• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.49-56
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• 2011

This paper deals with a methodology for searching optimal route of hazard material (hazmat) vehicles. When we make a decision of hazmat optimal paths, there is a conflict between the public aspect which wants to minimize risk and the private aspect which has a goal of minimizing travel time. This paper presents Efficient Vector Labeling algorithm as a methodology for searching optimal path of hazmat transportation, which is intrinsically one of the multi-criteria decision making problems. The output of the presented algorithm is a set of Pareto optimal paths considering both risk and travel time at a time. Also, the proposed algorithm is able to identify non-dominated paths which are significantly different from each other in terms of links used. The proposed Efficient Vector Labeling algorithm are applied to test bed network and compared with the existing k-shortest path algorithm. Analysis of result shows that the proposed algorithm is more efficient and advantageous in searching reasonable alternative routes than the existing one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.448-449
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• 2016

Enlargement and complexification of current structures increase the expected casualty in case of accident in those e.g., fire. In that case, there only have been basic instructions such as announcement of that situation, alarm bell, exit signs, etc. but any guidance to lead to proper escape route was not been provided so far. To tackle the problem, several schemes have been proposed. However, various risk factors were not considered and route discovery performance must be improved to be applied to structures. Therefore, this paper proposes an optimal route discovery system for emergency escape from disaster situations which takes into account various possible risk factors and enhances the searching efficiency by using the $A^{\ast}$ algorithm. Performance evaluation by computer simulation shows that the proposed scheme effectively leads to safe escape route.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.145-153
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• 2008

Existing shortest-path algorithms mainly consider a single attribute. But traveler actually chooses a route considering not single attribute but various attributes which are synthesized travel time, route length, personal preference, etc. Therefore, to search the optimal path, these attributes are considered synthetically. In this study route searching algorithm which selects the maximum utility route using discrete choice model has developed in order to consider various attributes. Six elements which affect route choice are chosen for the route choice model and parameters of the models are estimated using survey data. A multinomial logit models are developed to design the function of route choice model. As a result, the model which has route length, delay time, the number of turning as parameter is selected based on the significance test. We use existing shortest path algorithm, which can reflect urban transportation network such as u-turn or p-turn, and apply it to the real network.

• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.479-483
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• 2015

In case of the big city, choosing the adequate root of which we can reach the destination can affect the driver's condition and driving time. so it is quite important to find the optimal routes for arriving the destination as considering the factors, such as driving conditions or travel time and so on. In this paper, we develop route choice model with considering driving conditions and travel time, and it can search the optimal path which make drivers reduce their fatigues using genetic algorithm.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.451-457
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• 2012

Recently, as the use of real time traffic information of a car navigation system increases rapidly with the development of Intelligent Transportation Systems (ITS), path search is getting more important. Previous algorithms, however, are mostly for the shortest distance searching and provide route information using static distance and time information. Thus they could not provide the most optimal route at the moment which changes dynamically according to traffic. Accordingly, in this study, Semantic Shortest Path algorithm with Reduction ratio & Distance(SSP_RD) is proposed to solve this problem. Additionally, a routing model based on velocity reduction ratio and distance and a dynamic route link map are proposed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.91-99
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• 2019

Existing node-to-node based optimal path searching is built on the assumption that all destination nodes can be arrived at from an origin node. However, the recent appearance of the adaptive path search algorithm has meant that the optimal path solution cannot be derived in node-to-node path search. In order to reflect transportation data at the links in real-time, the necessity of the node-to-link (or link-to-node; NL) problem is being recognized. This research assumes existence of a network with link-label and non-additive path costs as a solution to the node-to-link optimal path problem. At the intersections in which the link-label has a turn penalty, the network retains its shape. Non-additive path cost requires that M-similar paths be enumerated so that the ideal path can be ascertained. In this, the research proposes direction deletion and turn restriction so that regulation of the loop in the link-label entry-link-based network transformation method will ensure that an optimal solution is derived up until the final link. Using this method on a case study shows that the proposed method derives the optimal solution through learning. The research concludes by bringing to light the necessity of verification in large-scale networks.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.109-117
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• 2014

