• Journal of Korean Port Research
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• v.14 no.3
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• pp.269-278
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• 2000

Today the pedestrian-related problems a key subject requiring the attention of the traffic engineers for improving the transportation system. Particularly in urban and CBD locations, the pedestrian presents an element of sharp conflict with vehicular traffic. Therefore pedestrian movements must be studied for the purpose of providing guideline for the design and operation of walking transportation systems. This paper is to address the characteristics of walking transportation in a big city. Especially the focuses are emphasized on the ratio occupied by pedestrian traffic among the whole unlinked trips in a city and walking time. The data for analysis are collected in Seoul metropolitan city through sampling 1,006 citizens. Compared with other similar research works this paper utilized diversified tools to acquire more useful results. Finally, policy directions for pedestrian environment improvement were suggested.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1010-1018
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• 2009

An inertial navigation system for pedestrian position tracking is proposed, where the position is computed using inertial sensors mounted on shoes. Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it needs to reset errors frequently. During normal walking, there is an almost periodic zero velocity instance when a foot touches the floor. Using this fact, estimation errors are reduced and this method is called the zero velocity updating algorithm. When implementing this zero velocity updating algorithm, it is important to know when is the zero velocity interval. The gait states are modeled as a Markov process and each state is estimated using the hidden Markov model smoother. With this gait estimation, the zero or nearly zero velocity interval is more accurately estimated, which helps to reduce the position estimation error.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.4
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• pp.315-321
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• 2017

This paper is a study on the design and realization of Pedestrian navigation service system for the visually impaired. As it is an user interface considering visually impaired, voice recognition functioned smartphone was used as the input tool and the Osteoacusis headset, which can vocally guide directions while recognizing the surrounding environment sound, was used as the output tool. Unlike the pre-existing pedestrian navigation smartphone apps, the developed system guides walking direction by the scale of the left and right stereo sound of the headset wearing, and the voice guidance about the forked or curved path is given several meters before according to the speed of the user, and the user is immediately warned of walking opposite direction or proceeding off the path. The system can acquire stable and reliable directional information using the motion tracker with the dynamic heading accuracy of 1.5 degrees. In order to overcome GPS position error, we proposed a robust trajectory planning algorithm for position error. Experimental results for the developed system show that the average directional angle error is 6.82 degrees (standard deviation: 5.98) in the experimental path, which can be stated that it stably navigated the user relatively.

• Archives of design research
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• v.20 no.3 s.71
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• pp.203-214
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• 2007

This study proposes an information retrieval method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. Firstly, the research evaluated subjects' preferences on commercial spaces set to a hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose methods of Navigation Knowledge Base (NKB). The NKB was composed of three elements; 1. the correlation model between emotional characteristics, 2. the causal relationship between visual characteristics and emotional characteristics, 3. the transformation model between visual characteristics and the physical characteristics. Secondly, this study classified the pedestrian's destination search into 4 types with his or her preferences and the time conditions limited during navigation. For each type it presented the Destination Search Algorithm (DSA). Finally, the research simulated the destination search in 4 navigation types using NKB and DSA and verified the availability of the information retrieval method reflecting pedestrian's preferences. In conclusion, the proposed information search method will be applied to reflect the user's preferences to develop information appliances.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.117-124
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• 2020

In this paper, the symmetric position drift of the integration approach in pedestrian dead reckoning (PDR) system with dual foot-mounted IMU is analyzed. The PDR system that uses the inertial sensor attached to the shoe is called the IA-based PDR system. Since this system is designed based on the inertial navigation system (INS), it has the same characteristics as the error of the INS, then zero-velocity update (ZUPT) is used to correct this error. However, an error that cannot be compensated perfectly by ZUPT exists, and the trend of the position error is the symmetric direction along the side of the shoe(left, right foot) with the IMU attached. The symmetric position error along the side of the shoe gradually increases with walking. In this paper, we analyze the causes of symmetric position drift and show the results. It suggests the possibility of factors other than the error factors that are generally considered in the PDR system based on the integration approach.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.1
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• pp.1-9
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• 2017

This paper proposes to improve the performance of a strap down inertial navigation system using a foot-mounted low-cost inertial measurement unit/magnetometer by configuring an attitude and heading reference system. To track position accurately and for attitude estimations, considering different dynamic constraints, magnetic measurement and a zero velocity update technique is used. A conventional strap down method based on integrating angular rate to determine attitude will inevitably induce long-term drift, while magnetometers are subject to short-term orientation errors. To eliminate this accumulative error, and thus, use the navigation system for a long-duration mission, a hybrid configuration by integrating a miniature micro electromechanical system (MEMS)-based attitude and heading detector with the conventional navigation system is proposed in this paper. The attitude and heading detector is composed of three-axis MEMS accelerometers and three-axis MEMS magnetometers. With an absolute algorithm based on gravity and Earth's magnetic field, rather than an integral algorithm, the attitude detector can obtain an absolute attitude and heading estimation without drift errors, so it can be used to adjust the attitude and orientation of the strap down system. Finally, we verify (by both formula analysis and from test results) that the accumulative errors are effectively eliminated via this hybrid scheme.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.251-256
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• 2006

In the work package 'Integrated Positioning' of the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environements) we are dealing with the navigation and guidance of visitors of our University. Thereby start points are public transport stops in the surroundings of the Vienna University of Technology and the user of the system should be guided to certain office rooms or persons. For the position determination of the user different location sensors are employed, i.e., for outdoor positioning GPS and dead reckoning sensors such as a digital compass and gyro for heading determination and accelerometers for the determination of the travelled distance as well as a barometric pressure sensor for altitude determination and for indoor areas location determination using WiFi fingerprinting. All sensors and positioning methods are combined and integrated using a Kalman filter approach. Then an optimal estimate of the current location of the user is obtained using the filter. To perform an adequate weighting of the sensors in the stochastic filter model, the sensor characteristics and their performance was investigated in several tests. The tests were performed in different environments either with free satellite visibility or in urban canyons as well as inside of buildings. The tests have shown that it is possible to determine the user's location continuously with the required precision and that the selected sensors provide a good performance and high reliability. Selected tests results and our approach will be presented in the paper.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.810-815
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• 2013

In case Wi-Fi network based First responder's position tracking system is used, range measurement must be generated from RSSI finger print database. However, it is impossible to build up finger print database and to perform rescue operation at same time in the scene of rescue. In this paper, improvised Wi-Fi network without finger print database and pedestrian dead reckoning based first responders tracking system is proposed.

• 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.