• International Journal of Highway Engineering
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• v.11 no.1
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• pp.47-58
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• 2009

Calibrating toll roads of highway networks needs additional weights within volume delay functions not like other general highway lints. However, current methods assigning additional weights in the volume delay function of toll roads are not sufficiently enough to predict real toll road volumes measured, since it does not consider discounting rates and an extra charges. This study develops methods to improve relevant and reliable volume delay functions. Suggested ideas include a method of weighting volume delay functions considering a value of time of vehicle types, a method of weighting volume delay functions considering lane distributions of vehicles, and a method of weighting volume delay functions considering percentages of link lengths per a number of lanes of toll roads. It is found that the method of weighting volume delay functions considering lane distributions of vehicles show most reliable and appropriate results, while the first method shows overestimation and the third method does underestimation of highway link volumes. In terms of assignment methods, total OD equilibrium assignment shows better results than PCU based assignment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.29-36
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• 2019

Unmanned Autonomous Vehicle's driving road in the national defense includes not only paved roads, but also unpaved roads which have rough and unexpected changes. This Unmanned Autonomous Vehicles monitor and recon rugged or remote areas, and defend own position, they frequently encounter environments roads of various and unpredictable. Thus, they need additional learning to drive in this environment, we propose a Additional Learning Nearest Neighbor (ALNN) which is modified from Approximate Nearest Neighbor to allow for quick learning while avoiding the 'Forgetting' problem. In addition, since the Execution speed of the ALNN algorithm decreases as the learning data accumulates, we also propose a solution to this problem using GPU parallel processing based on OpenGL Shader Language. The ALNN based on GPU algorithm can be used in the field of national defense and other similar fields, which require frequent and quick application of additional learning in real-time without affecting the existing learning data.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2319-2344
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• 2010

Accumulated deficits resulting from managing the Korean Railroad and debts from the construction of the KTX (Korea Train Express which is a high-speed rail system) have left the Korean Railroad faced with great troubles. Since it changed into a public corporation Korail on January 1st, 2005, the Korea Railroad has been making unceasing efforts to overcome the troubles and improve its management. However, even these efforts haven't worked in the face of the improved conditions of other transportation methods such as better networks of land roads and air ways. The Korea Railroad had its revenue from its railway transportation limited, and has tried to expand its business to non-transportational areas. In some metropolitan cities, the Korea Railroad made investments in real estate by constructing station buildings based on private money. Yet, in small and medium size cities, the Korea Railroad has little particular strategic projects for business development. Recently certain small and medium size regional cities began to plan on business developments for the ex-railway land, and some small towns have developed real estate on the ex-railway land. Nevertheless, there have been no systematic case studies to classify these real estate developments.

• Journal of ILASS-Korea
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• v.28 no.4
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• pp.184-190
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• 2023

The European Union has instituted a new emission standard protocol that necessitates real-time measurements from vehicles on actual roads. The adequate development of routes for real driving emissions (RDE) mandates substantial resources, encompassing both vehicles and a portable emission measurement system (PEMS). In this study, a simulation tool was utilized to predict the vehicle speed traversing the routes developed for the RDE measurements. Initially, the vehicle powertrain system was modeled for both a gasoline hybrid vehicle and a gasoline engine-only vehicle. Subsequently, the speed profile for the specified vehicle was constructed based on the RDE route developed for the EURO-6 standard. Finally, the predicted vehicle speed profiles for highway and urban routes were assessed utilizing the actual driving data. The driving model predicted more consistency in the vehicle speed at each driving section. Meanwhile, the human driver tended to accelerate further, and then decelerate in each section, instead of cruising at a predicted section speed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.165-173
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• 2008

This study aims at generating automatically three dimensional geometric models of roads using LIDAR data and a digital map. The main processes in the proposed method are (1) generating a polygon encompassing a road region using a road layer from the digital map, (2) extracting LIDAR points within the road region using the polygon, (3) organizing the points into surface patches and grouping the patches into surface clusters, (4) searching the road surface clusters and generating the surface model from the points linked to the clusters, (5) refining the boundary using a digital map. By applying the proposed method to real data, we successfully generated the linear and surface information of the roads.

• Management Science and Financial Engineering
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• v.12 no.2
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• pp.87-110
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• 2006

In a hierarchical road network, all roads can be classified according to their attributes such as speed limit, number of lanes, etc. By splitting the whole road network into the subnetworks of the highlevel and low-level roads, we can reduce the size of the network to be calculated at once, and find a path in the way that drivers usually adopt when searching out a travel route. To exploit the hierarchical property of road networks, we define a convenient path and propose an algorithm for finding convenient paths. We introduce a parameter indicating the driver's tolerance to the difference between the length of a convenient path and that of a shortest convenient path. From this parameter, we can determine how far we have to search for the entering and exiting gateway. We also propose some techniques for reducing the number of pairs of entries and exits to be searched in a road network. A result of the computational experiment on a real road network is given to show the efficiency of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.967-976
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• 2016

This paper presents a 3D carrier-smoothed GNSS/DR (Global Navigation Satellite System/Dead Reckoning) integrated system for precise ground-vehicle trajectory estimation. For precise DR navigation on sloping roads, the AHRS (Attitude Heading Reference System) methodology is employed. By combining the integrated carrier phase of GNSS and DR sensor measurements, a vehicle trajectory with an accuracy of less than 20cm is obtained even when cycle slip or change of visibility occur. In order to supplement the weak GNSS environment with DR successfully, the DR sensor is precisely compensated for using GNSS Doppler measurements when GNSS visibility is good. By integrating a multi-GNSS receiver with low-cost IMU, a precise 3D navigation system for land vehicles is proposed in this paper. For real-time implementation, a decoupled Kalman filter is employed in the integrated system. Through field experiments, the performance of the proposed system is verified in various road environments, including sloping roads, good-visibility areas, high multi-path areas, and under-ground parking areas.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.317-319
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• 2021

In Korea, an intelligent transportation system(ITS) is established to efficiently operate traffic congestion on roads and is being used for traffic information collection and speed control systems. Currently, designated and dedicated lanes are in place to ensure traffic circulation and traffic safety, and systematic and accurate illegal vehicle crackdown systems with artificial intelligence technology are needed. In this study, we propose a vehicle number recognition model that can improve the efficiency of the traffic of designated vehicles. By applying computer vision technology, we are going to identify three-lane and four-lane multi-lane roads in real time and detect vehicle numbers by car to suggest ways to crack down on vehicles that violate the designated lane system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.438-444
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• 2019

With the increasing supply of vehicles, construction of new roads and expansion of existing roads are growing and this is leading to a proportional rise in diverse hazards on a road. These hazards are classified into fixed hazards and variable hazards. Currently, drivers receive information of fixed hazards, such as overspeed, frequent accidents, and rock fall through navigations. However, variable hazards are more hazardous than fixed hazards. Map companies frequently enter information of variable hazards manually, but it is less real-time and hard to deal with unforseen hazards. This paper is intended to implement a road hazard warning system for making a contribution to pubic interests by improving this problem and delivering real-time information of hazards to drivers, and suggest a direction for using information of hazards on a road.