• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.57-70
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• 2012

Variable speed limit(VSL) is a useful speed management tool for alleviating traffic congestion and enhancing traffic safety. The purpose of this study is to identify promising freeway segments for safety enhancement through VSL operations. An ordered probit model was adopted to capture factors affecting freeway crash severity that can be used to support decision making for selecting the promising segments. Pseudo elasticity and marginal effects, which are outcomes of the ordered probit analysis, were used to determine priority of promising segments for traffic safety. The results of this study would be useful in installing VSL systems and developing traffic control and operations strategies in practice.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.35-44
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• 2006

Acceleration and deceleration curves have been used for design purposes worldwide. The curve in design level has been regarded as an single deterministic curve to be used for design of climb lanes. It should be noted that the curve was originally made using ideal driving truck and that the curve is applied during design based on the assumption of no difference between ideal and real driving conditions. However. observations show that aged vehicles and lazy behavioring drivers nay make lower performance of vehicles than the ideal performance. The present paper provides the results of truck speeds at climbing lanes then probabilistic variation of acceleration and deceleration corves. For these purposes. a study about identification of vehicle makers, and weights for trucks at freeway toll gates and then observation of vehicle-following speed were performed. The 85%ile results obtained were compared with the deterministic performance curves of 180, 200, and 220 Ib/hp. It was identified that the performance of 85%ile results obtained from vehicle-following-speed observations were lower than one from deterministic performance curves. From these results, it may be concluded that at the beginning Point of climbing lanes additional $16.19{\sim}67.94m$ is necessary and that at the end point of climbing lanes $53.12{\sim}103.24m$ of extension is necessary.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.423-433
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• 2017

During recent 5 years, it was recorded that 20% of total accident frequency and 30% of total number of death have been occurred due to drowsy driving. Drowsy driving accident is result from the loss of driving ability due to driver's accumulated fatigue. Continuous driving time can be measured as a surrogate variable to quantify the level of fatigue. The main purpose of this research is to investigate statistical correlation between the proportion of continuous driving vehicle (more than 2 hours) and the number of drowsy accidents. To carry this out, continuous driving time was measured using GPS route-guidance trajectory data. Also, accident frequency, traffic volume and segment length were collected to estimate safety performance function (SPF) for Jungbunearuk expressway in Korea. Through various types of estimated SPFs, statistical correlation was analyzed based on estimated statistical indices. This research can provide theoretical background for enforcement to regulate commercial vehicle driver's continuous driving time. In addition, throughout the trajectory data expansion, it is expected that strategy for anti-drowsy driving facilities installation can be established based on the suggested methodology.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.207-208
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• 2016

By according to increase the research for autonomous vehicle in automobile industries, the efficient of autonomous cargo truck instead of conventional driver cargo truck will be analyzed in logistics areas. The inland transportation has been serious problem such as traffic accident, traffic congestion in downtown, air pollution, noise and etc. even if it have a great effect to logistics industries. Especially there have to be improved its transportation schedule and sleepy driving in night which induced heavy accident in highway. In this study, the effectiveness of autonomous cargo truck will be analysed by considering the logistics cost including social effects.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.47-56
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• 2022

The safe driving reward system aims to reduce the loss of life and property by reducing the occurrence of accidents by motivating safe driving and encouraging active participation by providing direct reward to vehicle drivers who have performed safe driving. In the case of the existing digital tachograph, the goal is to limit dangerous driving by recording the driving status of the vehicle whereas the safe driving reward system is a support measure to increase the effect of accident prevention and induces safe driving with financial reward when safe driving is performed. In other words, in an area where accidents due to speeding are high, direct reward is provided to motivate safe driving to prevent traffic accidents when safe driving instructions such as speed compliance, maintaining distance between vehicles, and driving in designated lanes are performed. Since these safe operation data and reward histories must be managed transparently and safely, the reward evidences and histories were constructed using the closed blockchain Hyperledger Fabric. However, while transparency and safety are guaranteed in the blockchain system, low data processing speed is a problem. In this study, the sequential block generation speed was as low as 10 TPS(transaction per second), and as a result of applying the acceleration function a high-performance network of 1,000 TPS or more was implemented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.562-565
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• 2022

Recently, the increasing number of overloaded vehicles on the road poses a risk to traffic safety, such as falling objects, road damage, and chain collisions due to the abnormal weight distribution, and can cause great damage once an accident occurs. However, this irregular weight distribution is not possible to be recognized with the current weight measurement system for vehicles on roads. To address this limitation, we propose to build an object detection-based AI model to identify overloaded vehicles that cause such social problems. In addition, we present a simple yet effective method to construct an object detection model for the large-scale vehicle images. In particular, we utilize the large-scale of vehicle image sets provided by open AI-Hub, which include the overloaded vehicles from the CCTV, black box, and hand-held camera point of view. We inspected the specific features of sizes of vehicles and types of image sources, and pre-processed these images to train a deep learning-based object detection model. Finally, we demonstrated that the detection performance of the overloaded vehicle was improved by about 23% compared to the one using raw data. From the result, we believe that public big data can be utilized more efficiently and applied to the development of an object detection-based overloaded vehicle detection model.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.17-24
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• 2010

