• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.67-74
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• 2011

In recent years, with increasing utilization of mobile devices such as smartphones, the need for PNS(Pedestrian Navigation Systems) that provide guidance for moving pedestrians is increasing. For the navigation services, road network is the most important component when it comes to creating route and guidance information. In particular, pedestrian network requires modeling methods for more detailed and vast space compared to road network. Therefore, more efficient method is needed to establish pedestrian network that was constructed by existing field survey and manual editing process. This research proposed a pedestrian network creation method appropriate for pedestrians, based on CNS(Car Navigation Systems) data that already has been broadly constructed. Pedestrian network was classified into pedestrian link(sidewalk, side street, walking facility) and openspace link depending on characteristics of walking space, and constructed by applying different methodologies in order to create path that similar to the movements of actual pedestrians. The proposed algorithm is expected to become an alternative for reducing the time and cost of pedestrian network creation.

• Journal of Korea Planning Association
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• v.54 no.3
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• pp.106-118
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• 2019

In order to develop pedestrian navigation service that provides optimal pedestrian routes based on pedestrian satisfaction levels, it is required to develop a prediction model that can estimate a pedestrian's satisfaction level given a certain condition. Thus, the aim of the present study is to develop a pedestrian satisfaction prediction model based on three machine learning algorithms: Logistic Regression, Random Forest, and Artificial Neural Network models. The 2009, 2012, 2013, 2014, and 2015 Pedestrian Satisfaction Survey Data in Seoul, Korea are used to train and test the machine learning models. As a result, the Random Forest model shows the best prediction performance among the three (Accuracy: 0.798, Recall: 0.906, Precision: 0.842, F1 Score: 0.873, AUC: 0.795). The performance of Artificial Neural Network is the second (Accuracy: 0.773, Recall: 0.917, Precision: 0.811, F1 Score: 0.868, AUC: 0.738) and Logistic Regression model's performance follows the second (Accuracy: 0.764, Recall: 1.000, Precision: 0.764, F1 Score: 0.868, AUC: 0.575). The precision score of the Random Forest model implies that approximately 84.2% of pedestrians may be satisfied if they walk the areas, suggested by the Random Forest model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.396-404
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• 2011

Recently, the wide spread popularity of smart phones causes the advent of various mobile applications base on the location information. Since previous pedestrian navigations are applied by extending car navigations, these are not only difficult to provide the appropriate route information, but also raise limitations in the efficient query processing by data structures of car road networks. In addition, these increase the power consumption caused by the growth of I/O frequency. In this paper, we propose a pedestrian road network model for the accurate route information and a storage structure for the pedestrian road network based on POI to reduce the I/O frequency. The proposed method enables efficient route searches over POI reflecting the characteristics and requirements of pedestrian roads. Also, a reduction of query processing costs for the route searching by a data structure considered with POI can save the power consumption more than previous approaches.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.7-8
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• 2010

Due to development of wireless environment and portable device, it is possible to use navigation out of car. Specially, pedestrians can freely walk openspace, so there are limits that we use network data of car navigation systems for pedestrian navigation systems. Therefore, in this paper, we proposed the method of generating network data for pedestrians based on the exiting spatial data sets.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.27-32
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• 2016

The global positioning system (GPS)-enabled mobile phones provide location-based applications such as car and pedestrian navigation services. The pedestrian navigation services provide safe and comfortable route and path guidance for pedestrians and handicapped or elderly people. One of the essential components for a navigation system is a spatial database used to perform navigation and routing functions. In this paper, we develop modeling and categorization of pedestrian path components for smart tour guide services using the mobile pedestrian navigation application. We create pedestrian networks using 2D base map and sky view map in urban area. We also construct pedestrian networks and attributes of node, link, and POI using on-site GPS data and photos for smart pedestrian tour guide in the major walking tourist spots in Jeju.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.335-341
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• 2018

The KDE (Kernel Density Estimation) technique in GIS (Geographic Information System) has been widely used as a method for determining whether a phenomenon occurring in space forms clusters. Most human-generated events such as traffic accidents and retail stores are distributed according to a road network. Even if events on forward and rear roads have short Euclidean distances, network distances may increase and the correlation between them may be low. Therefore, the NKDE (Network-based KDE) technique has been proposed and applied to the urban space where a road network has been developed. KDE is being studied in the field of business GIS, but there is a limit to the microscopic analysis of economic activity along a road. In this study, the NKDE technique is applied to the analysis of urban phenomena such as the density of shops rather than traffic accidents that occur on roads. The results of the NKDE technique are also compared to pedestrian networks and road centerline networks. The results show that applying NKDE to microscopic trade area analysis can yield relatively accurate results. In addition, it was found that pedestrian network data that can consider the movement of actual pedestrians are necessary for accurate trade area analysis using NKDE.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2009.04a
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• pp.7-9
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• 2009

Because unlike cars, pedestrians are not moving along the middle axis of street lanes, PNS needs more sophisticated information. So we defined the specific needs of pedestrians, analyzed already existing geodata sets and selected the reasonable layers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.269-275
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• 2013

Recently, importance of pedestrian road network is getting emphasized as it is possible to provide mobile device users with both route guidance services and surrounding spatial information. However, it costs a tremendous amount of budget for generating and renovating pedestrian road network nationally, which hinder further advances of these services. Hence, algorithms extracting pedestrian road network automatically based on raster data are needed. On the other hand, road dataset generated from raster data usually has unnecessary vertices which lead to maintenance disutility such as excessive turns and increase in data memory. Therefore, this study proposed a method of selecting a proper threshold automatically for separate road entity using not only Douglas-Peucker algorithm but also road attribute data of digital map in order to remove redundant vertices, which maximizes line simplification efficiency and minimizes distortion of shape of roads simultaneously. As a result of the test, proposed method was suitable for automatic line simplification in terms of reduction ratio of vertices and accuracy of position.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1189-1195
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• 2008

We introduce a MEMS-based pedestrian dead reckoning (PDR) system. A walking navigation algorithm for pedestrians is presented and map-matching algorithm for the navigation system based on dead reckoning (DR) is proposed. The PDR is equipped on the human body and provides the position information of pedestrians. And this is able to be used in ubiquitous sensor network (USN), U-hearth monitoring system, virtual reality (VR) and etc. The PDR detects a step using a novel technique and simultaneously estimates step length. Also an azimuth of the pedestrian is calculated using a fluxgate which is the one of magnetometers. Map-matching algorithm can be formulated to integrate the positioning data with the digital road network data. Map-matching algorithm not only enables the physical location to be identified from navigation system but also improves the positioning accuracy. However most of map-matching algorithms which are developed previously are for the car navigation system (CNS). Therefore they are not appropriate to implement to pedestrian navigation system based on DR system. In this paper, we propose walking navigation system and map-matching algorithm for PDR.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.26-32
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• 2008

A pedestrian navigation system, an information delivery server, and a program for naturally guiding (such as speech-guiding) the user of a portable terminal at an intersection. An information delivery server comprises a map database containing data such as nodes including paths constituting intersections, links, and costs of the links. The node-link structure is the most important part in pedestrian navigation system. Functional requirements for the road map database vary in different navigation phases. though there are various road network models, their traditional node-link structures, unfortunately, do not solve the problem well. This paper proposes a node-link structure for pedestrian navigation system. The network topological structure in pedestrianl network is presented, which accords with the practical walking habit better than traditional way treating the entire road network.