• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.117-130
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• 2017

Bicycles are leading to serious accidents in the event of a side collision, and it is very important to prevent accidents in advance because it is difficult to actively deal with them in a dangerous situation. As a part of the bicycle safety driving support technology, this study establishes bicycle accidents dangerous zone based on bicycle accident data and road property information of digital map nationwide and provides timely safety information to cyclists. The point selected by using actual accident data was called 'dangerous zone', and the potential accident occurrence point generated by modeling based on this 'dangerous zone' was called 'logical dangerous zone'. As a result of the research on the Designation of Logical Bicycle Accident Dangerous Zone, the regional specificity of the bicycle accident points across the nation was generalized to the form of the logical dangerous zone through the network data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.26-37
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• 2017

The study is to develop safety performance functions(SPFs) for urban intersections using random effects Tobit regression model and to analyze correlations between crashes and factors. Also fixed effects Tobit regression model was estimated to compare and analyze model validation with random effects model. As a result, AADT, speed limits, number of lanes, land usage, exclusive right turn lanes and front traffic signal were found to be significant. For comparing statistical significance between random and fixed effects model, random effects Tobit regression model of total crash rate could be better statistical significance with $R^2_p$ : 0.418, log-likelihood at convergence: -3210.103, ${\rho}^2$: 0.056, MAD: 19.533, MAPE: 75.725, RMSE: 26.886 comparing with $R^2_p$ : 0.298, log-likelihood at convergence: -3276.138, ${\rho}^2$: 0.037, MAD: 20.725, MAPE: 82.473, RMSE: 27.267 for the fixed model. Also random effects Tobit regression model of injury crash rate has similar results of model statistical significant with random effects Tobit regression model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.64-77
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• 2017

Domestic railway station calculates average number of passenger per day by considering future regional society and development of industrial economy etc, is carrying out designs on railway station scale. However, problems are being suggested situationally because selected average passenger data does not consider passengers having been diversified for a year. For representative example, confusion of Gwangju-Songjeong Railway Station got worse due to passengers whose number is more than original plan since the opening. Therefore, this study quotes the concept of design hourly factor using in designing roads to consider passengers having been diversified for a year in railway field. In order to calculate factor, collecting railway passenger data and also estimate, reliability verification were executed by using exponential model and 3rd equation model. As a result of deducing design hourly factor through inflection point calculation, utilizing exponen tial model is analyzed to well reflect the value of design hourly factor on railway passengers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.12-28
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• 2017

The core of the transportation service, so-called Mobility 4.0 is the flexibility of the entire mobility and its implementation. By doing so, the most essential element is to build a platform to link a supply and a demand simultaneously. In other word, a comprehensive analytical framework is to be set with a data repository which can be periodically updated. With such circumstances, the entire trip chain including pedestrian movements is required to be thoroughly investigated and constructed at the viewpoint of the intermodal transit station. A few studies, however, have been attempted. In this study, the comprehensive analytical framework with the integrated mobility at intermodal transit station was proposed, which consisted of the three modules; 1) Data Repository Extracting from Smart Card DB, 2) Framework of Analyzing Integrated Mobility, and 3) Interpretation of the Integrated Mobility with GIS information and the other factors. A case study with the seven railway stations (Sadang, Sindorom, Samseong, Gwanghwanoon, Gangnam, Jamsil, Seoul Nat'l Univ. of Education) was conducted. The stations of the case study were clustered by the three groups with the statistical ground, and it is most likely to understand the effect of a variety of factors and a comprehensive data-driven analyses with the entire trip stages.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.134-143
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• 2017

In the case of highway, there may be a large number of travel time groups when there are a bus exclusive lane, a rest area, a sleeping shelter, etc. in the corresponding section. In most of the conventional travel time estimation studies, one representative travel time (assuming normal distribution) group is assumed in the low sample collection state, and if it is out of the specified range, it is determined as outliers and then the travel time is estimated. However, if there is a bus exclusive lane, a rest area, or a sleeping shelter in the relevant section, such as the highway, the distribution of travel time will be in the form of a bi-modal or a multi-modal, rather than a regular distribution. Therefore, applying the existing estimation methodology may result in distorted results. To solve this problem, first, it should be reliable even in the case of insufficient number of samples. Second, we propose a methodology to select the representative time group among a number of time groups and to estimate the representative time using individual time data of the selected time group.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.110-123
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• 2019

Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.202-210
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• 2019

This paper evaluated the performance of passenger vehicles with an AEB(Autonomous Emergency Braking) for various pedestrian-vehicle collision situations. The experiment was conducted at a speed of 30-60km/h on a 2017 3,000cc vehicle using a range of collision scenarios. The results showed that the test vehicle stopped before crashing a pedestrian dummy under all scenarios at 30km/h. The test vehicle reduced the speed but crashed the pedestrian dummy in all scenarios at 40-60km/h. From the paired t-test, there was a speed difference from the AEB system at a significant level of 0.05. In addition, the percentage of speed reduction was quite different for each scenario tested. It was concluded that the current AEB system can prevent pedestrian collisions at speed of 30km/h, but cannot prevent collisions with pedestrians at speed of 40-60 km/h.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.32-43
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• 2020

The transfer time is an important factor in establishing public transportation planning and policy. Therefore, in this study, the influencing factors of the transfer time for transit users were identified using smart card data, and the estimation results for the transfer time using the deep learning method such as deep neural network models were compared with traditional regression models. First, the intervals and the distance to the bus stop had positive effects on the subway-to-bus transfer time, and the number of bus routes had a negative effect. This also showed that the transfer time is affected by the area in which the subway station exists. Based on the influencing factors of the transfer time, the deep learning models were developed and their estimation results were compared with the regression model. For model performance, the deep learning models were better than those of the regression models. These results can be used as basic data for transfer policies such as the differential application of transit allowance times according to region.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.58-70
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• 2020

Detour behavior on the expressway means that the driver uses the local road by passing the part of the expressway which is stagnant at the time of the traffic demand such as holidays. Since the detour rate was estimated through the survey at toll gate in the past, there was a difficulty in estimating the actual detour rate due to the small sample of the survey. In this study, we use DSRC-based route travel data to conduct empirical studies on detour patterns such as the estimation of actual detour rate, the improvement of travel time using detour road, and the correlation between traffic conditions on the expressway and detour rate. On the day of Chuseok and the day before Chuseok, the analysis of Giheung-DongtanIC→OsanIC and Seopyeongtaek IC→Walgott JC showed that the use of detour roads increased gradually during the congestion of the main line and travel time reduced when using detour roads, However, when the traffic congestion of the main line is not severe, the travel time increases when using the detour roads. The correlation between the traffic condition of the expressway and the actual detour rate has a negative correlation, which is consistent with the congestion pattern of the main line. The results of this study can be used to overcome limitations of detour pattern research based on surveys in the past and to establish a detour strategy for expressway sections where traffic demand is concentrated.