• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.95-101
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• 2011

This study proposes the accident estimation model developed based on the time-series cross-sectional data at 50 intersections in Cheongju. The data were collected repeatedly and accumulated from 2004 to 2007. This study focused on deriving the optimal among the various models including TSCSREG(Time Series Cross Section Regression). Four different models utilizing various elements affecting accidents were developed. Through a statistical test, it was found that the t values of independent variables of the fixed effect models were less than those of the random effect models. Two variables were then found to be positive to the accidents: the number of crosswalks at an intersection and the number of intersections.

• Journal of the Korean Society of Safety
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• v.27 no.3
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• pp.141-146
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• 2012

This study deals with the accident model using panel data which are composed of time series data of 2005 through 2007 and cross sectional data of link sections in Cheongju. Panel data are repeatedly collected over time from the same sample. The purpose of the study is to develop the traffic accident model using the above panel data. In pursuing the above, this study gives particular attentions to deriving the optimal models among various models including TSCSREG (Time Series Cross Section Regression). The main results are as follows. First, 8 panel data models which explained the various effects of accidents were developed. Second, $R^2$ values of fixed effect models were analyzed to be higher than those of random effect models. Finally, such the variables as the sum of the number of crosswalk on intersections and sum of the number of intersections were analyzed to be positive to the accidents.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.49-57
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• 2011

This study deals with the traffic accident of arterial link sections in the case of Cheongju. The purpose of the study is to develop the traffic accident model by the function of arterial links. In pursuing the above, this study gives particular attentions to developing the appropriate models using the accident data of main and minor arterial roads divided by 472 small link sections. The main results analyzed are as follows. First, as the t test on the accident characteristics of main and minor arterial roads shows that there are differences in the number of accident and EPDO(equivalent property damage only) between two roads, the development of models by function is analyzed to be appropriate. Second, it is analyzed that ZINB models are all statistically suitable to the number of accident and EPDO of main arterial roads. Third, the analysis shows that EPDOs of minor arterial roads fit to ZINB, and the number of the accident fit to ZIP model. Finally, the common variables of main arterial roads are evaluated to be the traffic volume and the number of inflection point, and those of minor be the average grade.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.161-170
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• 2008

This study deals with the accident models by vehicle type. The goal is to develop the accident models by vehicle type using the data of 143 4-legged signalized intersections in Cheongju. In pursuing the above, this study gives the particular attentions to explaining the relationships between the values of EPDO(equivalent property damage only) and the traffic and geometric elements. The main results analyzed are the followings. First, 6 negative binomial models are developed, which are all significant at the 90% confidence level. Second, the values of ${\rho}^2$ by vehicle type are 0.14307(auto), 0.35556(large van), 0.21684(small van), 0.205152(motocycle), 0.32338(light-duty truck) and 0.29046(heavy-duty truck), that are all analyzed to be statistically significant. Finally, the common variable included in all models is ADT(average daily traffic), and the specific variable(SV) of auto is analyzed to be the sum of lane width of main road, SV of large van is the average yellow time, and SV of small van is the difference in the number of lane between main and minor road.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.12
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• pp.377-401
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• 1999

This study is focused on the privity of the contract of carriage of goods by sea, so to speak, privity between B/L holder and carrier by transfer of bill of lading, privity by attornment to delivery order and conflict between bills of lading and charterparty terms. Under a CIF contract, possession of the bill of lading is equivalent to possession of the goods, and delivery of the bill of lading to the buyer or to a third party may be effective to pass the property in the goods to such person. The bill of lading is a document of title enabling the holder to obtain credit from banks before the arrival of the goods, for the transfer of the bill of lading can operate as a pledge of the goods themselves. In addition, it is by virtue of the bill of lading that the buyer or his assignee can obtain redress against the carrier for any breach of its terms and of the contract of carriage that it evidences. In other words the bill of lading creates a privity between its holder and the carrier as if the contract was made between them. The use of delivery orders in overseas sales is commen where bulk cargoes are split into more parcels than there are bills of lading, and this practice gives rise to considerable difficulties. For example, where the holder of a bill of lading transferred one of the delivery orders to the buyer who presented it to the carrier and paid the freight of the goods to which the order related, it was held that there was a contract between the buyer and the carrier under which the carrier could be made liable in repect of damage to the goods. The contract was on the same terms as that evidenced by, or contained in, the bill of lading, which was expressly incorporated by reference in the delivery order. If the transferee of the delivery order presents it and claims the goods, he may also be taken to have offered to enter into an implied contract incorporating some of the terms of the contract of carriage ; and he will, on the carrier's acceptance of that offer, not only acquire rights, but also incur liabilities under that contract. Where the terms of the charterparties conflict with those of the bills of lading, it is interpreted as below. First, goods may be shipped in a ship chartered by the shipper directly from the shipowner. In that case any bill of lading issued by the shipowner operates, as between shipowner and charterer, as a mere receipt. But if the bill of lading has been indorsed to a third party, between that third party and carrier, the bill of lading will normally be the contract of carriage. Secondly, goods may be shipped by a seller on a ship chartered by the buyer for taking delivery of the goods under the contract of sale. If the seller takes a bill of lading in his own name and to his own order, the terms of that bill of lading would govern the contractual relations between seller and carrier. Thirdly, a ship may be chartered by her owner to a charterer and then subchartered by the chaterer to a shipper, to whom a bill of lading may later be issued by the shipowner. In such a case, the bill of lading is regarded as evidencing a contract of carriage between the shipowner and cargo-owners.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.63-72
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• 2007

The purpose of this study is to develop a traffic characteristic analysis, a correlation analysis with the variables of traffic characteristics, and accident estimation models while recognizing the seriousness of the traffic accidents. The analyses deal with the 181 4-legged signalized intersections that accounted for 1,183 out of 3,115 accidents in Cheongju in 2004. After measuring ADT, intersection area, average lane width, elevation, and other items as independent variables and the number of traffic accidents, the traffic accident rate (accidents per million entering vehicles) and equivalent property damage only (EPDO) figures as dependent variables which are estimated as influencing signalized intersection accidents, the estimation models are developed using correlation analysis and multiple regression analysis. In the analysis of the number of traffic accidents, the model indicates an $R^2$ of 0.612, and five independent variables are taken as significant factors. In the analysis of traffic accident rates, the model indicates an $R^2$ of 0.304 and five significant factors, including intersection area and ADT. Also, for the analysis or the EPDO numbers, which coincides with understanding the seriousness of the traffic accidents and the traffic characteristic analysis, the model indicates an $R^2$ of 0.559, and four independent variables (ADT, main street average lane width, elevation, and speed limit) as significant factors.