• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.103-111
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• 2011

To evaluate highway safety countermeasures or identify high risk sites, the expected crashes for a site (or segment) have been estimated using the panel crash data. Past studies show that two different methods can be employed to estimate the expected crashes: observed crash based method and empirical Bayes (EB) method. This study conducts a simulation study to analyze how the estimation errors of the two estimates are affected by the different structures of the panel crash data and the presence of the change in safety over time. The results disclose that the estimation errors of the observed crash based estimates (i.e. the mean observed crash and comparative parallel estimate) are always greater than those of the EB estimates regardless of the structure of the panel crash data and the presence of the change in safety over time. Thus, it is highly recommended that the EB method be used in the study of traffic safety to obtain more reliable estimates for the expected crashes. In addition, this study corroborates that the estimation errors of the two estimates decrease as the analysis periods increase if safety does not change over time. Hence, it is also recommended that the 1-year analysis period used for identifying high risk sites in Korea be extended to produce more efficient estimates of the time-constant expected crashes.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.119-126
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• 2018

PURPOSES : The purpose of this study is to develop a crash prediction model at signalized intersections, which can capture the randomness and uncertainty of traffic accident forecasting in order to provide more precise results. METHODS : The authors propose a random parameter (RP) approach to overcome the limitation of the Count model that cannot consider the heterogeneity of the assigned locations or road sections. For the model's development, 55 intersections located in the Daejeon metropolitan area were selected as the scope of the study, and panel data such as the number of crashes, traffic volume, and intersection geometry at each intersection were collected for the analysis. RESULTS : Based on the results of the RP negative binomial crash prediction model developed in this study, it was found that the independent variables such as the log form of average annual traffic volume, presence or absence of left-turn lanes on major roads, presence or absence of right-turn lanes on minor roads, and the number of crosswalks were statistically significant random parameters, and this showed that the variables have a heterogeneous influence on individual intersections. CONCLUSIONS : It was found that the RP model had a better fit to the data than the fixed parameters (FP) model since the RP model reflects the heterogeneity of the individual observations and captures the inconsistent and biased effects.

• Journal of Distribution Science
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• v.20 no.12
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• pp.81-87
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• 2022

Purpose: This study aims to explore the relationship between stock liquidity and skewness risk-tail risk (stock price crash risk) in an emerging market, in which problems on liquidity are more severe than in developed markets. Research design, data, and methodology: Based on the Thai market stock exchange over the period of 2000 to 2019, our sample include 13,462 firm-period observations. We employ a panel regression models regarding to five liquidity measures. These five liquidity measures cover three dimensions of liquidity namely the volume-based, price-based, and transaction cost-based measures for the liquidity-tail risk relationship. Results: We find a positively significant relationship between stock liquidity and tail risk in all cases. The finding here shows that the higher the stock liquidity, the larger the tail risk is. Conclusion: As the prior studies show inconclusive effect of stock liquidity on stock price crash risk, we demonstrate that mixed results found in prior studies are probably driven from the type of liquidity measure. The stock liquidity-tail risk association is present in the Stock Exchange of Thailand. The results remain the same regardless of the definition of tail risk and liquidity factors. An endogeneity issue is addressed by employing the two-stage least squares regression.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.710-713
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• 2005

Many impact or drop test researches of home appliances are published, but those of toys cannot be found easily. External impacts are the primary causes of fracture of toys. For impact proof design, the finished product should pass an impact test after molding design. There are several international toy safety standards or requirements such as US CPSC(Consumer Product Safety Commission), ASTM F963-96a, EN71 and so on. The puppy robot which patrols around the house, namely, the watchdog was selected to investigate toy safety because it has considerable weight and outer panels are made of plastics. First the model of watchdog robot was obtained by 3 dimensional scan. Surface data can be generated from 3D polygon data of the watchdog. A reliable drop simulation method for the watchdog was established using Pam-crash program according to Korean toy safety standards. When there is a low impact allowance value, the molding design should be reinforced or changed. It was found that the maximum impact stress reaches the ultimate stress of panel material.