• International Journal of Highway Engineering
• /
• v.13 no.1
• /
• pp.69-77
• /
• 2011

This study is to suggest a methodology to overcome the uncertainty and lack of reliability of data. The fuzzy reasoning model and the neural network model were developed in order to overcome the potential lack of reliability which may occur during the process of data collection. According to the result of comparison with the Poisson regression model, the suggested models showed better performance in the accuracy of the accident frequency prediction. It means that the more accurate accident frequency prediction model can be developed by the process of the uncertainty of raw data and the adjustment of errors in data by learning. Among the suggested models, the performance of the neural network model was better than that of the fuzzy reasoning model. The suggested models can evaluate the safety of signalized intersections in operation and/or planning, and ultimately contribute the reduction of accidents.

• International Journal of Highway Engineering
• /
• v.9 no.2 s.32
• /
• pp.1-11
• /
• 2007

The rapid growths of economy and automobiles since the 1970's have caused serious traffic jams and environmental disruption in urban areas. To relieve these problems caused by urbanization, there should be considered alternative means of transportation modes. Many developed countries have accepted bicycles as a so called "Green Mode" for environmentally oriented strategies to increase the qualities of urban lives. Korea have also attempted various means to raise bicycle usages. In this research, significant factors affecting bicycle crashes at signalized intersections in urban areas were studied. The model results showed that Poisson regression is the best fit methodology for data modeling and revealed that traffic volume, a number of driveways, configuration of the ground, presence of bicycle path, school, and bus stop, residential area, size of intersection are significant factors affecting the bicycle crashes.

• Journal of Korean Society of Transportation
• /
• v.27 no.6
• /
• pp.69-77
• /
• 2009

The maximum and mean acceleration rates of vehicles estimated from the stopping conditions at signalized intersections provided an important clue to analyze traffic accident investigation when there was a dispute about legal liability such as first entering vehicle at the intersection, etc. This paper provided the maximum and mean acceleration rates of vehicles reflecting current traffic conditions in Korea through field studies. The mean acceleration rates of vehicles at stopline were measured up to 50m at the intervals of 5m. Results showed that the mean acceleration rate for bus was found to be $1.011^m/s^2{\sim}1.314^m/s^2$(0.1g~0.13g), and for passenger car was $1.548^m/s^2{\sim}1.818^m/s^2$(0.16g~0.19g). Statistical test results indicated that the observed differences from vehicle types and vehicle positions were statistically significant for the all ranges tested. It is expected that the accuracy of accident investigation practice will be improved by applying the acceleration rate values presented in this paper.

• International Journal of Highway Engineering
• /
• v.11 no.4
• /
• pp.33-40
• /
• 2009

This study deals with the traffic accidents of elderly drivers. The objectives are to comparatively analyze the characteristics of accident between the elderly and other drivers, and to develop the models of traffic accidents. In pursuing the above, this paper gives particular attentions to testing the differences between the above two groups, and developing the models(Poisson and negative binomial regression) using the data of Cheongju 4-legged signalized intersections. The main results analyzed are as follows. First, the differences between the elderly and other drivers' accidents were clearly defined by the time of day, accident type, etc. Second, 3 accident models which were all statistically significant were developed. Finally, the differences between elderly and other drivers' models were comparatively analyzed using the common and specific variables.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.41 no.6
• /
• pp.707-714
• /
• 2021

An important factor that causes delays at roundabouts is unbalanced traffic conditions. The majority of domestic studies have tendedto focus on the proportion of entering traffic rather than conflicting traffic in order to explain unbalanced traffic conditions. Also, there is scant research on the proper distance between a signalized intersection and a roundabout. In this study, therefore, unbalanced traffic conditions and optimal distance between two intersections were analyzed using SIDRA software based on the Gajwa-ro roundabout in Icheon, where unbalanced traffic conditions occur during afternoon peak hours, and its position is 295 m from a signalized intersection. It was found that a state of unbalanced traffic conditions in the form of conflicting traffic caused delays at Gajwa-ro roundabout, and the queuing length on each approach was removed when there was 850 m of distance between two intersections.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.4D
• /
• pp.573-580
• /
• 2006