In navigation route planning systems using A* algorithms, the cardinality of an Open list, which is a list of candidate nodes through which a terminal node can be accessed, increases as the path length increases. In this paper, a method of alternately utilizing the Dijkstra's algorithm and the A* algorithm to reduce the cardinality of the Open list is investigated. In particular, by employing a depth parameter, named Level, the two algorithms are alternately performed depending on the Level's value. Using the hybrid searching approach, the Open list constructed in the Dijkstra's algorithm is transferred into the Open list of the A* algorithm, and consequently, the unconstricted increase of the cardinality of the Open list of the former algorithm can be avoided and controlled appropriately. In addition, an optimal or nearly optimal path similar to the Dijkstra's route, but not available in the A* algorithm, can be found. The experimental results, obtained with synthetic and real-life benchmark data, demonstrate that the computational cost, measured with the number of nodes to be compared, was remarkably reduced compared to the traditional searching algorithms, while maintaining the similar distance to those of the latter algorithms. Here, the values of Level were empirically selected. Thus, a study on finding the optimal Level values, while taking into consideration the actual road conditions remains open.

• Information Systems Review
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• v.10 no.1
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• pp.115-133
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• 2008

The third-party logistics industry mainly delivers goods from a place to an arrival place on behalf of the freight owner. To handle the work, they need a transportation route including transportation equipment between the starting place and the arrival place, schedule information for departure/arrival and transportation cost. Actually, automatic searching for an optimal transportation route, which considers arrival and departure points for intermodal transportation, is not a simple problem. To search efficiently transportation route, the collection of schedule information for intermodal transportation and transportation route generation have become critical and vital issues for logistics companies. Usually, they manually make a plan for a transportation route by their experience. Because of this, they are limited in their ability if there is too much cargo volume and a great many transactions. Furthermore, their dependence on the conventional way in doing business causes an inefficient selection of transporters or transportation routes. Also, it fails to provide diverse alternatives for transportation routes to the customers, and as a result, increases logistics costs. In an effort to solve these problems, this study aims to develop a route planning system based on agent, which can collect scattered schedule information on the Web. The route planning system also has an algorithm for transportation route generation in intermodal transportation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.150-157
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• 2016

In this paper, a control system for E-bike based on IOT was developed, which collects and monitors information of states of E-bike and surrounding environments from several sensors and control devices in E-bike, and informs the possible dangers to rider when riding the E-bike. Developed electronic control system can manage battery efficiently, obtain battery's remaining power in real-time and provide possible riding distance to rider. It makes possible for rider to schedule near optimal riding route in terms of battery usage and respond quickly to battery discharge. Results of applying developed system to E-bike show that according to driving-mode, possible driving distance can be calculated efficiently and using user application App, real-time driver position marking and driving route searching functions lead to energy efficient E-bike driving. Later we will endeavor to integrate BMS, ECU, smart-phone and PC(server) to provide stable driving system based on various driving information of E-bike.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.1-12
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• 2017

The Seoul metropolitan transportation card's high value lies in its recording of total population movements of the public transit system. In case of recorded information on transit by bus, even though route information utilized by each passenger is accurate, the lack of passenger transfer information of the urban railway makes it difficult to estimate correct routes taken by each passenger. Therefore, pinpointing passenger path selection patterns arising in the metropolitan railway network and using this as part of a path movement estimation model is essential. This research seeks to determine that features of passenger movement routes in the urban railway system is comprised of M-similar routes with increasing number of transfer reflected as additional costs. In order to construct the path finding conditions, an M-similar route searching method is proposed, embedded with non additive path cost which appears through inclusion of the stepwise transportation parameter. As well, sensitivity of the M-similar route method based on transportation card records is evaluated and a stochastic trip assignment model using M-similar path finding is constructed. From these, link trip and transfer trip results between lines of the Seoul metropolitan railway are presented.