• International Journal of Highway Engineering
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• v.15 no.5
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• pp.145-156
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• 2013

PURPOSES : This research is a study on the changes in the road network of the surrounding area is installed according to the Kiss & Ride Zone. METHODS : Estimating the transportation mode of students by using the Metropolitan household Surveys(2006) and estimating the O/D by Kiss & Ride ratio with the estimated data, then being applied to a method of reducing the number of lanes for certain sections of the road which would be installed with Kiss & Ride Zone. RESULTS : The reason why it is different for delay resolving time and the affected roads as the Kiss & Ride percentage change, was the impact of the Kiss & Ride Zone's installation position. CONCLUSIONS : The purpose of the study was to analyze the impact of the road network in accordance with the installation of Kiss & Ride Zone by using speed and queue delay resolving time, and it is a need to develop a quantitative evaluation technique which was using various indicators in impact analysis according to the installation of the traffic safety facilities in the future.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.167-176
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• 2011

This study's purpose is to analyse factors of determination about detouring for makinga standard model in regard of unfavorableness and uncertainty when unspecified individual recipients make a decision at the time of course detour. In order to achieve this, we surveyed SP investigation whether making a detour or not for drivers as a target who take a high way and National highway. Based on this result, we analysed detour determination factors of drivers, establishing a combination model of Decision Tree and Neural Network model. The result demonstrates the effected factors on drivers' detour determination are in ordering of the recognition of alternative routevs, reliable and frequency of using traffic information, frequency of transition routes and age. Moreover, from the outcome in comparison with an existing model and prediction through undistributed data, the rate of combination model 8.7% illustrates the most predictable way in contrast with logit model 12.8%, and Individual Model of Decision Tree 13.8% which are existed. This reveals that the analysis of drivers' detour determination factors is valid to apply. Hence, overall study considers as a practical foundation to make effective detour strategies for increasing the utility of route networking and dispersion in the volume of traffic from now on.

• Journal of Korean Society of Transportation
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• v.4 no.1
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• pp.3-11
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• 1986

One important element of a systematic approach to the management and control of the flow of people over an urban street network is the monitoring and evaluation of system performance. The nature of TSM strategies that, in part, differentiates them from traditional long-range transportation improvement alternatives is that they are less costly, are more quickly implemented and modified, and are often oriented toward sub-area problems which must be addressed at a more microscopic level of analysis. These factors suggest that pre-implementation evaluations of alternative TSM actions will often have to rely on quick-turn around, manual methods of analysis to guide the choice of which management action should be implemented. This paper was prepared to focus on the definition and importance of TSM, specifically associated with monitoring and evaluating traffic performance in the context of TSM startegies. A simple case study of reversible lane technique was presented. The purposes of the case study is to illustrate the methodology of evaluating TSM strategies and demonstrate to identify the benefit from the reversible lane technique, which may otherwise be overlooked in real world. Applying the reversible lane technique to Sam-Il elevate highway, it was found to be a very promising low cost alternative to reduce total travel time(or delay) and fuel consumption.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.208-218
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• 2017

This study aims to develop the Vehicle Local Dynamic Map (V-LDM) and demonstrate its performance for providing dynamic map data efficiently to the vehicle control module. Firstly, the concept of the in-vehicle LDM has been established and then the system has been carefully designed according to the international standards. The high-precision digital map embedded in LDM has been designed to incorporate the lane-level information of road network, and the Dynamic Map protocol (DM protocol) which is a message protocol including the road data with dynamic traffic event data has been defined. The performance test of the proposed system has been conducted in the uninterrupted road section of Kyungbu expressway, showing that both of the data size and the elapsed time to finish the process are almost linearly proportional to the length of target road. Finally, it is recommended that the length of target road for DM protocol be less than 250m.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2465-2471
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• 2013

This paper develops a travel time prediction algorithm that can be used for real-time application. The algorithm searches for the most similar pattern in historical travel time database as soon as a series of real-time data become available. Artificial neural network approach is then taken to forecast travel time in the near future. To examine the performance of this algorithm, travel time data from Gyungbu Highway were obtained and the algorithm is applied. The evaluation shows that the algorithm could predict travel time within 4% error range if comparable patterns are available in the historical travel time database. This paper documents the detailed algorithm and validation procedure, thereby furnishing a key to generating future travel time information.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1999-2007
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• 2013

