• Journal of Mechanical Science and Technology
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• v.17 no.7
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• pp.958-965
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• 2003

Structural integrity of either a passenger car or a light truck is one of the basic requirements for a full vehicle engineering and development program. The results of the vehicle product performance are measured in terms of ride and handling, durability, noise/vibration/harshness (NVH), crashworthiness and occupant safety. The level of performance of a vehicle directly affects the marketability, profitability and, most importantly, the future of the automobile manufacturer In this study, we used the virtual proving ground (VPG) approach for obtaining the dynamic characteristics. The VPG approach uses a nonlinear dynamic finite element code (LS-DYNA3D) which expands the application boundary outside the classic linear static assumptions. The VPG approach also uses realistic boundary conditions of tire/road surface interactions. To verify the predicted dynamic results, a single lane change test has been performed. The prediction results were compared with the experimental results, and the feasibility of the integrated CAE analysis methodology was verified.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.91-102
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• 2009

A traffic accident prediction model developed using various design variables(road design variables, geometric variables, and traffic environmental variables) is one of the most important factors to safety design evaluation system for roads. However, statistical accident models have a crucial problem not applicable for all intersections. To make up this problem, this study developed AMFs(Accident Modification Factors) through statistical modeling methods, historical accident databases, judgment from traffic experts, and literature review by considering design variable's characteristics, traffic accident rates, and traffic accident frequency. AMFs developed in this study include exclusive left-turn lane, exclusive right-turn lane, sight distance, and intersection angle. Predictabilities of the developed AMFs and the existing accident prediction models are compared with real accident historical data. The results showed that performances of the developed AMFs are superior to the existing statistical accident prediction models. These findings show that AMFs should be considered as a important process to develop safety design evaluation algorithms. Additionally, AMFs could be used as an index that can judge the impact of corresponding design variables on accidents in rural intersections.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.207-215
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• 2009

Generally, traffic accidents can be influenced by variables driving conditions including geometric, roadside design, and traffic conditions. Under the circumstance, homogeneous roadway segments were firstly identified using typical geometric variables obtained from field data collections in this study. These field data collections were conducted at highways located in several areas having various regional conditions for examples, outside metropolitan city; level and rolling rural areas. Due to many zero cells in crash database, a Zero Inflated Poisson model was used to develop crash prediction model to overestimated results in this study. It was found that EXPO, radius, grade, guardrail, mountainous terrain, crosswalk and bus-stop have statistically significant influence on vehicle to vehicle crashes at rural multi-lane roadway segments.

• Journal of the Korean Institute of Navigation
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• v.1 no.1
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• pp.1-16
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• 1977

The aspects of Omega phase prediction are briefly reviewed, and Swanson's Model and Pierce's Model are presented. The equations for the Omega phase prediction and the most probable coefficients of the propagating equations are derived on the base of Pierce's Model by the least square method. The coefficients are calculated from the data which are the phase differences between the pairs of the Station A (Aldra, Norway), C(Haiku, Hawaii), and D(La Mour, North Dakota) observed at Busan Harbor of the South Coast of Korea in June and September, 1976. It is clearly shown that the standard deviations of the observed lane values at Busan Harbor are as followed: 1. June, 1976. Pair (A-C) : 0.1446 Pair (C-D) : 0.2598 2.September, 1976. Pair (A-D) : 0.3958 Pafr (C-D) : 0.3278 As a conclusion of the above investigation, it is shown that the Omega phase velocity can be predicted by the method, proposed in this paper, of analyzing the diurnal and seasonal variations of the Omege phase velocity except SID, PCD and AZD. If more observed data are employed, more exact Omega phase velocity is expected to be obtained.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.3
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• pp.236-242
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• 2002

This paper presents some advanced and supplemental methods to enhance the accuracy In case of calculating geometric divergence attenuation, attenuation by multiple screening structures, ground attenuation at unflat surfaces of sound during propagation outdoors by the methods specified in ISO 9613-2. Moreover, a calculation method for considering short-term wind effect, specified in ASJ Model-1998, is also introduced. To verity the accuracy of adopted methods, we have carried out highway traffic noise prediction and measurement at tile twelve locations appearing representative road shapes and structures, such as flat, retained cut, elevated, barrier-constructed roads. From the results, we have confirmed the predicted results show good correspondence with the measured at direct, diffracted and reflected sound fields within 30 m from the center of near side lane.