The Saturation headway is a major parameter in estimating the intersection capacity and setting the signal timing. But Existing algorithms are still far from being robust in dealing with factors related to the variation of saturation headways at signalized intersections. So this study apply the fuzzy inference system using ANFIS. The ANFIS provides a method for the fuzzy modeling procedure to learn information about a data set, in order to compute the membership function parameters that best allow the associated fuzzy inference system to track the given input/output data. The climate conditions and the degree of brightness were chosen as the input variables when the rate of heavy vehicles is 10-25 %. These factors have the uncertain nature in quantification, which is the reason why these are chosen as the fuzzy variables. A neuro-fuzzy inference model to estimate saturation headways at signalized intersections was constructed in this study. Evaluating the model using the statistics of $R^2$, MAE and MSE, it was shown that the explainability of the model was very high, the values of the statistics being 0.993, 0.0289, 0.0173 respectively.

• Journal of the Society of Disaster Information
• /
• v.11 no.4
• /
• pp.597-606
• /
• 2015

Until now, u-turn lane installation methods have been studied variously. But, There is no specific standard yet. This study ranges are commercial area in Incheon metropolitan city through field investigation and presents specific design standard for efficient operation of left turn using a field data through calculating relevant permitted u-turn lane length and minimum separation distance from the front intersection to starting point of permitted u-turn lane in urban signalized intersections in commercial area. Relevant permitted u-turn lane length is found to be 32m and minimum separation distances from the front intersection to starting point of permitted u-turn lanes are 72m, 40m, 24m in case of 1 left turn lane, 2 left turn lanes and 3 left turn lanes respectively. By comparing result values and field data, they had a large difference under the similar situations in their lengths. This result is caused of no specific standard about design of u-turn lanes. If results of this study applied to design of u-turn lanes, signalized intersections in urban commercial areas would be operated more safety and efficiently.

• Journal of Korean Society of Transportation
• /
• v.28 no.6
• /
• pp.109-120
• /
• 2010

This study aims to develop mathematical models for estimating saturation flow rates at the stop line of signalized intersection due to Workzones in the vicinity, since the saturation flow rate is the most critical parameter in capacity analysis for signalized intersections. It was found by reference review that saturation flow rates are sensitively influenced by the location of Workzone, the number of lanes, cycle length and effective green time. Extensive microscopic simulation runs were also performed and compared to the those of mathematical models for model verification. Mathematical models were developed based on traffic flow theory and dualizing them by the location of workzones. And then each result produced by changing important parameter values was carefully examined and analyzed. Small but consistent differences in saturation flow rate values between mathematical models and simulations exist. However, the pattern of changes in saturation flow rates depending on each variable was similar.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.3
• /
• pp.153-164
• /
• 2018

Calculating the relevant length of left turn storages in urban intersections is very crucial in road designs. A left turn lane consists of deceleration lanes and left turn storages. In this study, we developed methods for calculating relevant lengths of left turn storages that vary at each intersection using UAV (Unmanned Aerial Vehicle) spatial images. Problems of conventional design techniques are applying the same number of left turn vehicles (N) using Poisson distribution without considering land use types, using a vehicle length that may not be measurable when applying the length of waiting vehicles (S), and using same storage length coefficient (${\alpha}$), 1.5, for every intersections. In order to solve these problems, we estimated the number of left turn vehicles (N) using an empirical distribution, suggested to use headways of vehicles for (S) to calculate the length of waiting vehicles (S) with a help of using UAV spatial images, and defined ranges of storage length coefficient (${\alpha}$) from 1.0 to 1.5 for flexible design. For more convenient design, it is suitable to classify two cases when possible to know and impossible to know about ratio of large trucks among vehicles when planning an intersection. We developed formula for each case to calculate left turn storage lengths of a minimum and a maximum. By applying developed methods and values, more efficient signalized intersection operation can be accomplished.

• International Journal of Highway Engineering
• /
• v.14 no.6
• /
• pp.121-129
• /
• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.