The key characteristics of two-lane-and-two-way traffic flow are platoon and overtaking caused by low-speed vehicle such as truck. In order to develop two-way traffic flow model comprised of CF(car-following) and overtaking model, it is essential to develop a car-following model which is suitable to two-way traffic flow. Short distance between vehicles is caused when a high-speed vehicle tailgates and overtakes foregoing low-speed vehicle on two-way road system. And a vehicle following low-speed vehicle decides to overtake the front low-speed vehicle using suitable space within the headway distribution of opposite traffic flow. For this reason, a two-way CF model should describes not only running within short gap but also headway distribution. Additionally considering domestic two-way-road size, there is a on-going need for large-network simulation, but there are few studies for two-way CF model. In this paper, a two-way CA model is developed, which explains two-way CF behavior more realistic and can be applied for large road network. The experimental results show that the developed model mimics stop-and-go phenomenon, one of features of congested traffic flow, and efficiently generates the distribution of headway. When the CF model is integrated with overtaking model, it is, therefore, expected that two-way traffic flow can be explained more realistically than before.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.95-105
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• 2009

Traffic accidents on highways are likely to happen when there is an imbalance in the complex relationships among key elements such as road geometries, driver related factors, and mechanical performances. The Demand-Effort Model (DEM), which evaluates highway safety, can be explained by the imbalance, which occurs when the level of demand of the driver's attention to the road environment exceeds that of the response from the driver. This study suggests a new model that improves the reliability of the current DEM through the reinterpretation on the physiological signals with the help of the Neural Network Model (NNM). The data were collected from 149 subjects, who drove a test vehicle on the Yongdong, Honam, and Seohaean Expressways in Korea. Three important results could be drawn from the recursive tests as follows; (1) Only 5 out of 10 parameters on the physiological signals which are currently used were proven to be meaningful through the Normality Test, Cluster Analysis, and Mann-Whitney Analysis. (2) The revised DEM, which internally uses the NNM, showed more reliable results than existing DEM. Group 1, which is based on the new DEM showed 80.0% of accuracy in measuring the level of driver's efforts, however, that of Group 2 based on the current DEM was 74.3%. (3) Field tests on the Honam Expressway showed lower 'type II error' with the new DEM (40.5%) than the old DEM (58.8%). The DEM is designed as a quick and easy way to determine highway safety prior to the minute road safety audit (RSA) by a professional audit team. Then a new DEM, which is based on the NNM, needs to be considered since it showed higher reliability and lower error.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.71-78
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• 2018

Transportation is gradually changing into the era of V2X and autonomous cars. Accurate judgement of traffic conditions is an important indicator of route choice or autonomous driving. There are many ways to use probes car such as taxis, as a way to identify accurate traffic conditions. These methods may vary depending on the characteristics of the probe vehicle, and there is a problem with the cost. The V2X vehicle can solve these problems and collect traffic information in real time. If all vehicles are of V2X vehicle, these issues are expected to be resolved briefly. However, if the communication information of a V2X vehicle is represented by a traffic representative in a traffic with only V2X, the traffic information of some V2X vehicles will be able to collect traffic information. To accomplish this, a virtual network and transport were created and various scenarios were performed through SUMO simulations. It has been analyzed that 3-5 % of V2 vehicles are capable of representative the road traffic characteristics. In the future, various follow-up studies are planned.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.141-155
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• 2017

As the use of SNS becomes more active, many people are posting their thoughts about specific events in their SNS in the form of text. As a result, SNS is used in various fields such as finance and distribution to conduct service satisfaction surveys and consumer monitoring. However, in the transportation area, there are not enough cases to utilize unstructured data analysis such as emotional analysis. In this study, we developed an emotional analysis methodology that can be used in transportation by using highway VOC data, which is atypical data collected by Korea Expressway Corporation. The developed methodology consists of morpheme analysis, emotional dictionary construction, and emotional discrimination of the collected unstructured data. The developed methodology was verified using highway related tweet data. As a result of the analysis, it can be guessed that many information and information about the construction and the accident were related to the highway during the analysis period. Also, it seems that users complain about the delay caused by construction and accident.

• International Journal of Highway Engineering
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• v.11 no.3
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• pp.129-139
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• 2009

The transportation network is a critical infrastructure in the event of natural and human caused disasters such as rainfall, snowfall, and terror and so on. Particularly, the transportation network in an urban area where a large number of population live is subject to be negatively affected from such events. Therefore, efficient traffic operation plans are required to assist rapid evacuation and effective detour of vehicles on the network as soon as possible. Recently, ubiquitous communication and sensor network technology is very useful to improve data collection and connection related emergency information. In this study, we develop a specific algorithm to provide evacuation route and detour information only for vehicles under emergency situations. Our algorithm is based on shortest path search technique and dynamic traffic assignment. We perform the case study to evaluate model performance applying hypothetical scenarios involved terror. Results show that the model successfully describe effective path for each vehicle under emergency situation.