• Journal of Environmental Impact Assessment
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• v.21 no.4
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• pp.567-572
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• 2012

This paper suggests the set-up plan of the assessment scope in road noise considering road characteristics with the prediction model of road noise. The RLS90 prediction model with some assumptions is used to establish the assessment scope of road noise. The main contents of the applied assumptions are smooth drive of cars, flat region, location of all noise sources in one lane, drive in design speed, and set-up of assessment scope according to traffic volume and car speed. The information of traffic volume to predict road noise is obtained by the distribution of small cars and full-sized cars in road. In this study, the total traffic volume in road is computed by adding the number of small cars to the conversion number of small cars, which means the number of small cars making the same noise as one full-sized car. The prediction result of road noise with the influence factor of traffic volume, car speed, distance between road and receiver is presented. The resultant assessment scope of road noise is obtained by combining road noise prediction data with the set-up standard of road noise assessment scope.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1280-1286
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• 2001

This paper presents some advanced and supplemental methods to enhance the accuracy in case of calculating geometric divergence attenuation, attenuation by multiple screening structures, ground attenuation at unflat surfaces of sound during propagation outdoors by the methods specified in ISO 9613-2. Moreover, a calculation method for considering short-term wind effect, specified in ASJ Model-1998, is also introduced. To verify the accuracy of adopted methods, we have carried out highway traffic noise prediction and measurement at the twelve locations appearing representative road shapes and structures, such as flat, retained cut, elevated, barrier-constructed roads. From the results, we have confirmed the predicted results show good correspondence with the measured at direct, diffracted and reflected sound fields within 30m from the center of near side lane.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.131-139
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• 2002

This study introduces a developed artificial neural networks(ANN) model as a more efficient and reliable prediction model in operating speed Prediction with the 85th percentile horizontal curve of two-way rural highway in the aspect of evaluating highway design consistency. On the assumption that the speed is decided by highway geometry features, total 30 survey sites were selected. Data include currie radius, curve length, intersection angle, sight distance, lane width, and lane of those sites and were used as input layer data of the ANN. The optimized model structure was drawn by number of unit of hidden layer, learning coefficient, momentum coefficient, and change in learning frequency in multi-layer a ANN model. To verify learning Performance of ANN, 30 survey sites were selected while data in obtained from the 20 cites were used as learning data and those from the remaining 10 sites were used as predictive data. As a result of statistical verification, the model D of 4 types of ANN was evaluated as the most similar model to the actual operating speed value: R2 was 85% and %RMSE was 0.0204.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.73-82
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• 2011

Recent advancement in traffic surveillance systems has allowed the researchers to obtain more detailed vehicular movement such as individual vehicle trajectory data. Understanding the characteristics of interactions between leading and following vehicles in the traffic flow stream is a backbone for designing and evaluating more sophisticated traffic and vehicle control strategies. This study proposes a methodology for estimating rear-end crash potential, as a probabilistic measure, in real-time based on the analysis of vehicular movements. The methodology presented in this study consists of three components. The first predicts vehicle position and speed every second using a Kalman filtering technique. The second estimates the probability for the vehicle's trajectory to belong to either 'changing lane' or 'going straight'. A binary logistic regression (BLR) is used to model the lane-changing decision of the subject vehicle. The other component calculates crash probability by employing an exponential decay function that uses time-to-collision (TTC) between the subject vehicle and the front vehicle. The result of this study is expected to be adapted in developing traffic control and information systems, in particular, for crash prevention.

• Journal of the Korean Society of Safety
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• v.17 no.3
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• pp.36-42
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• 2002

Structural integrity of either a passenger car or a light truck is one of the basic requirements for a full vehicle engineering and development program. The results of the vehicle product performance are measured in terms of ride and handling, durability, noise/vibration/harshness(NVH), crashworthiness and occupant safety. The level of performance of a vehicle directly affects the marketability, profitability and, most importantly, the future of the automobile manufacturer. In this study, we used the virtual proving ground(VPG) approach for obtaining the dynamic characteristics. VPG approach uses a nonlinear, dynamic, finite element code(LS-DYNA3D) which expands the application boundary outside the classic linear, antic assumptions. VPG approach also uses realistic boundary conditions of tire/road surface interactions. To verify the predicted dynamic results, a single lane change test has been performed. The prediction results were compared with the experimental test results, and the feasibility of the integrated CAE analysis methodology was verified.