As various social problems occur due to increasing traffic accidents, the government has setup and executed strong safety policies. As a result, the number of traffic accidents and the death toll have been decreasing in recent years. However, the setup and execution of the various policies for reducing traffic accidents cost much, so it is necessary to evaluate the cost-effectiveness of each policy. In the present study, enforcement by means of an unmanned over-speed enforcement system, the enforcement effect of which was proven good compared to the cost required for traffic enforcement, is compared with enforcement by policemen. As a result of the comparison, the average speed was 82.66 km/h before the use of unmanned systems and policemen; the average speed with manned enforcement was 70.57 km/h; and the average speed with unmanned systems was 67.85 km/h. The speed limit violation rate was 65% before the use of unmanned systems and policemen; 32% with manned enforcement; and 15% with unmanned systems. Considering the kinds of vehicles, the average speed and violation rate were highest among private cars, then vans, and then trucks.. Considering lanes. The accident rate was estimated based on the above results, and the input cost-to-advantage was estimated. The annual cost-to-advantage was estimated by comparing the above estimated values with the conditions before the unmanned over-speed enforcement system. Subsequently, the enforcement by policemen showed a negative advantage of 76,130,590 won, and the enforcement by the unmanned system showed a positive advantage of 38,577,670 won.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.173-185
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• 2015

This study aims to investigate the characteristics and types of car accidents and establish a prediction model by analyzing 456 car accidents having occurred in the 11 tunnels in Busan, through statistical analysis techniques. The results of this study can be summarized as below. As a result of analyzing the characteristics of car accidents, it was found that 64.9% of all the car accidents took place in the tunnels between 08:00 and 18:00, which was higher than 45.8 to 46.1% of the car accidents in common roads. As a result of analyzing the types of car accidents, the car-to-car accident type was the majority, and the sole-car accident type in the tunnels was relatively high, compared to that in common roads. Besides, people at the age between 21 and 40 were most involved in car accidents, and in the vehicle type of the first party to car accidents, trucks showed a high proportion, and in the cloud cover, rainy days or cloudy days showed a high proportion unlike clear days. As a result of analyzing the principal components of car accident influence factors, it was found that the first principal components were road, tunnel structure and traffic flow-related factors, the second principal components lighting facility and road structure-related factors, the third principal factors stand-by and lighting facility-related factors, the fourth principal components human and time series-related factors, the fifth principal components human-related factors, the sixth principal components vehicle and traffic flow-related factors, and the seventh principal components meteorological factors. As a result of classifying car accident spots, there were 5 optimized groups classified, and as a result of analyzing each group based on Quantification Theory Type I, it was found that the first group showed low explanation power for the prediction model, while the fourth group showed a middle explanation power and the second, third and fifth groups showed high explanation power for the prediction model. Out of all the items(principal components) over 0.2(a weak correlation) in the partial correlation coefficient absolute value of the prediction model, this study analyzed variables including road environment variables. As a result, main examination items were summarized as proper traffic flow processing, cross-section composition(the width of a road), tunnel structure(the length of a tunnel), the lineal of a road, ventilation facilities and lighting facilities.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.121-133
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• 2017

Since the mid 1990s, policies have been actively promoted to improve safety and pedestrian environment around the school such as the improvement of School zone. However, the prevention of accidents was not effective because it did not extend to the school road where the main transportation route for children's commuting takes place. In addition, due to the rapid increase of automobiles, trunk road traffic in the peak time bypasses the back roads, which threatens children's safety and the environment by invading the school area, which is the main living space of children. In this study, the characteristics of domestic children's traffic accidents were investigated and the problems were analyzed by conducting a field survey on Yeouido Secondary School in Seoul and Unjung Elementary School in Gyeonggi Province. In addition, Variable speed limit signs and Beacons were installed in the pedestrian road of comunity including School zone, and the effects of facilities on the speed of vehicles were analyzed. As a result of the analysis, the Variable speed limit sign showed a deceleration effect of about 8.3km/h, and the Beacon showed a phenomenon in which the traveling speed of 0.8km/h increased only slightly. In addition, the traffic violation rate of passenger cars, buses, and lorries decreased by about 3% as a result of investigating the number of traffic violation vehicles before and after installation.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.115-131
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• 2001

The Purpose of this study is to develop a simulation model for large-scale network with interrupted flow as well as uninterrupted flow. The Cell Transmission(CT) theory is used to simulate traffic flow. Flow transition rules have been newly developed to simulate traffic flows at merging and diverging sections, and signalized intersections. In the model, it is assumed that dynamic OD table is exogenously given. Simulation results for toy network shows that the model can explain queue dynamics not only in signalized intersections of urban arterials, but also in merging and diverging sections of freeway. In case study, the model successfully simulated traffic flows of 145,000 vehicles on CBD network of city of Seoul with 74 traffic zones, 133 signalized intersections among 395 nodes and 1110 links.