• Journal of Korean Society of Transportation
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• v.24 no.1 s.87
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• pp.85-94
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• 2006

Currently, when the military performs military operations in wartime and peace time, it is important for him to obtain repeatedly updated traffic information for security of the military supply support. The purpose of this study is to present an acquisition way of the repeatedly updated traffic information which the military is available. To achieve this Purpose, firstly, this paper finded types of traffic information which the military demanded and limitations caused by an connection of traffic information network between the military and associated government agencies. Also. grasped ITS(Intelligent Transportation systems) equipment operation by associated government agencies (Ministry Construction & Transportation, Korea Highway Corporation, Seoul Metropolitan Government, National Police Agency, Korea Institute of Construction Technology) and connection situations of traffic information network among associated government agencies. On the basis of these materials, this study presented the most efficient connection method in the field of the space and the contents of traffic information between the military and associated government agencies and ITS connection system between the military and associated government agencies was contrived. Throughout the upper processes, this paper showed a method which is available for acquiring ITS traffic information of associated government agencies. In addition to the connection method of ITS traffic information network, resolutions for the problems caused by connection of ITS network were come up with. But the more deep study for this matter is needed since resolutions for the problems of the ITS network connection, which this paper presented, were very restricted.

• Proceedings of the KOR-KST Conference
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• 2003.02a
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• pp.127-150
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• 2003

This research presents a novel application of static traffic assignment methods, but with a variable time value, for estimating the market share of a high-speed rail (HSR) in the NW-SE corridor of Korea which is currently served by the airline (AR), conventional rail (CR), and highway (HWY) modes. The proposed model employs the time-space network structure to capture the interrelations among all competing transportation modes, and to reflect their supply- and demand-sides constraints as well as interactions through properly formulated link-node structures. The embedded cost function for each network link offers the flexibility for incorporating all associated factors, such as travel time and fare, in the model computation, and enables the use of a distribution rather than a constant to represent the time-value variation among all transportation mode users. To realistically capture the tripmakers' value-of-time (VOT) along the target area, a novel method for VOT calibration has been developed with aggregate demand information and key system performance data from the target area. Under the assumption that intercity tripmakers often have nearly "perfect" travel information, one can solve the market share of each mode after operations of HSR for each O-D pair under the time-dependent demand with state-of-the-art traffic assignment. Aside from estimating new market share, this paper also investigated the impacts of HSR on other existing transportation modes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3369-3385
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• 2019

There are various research challenges in vehicular ad hoc networks (VANETs) that need to be focused until an extensive deployment of it becomes conceivable. Design and development of a scalable routing algorithm for VANETs is one of the critical issue due to frequent path disruptions caused by the vehicle's mobility. This study aims to provide a novel road-aware routing protocol for vehicular networks named as Two-level hierarchical Hybrid Road-Aware (THERA) routing for vehicular ad hoc networks. The proposed protocol is designed explicitly for inter-vehicle communication. In THERA, roads are distributed into non-overlapping road segments to reduce the routing overhead. Unlike other protocols, discovery process does not flood the network with packet broadcasts. Instead, THERA uses the concept of Gateway Vehicles (GV) for the discovery process. In addition, a route between source and destination is flexible to changing topology, as THERA only requires road segment ID and destination ID for the communication. Furthermore, Road-Aware routing reduces the traffic congestion, bypasses the single point of failure, and facilitates the network management. Finally yet importantly, this paper also proposes a probabilistical model to estimate a path duration for each road segment using the highway mobility model. The flexibility of the proposed protocol is evaluated by performing extensive simulations in NS3. We have used SUMO simulator to generate real time vehicular traffic on the roads of Gangnam, South Korea. Comparative analysis of the results confirm that routing overhead for maintaining the network topology is smaller than few previously proposed routing algorithms.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.101-109
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• 2007

