffic volumes, minor road lanes, major road left-turn lanes, major road left-turn signal, major road yellow signal time, cross angle, major and minor road speed limits are significant factors affecting crash severities at signalized intersections.

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