• Journal of the Korean Society of Safety
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• v.29 no.3
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• pp.98-106
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• 2014

This study proposes severity analysis for pedestrian accidents by improving variables which were used for general severity analysis. The existing variables were collected based on the interviews with policeman or witnesses and evidence of accidents. Therefore, existing variables were subjective and had several measurement errors. In order to improve such problems, this study collected variables from vehicle recorder of taxi which recorded the moment of accidents. As a result, explanatory power of independent variables was enhanced and the complete objective variables could be collected. After collecting variables, ordered probit model was developed by utilizing vehicle recorder database. Fitness of ordered probit model was 0.23. Vehicle speed and pedestrian's eye direction variables were the most critical factors for severity of pedestrian accident. In addition, severity analysis for vulnerable pedestrian was carried out. As a result, it was revealed that vehicle speed, pedestrian's eye direction and safety zone variables affected the severity of pedestrian accidents most. Particularly, vehicle speed variable is the most important factor. Consequently, driver's defensive driving and compliance to the regulations are the priority to reduce severity of pedestrian accidents and prevent pedestrian accident.

• Journal of the Korean Society for Railway
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• v.18 no.5
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• pp.471-480
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• 2015

Reliance on road transport in domestic logistics can lead to intensified congestion and greenhouse gas emissions due to the rise in oil prices, any increase in logistics costs can have a high social cost. The government policy on Low Carbon Green Growth is seeking to take advantage of the railway system. However, existing railway transport logistics systems, for reasons such as low speed, low track capacity constraints, and the impossibility of implementing a Door to Door system, make it difficult to activate a railway logistics program. As a result of this study, a national R&D project to develop a High-Speed Passenger/Baggage Mixed Train(Hy-SoBex) utilizing the rail capacity constraints to overcome the difficulties of linking an air cargo and freight railway logistics system, we propose a variety of service models and select the optimal service model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.70-85
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• 2021

Deep learning methodology, which has been actively studied in recent years, has improved the performance of artificial intelligence. Accordingly, systems utilizing deep learning have been proposed in various industries. In traffic systems, spatio-temporal graph modeling using GNN was found to be effective in predicting traffic speed. Still, it has a disadvantage that the model is trained inefficiently due to the memory bottleneck. Therefore, in this study, the road network is clustered through the graph clustering algorithm to reduce memory bottlenecks and simultaneously achieve superior performance. In order to verify the proposed method, the similarity of road speed distribution was measured using Jensen-Shannon divergence based on the analysis result of Incheon UTIC data. Then, the road network was clustered by spectrum clustering based on the measured similarity. As a result of the experiments, it was found that when the road network was divided into seven networks, the memory bottleneck was alleviated while recording the best performance compared to the baselines with MAE of 5.52km/h.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.77-84
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• 2016

In 2012, total GHG emissions in transport sector reached 88 Million ton CO2eq. The emissions generated in the road accounted for 94% of the transport sector. Currently, there are many efforts to operate an education and campaign for eco-driving. However study for eco-friendly vehicle control considering road alignment is limited. Therefore, the purpose of this study is to address fuel-efficient driving strategy in horizontal curve section. To fulfill the goal, designed ideal freeway horizontal curve road follows regulations about road structure. And safety speed is calculated for considering vehicle's safety on horizontal curve road. Authors composed the acceleration and deceleration scenario for each horizontal curve section and generated the speed profiles that are limited by the safety speed. Speed profiles are converted into force that horizontal curve affect to fuel consumption. Then, we calculated fuel consumption using Comprehensive Modal Emission Model. Then, we developed eco-driving strategy by selecting most fuel-efficient scenario. To validate this strategy, we selected study site and compared fuel consumption for eco and manual driving. As the result, fuel consumption when driver used eco-driving was lessened by 20.73% than that of manual driving.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.70-81
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• 2020