Two variations of toll roads exist: mainline toll plazas and entry/exit tolls. On a mainline toll system(open toll scheme), all vehicles stop at various locations along the highway to pay a toll. While this may save money from the lack of need to construct tolls at every exit, it can cause lots of traffic congestion, and drivers could evade tolls by going around them. With entry/exit tolls, vehicles collect a ticket when entering the highway, which displays the fares it will pay when it exits, increasing in cost for distance travelled. Upon exit, the driver will pay the amount listed for the given exit. The pressures on the Seoul ring roadway network have been changing over time. In the past, the emphasis was on mobility and maintenance of the road network to provide an efficient transportation network, but recently, road use has outstripped the network's ability to extend and expand the road network and hence the policy emphasis has moved towards reducing free riders rather than mitigating its effects. In addition to this pressure is an incidental pressure, which argues that provision of free ride segments generates further traffic in isolation of other factors. This paper is examining policies to reduce the burden of traffic congestion in Seoul ring roadway which is used open toll scheme for decades. One key mechanism to achieve this policy aim is automatic charging mechanism on freeway, but if a nation-wide electronic toll collection is to be implemented successfully, there are a number of prerequisites which must be place.

• The Journal of Information Systems
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• v.29 no.2
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• International Journal of Highway Engineering
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• v.19 no.4
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• pp.1-7
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• 2017

PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

• International Journal of Highway Engineering
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• v.17 no.3
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• pp.97-105
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• 2015

PURPOSES : The Toll Collection System (TCS) operated by the Korea Expressway Corporation provides accurate traffic counts between tollgates within the expressway network under the closed-type toll collection system. However, although origin-destination (OD) matrices for a travel demand model can be constructed using these traffic counts, these matrices cannot be directly applied because it is technically difficult to determine appropriate passenger car equivalent (PCE) values for the vehicle types used in TCS. Therefore, this study was initiated to systematically determine the appropriate PCE values of TCS vehicle types for the travel demand model. METHODS : To search for the appropriate PCE values of TCS vehicle types, a traffic demand model based on TCS-based OD matrices and the expressway network was developed. Using the traffic demand model and a genetic algorithm, the appropriate PCE values were optimized through an approach that minimizes errors between actual link counts and estimated link volumes. RESULTS : As a result of the optimization, the optimal PCE values of TCS vehicle types 1 and 5 were determined to be 1 and 3.7, respectively. Those of TCS vehicle types 2 through 4 are found in the manual for the preliminary feasibility study. CONCLUSIONS : Based on the given vehicle delay functions and network properties (i.e., speeds and capacities), the travel demand model with the optimized PCE values produced a MAPE value of 37.7%, RMSE value of 17124.14, and correlation coefficient of 0.9506. Conclusively, the optimized PCE values were revealed to produce estimates of expressway link volumes sufficiently close to actual link counts.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.117-130
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• 1999

Earthquakes damage roadway bridges and structures, resulting in significant impacts on transportation system Performance and regional economy. Seismic risk analysis (SRA) procedures establish retrofit priorities for vulnerable highway bridges. SRA procedures use average daily traffic volumes to determine the relative importance of a bridge. This research develops a cost-effective transportation network analysis (TAN) procedure for evaluating numerous traffic flow analyses in terms of the additional system cost due to failure. An important feature of the TNA Procedure is the use of an associative memory (AM) approach in the artificial intelligence held. A simple seven-zone network is developed and used to evaluate the TNA procedure. A subset of link failure system states is randomly selected to simulate synthetic post-earthquake network flows. The performance of different AM model is evaluated. Results from numerous link-failure scenarios demonstrate the applicability of the AM models to traffic flow estimation.

• International Journal of Highway Engineering
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• v.13 no.2
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• pp.195-202
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• 2011

This study develops a day-to-day dynamics modeling framework, incorporating a consistent drivers' travel time perception behavior and traffic information provision. Descriptive traffic information is updated and provided to the subscribers making a final decision on route choice. Nonsubscribers(not equipped any information devices) are assumed to obtain daily traffic information from their experience or friends or other public agencies. Drivers' route choice behavior is modeled based on boundedly-rational behavior rules. A microscopic traffic simulation model is adopted to evaluate the network system performance. Numerical experiments on a real world network have demonstrated the convergent property of the proposed model and the effectiveness of the consistent perception model.

• Journal of Korean Society of Transportation
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• v.35 no.3
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• pp.220-233
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• 2017

Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.