Point-by-point data, which is abundantly collected by vehicles with embedded GPS (Global Positioning System), generate useful information. These data facilitate decisions by transportation jurisdictions, and private vendors can monitor and investigate micro-scale driver behavior, traffic flow, and roadway movements. The information is applied to develop app-based route guidance and business models. Of these, speed data play a vital role in developing key parameters and applying agent-based information and services. Nevertheless, link speed values require different levels of physical storage and fidelity, depending on both collecting and reporting intervals. Given these circumstances, this study aimed to establish an appropriate collection interval to efficiently utilize Space Mean Speed information by vehicles with embedded GPS. We conducted a comparison of Probe-vehicle data and Image-based vehicle data to understand PE(Percentage Error). According to the study results, the PE of the Probe-vehicle data showed a 95% confidence level within an 8-second interval, which was chosen as the appropriate collection interval for Probe-vehicle data. It is our hope that the developed guidelines facilitate C-ITS, and autonomous driving service providers will use more reliable Space Mean Speed data to develop better related C-ITS and autonomous driving services.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.116-127
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• 2017

A fog on road is known as a weather factor that affects traffic flow. The method in order to solve the problem, recently, Variable Speed Limit(VSL) which provide reasonable speed limit by road and weather conditions in real time is introduced. However, if drivers do not comply with VSL, the road safety more decrease than without VSL because individual vehicle's speed deviation is larger than without VSL. Therefore, this paper aims to analyze to speed limit compliance and traffic characteristics under foggy conditions with and without VSL. A test using driving simulator divides into normal and foggy condition with visibilities are 200m, 150, 50~100m. The test results showed that 70 subjects's average speed mostly obeyed speed limit, but speed deviation generally declined with VSL. Especially, the speed deviation more reduced under foggy conditions. According to this study, compliance of VSL clearly rose in low visibility and VSL helped improve road safety due to reduction of speed deviation. The results of this study are expected to make use of reasonable speed limit for reference.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.68-77
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• 2013

This study suggested experimental study results of congestion detection method for intruding vehicle enforcement system. This congestion detection method is developed to determine optimal operation criteria of intruding vehicle enforcement system as detecting traffic congestion. In ITS sector, traffic management systems generally have used a sectional travel speed for congestion detection. However, image sensors have high error rate of congestion detection because of speed error. This study suggested comprehensive congestion detection criteria based on speed and occupancy rate using field studies. As field study results, the proposed intruding vehicle enforcement system using image sensor is capable of accurately detecting the traffic congestion using sectional speed of 20km/h and occupancy rate of 60% as congestion detection criteria.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.13-22
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• 2009

Recently, DSRC technology is used in the various fields such as parking system, BIS, ETC, etc. This paper suggests a traffic information system using this DSRC technology. The traffic information processing based on point detection using existing vehicle detection equipment is the system in which a collection and a service are operated separately while the traffic information system based on the link detection using DSRC is able to collect and provide the traffic information through the communication between RSE and OBU. The speed of a traffic congestion is high on the process converted from a point passing speed to a link average speed because the vehicle detection equipment makes the link traffic information into the point information. When the condition of traffic is deteriorated, traffic speed of the vehicle detection equipment becomes higher than DSRC. Especially, in this system, deflection by data of the traffic speed of the traffic information system is much decreased, and the unexpected condition detection and traffic condition are provided promptly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.152-167
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• 2018

The high-speed weigh-in-motion system can collect the traveling speed and load information of individual vehicles, which can be used in a variety of ways for the traffic surveillance. However, it has a limit to apply the high-speed weigh-in-motion data directly to a safety analysis because high-speed weigh-in-motion's raw data are point measured data. In order to overcome this problem, this paper proposes a method to calculate the conflict rate and the Impulse severity based on surrogate safety measures derived from the detection time, detection speed, vehicle length, vehicle type, vehicle weight. It will be possible to analyze and evaluate the risk of rear-end collision on freeway traffic. In addition, this study is expected to be used as a fundamental for identifying crash risks and developing policies to enhance traffic safety on freeways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.85-95
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• 2017

This study aims to identify the throw distance in terms of truck weight, bumper height, and speed in a truck and pedestrian collision, and to propose a model for throw distance estimates. For this purpose, a simulation analysis is performed using the PC-crash program with the following experiment conditions: Truck weight of 5t, 15t, and 25t, Bumper height from 0.3m to 0.6m by 0.1m, and speed from 10km/h to 100km/h by 10 km/h. Experimental results show that the truck speed and bumper height are found to be significant factors for pedestrian throw distance, but truck weight is not a significant factor. Also, a regression model is developed for pedestrian throw distance estimate from the multiple regression analysis. The adjusted $R^2$ value of the model is 93.3%, which is very good explanatory power.