• Title/Summary/Keyword: Bus arrival information

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Self-powered wireless bus information and disaster information system based on Internet of Things (IoT) (사물인터넷 기반의 자가 전력을 이용한 무선 버스 정보 및 재난 정보 시스템)

  • Kim, Tae-Kook
    • Journal of Internet of Things and Convergence
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    • v.8 no.1
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    • pp.17-22
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    • 2022
  • This paper is a study on the self-powered wireless bus information and disaster information system based on Internet of Things (IoT). The existing bus information system supplies power and communication by cable, which causes a problem of increased installation cost and limited installation site due to cable burial. To solve this problem, a self-powered wireless bus information and disaster information system was proposed. The proposed system provides bus arrival information. Furthermore, in the event of a disaster such as a natural disaster, it can also reduce confusion and damage by notifying the disaster information through the system's speaker. In this study, a self-powered system using a solar module was proposed. As data are transmitted and received through wireless WiFi or LTE, the installation cost can be reduced and the problem of installation location restrictions can be solved.

Comparison of Deep Learning Algorithm in Bus Boarding Assistance System for the Visually Impaired using Deep Learning and Traffic Information Open API (딥러닝과 교통정보 Open API를 이용한 시각장애인 버스 탑승 보조 시스템에서 딥러닝 알고리즘 성능 비교)

  • Kim, Tae hong;Yeo, Gil Su;Jeong, Se Jun;Yu, Yun Seop
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.388-390
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    • 2021
  • This paper introduces a system that can help visually impaired people to board a bus using an embedded board with keypad, dot matrix, lidar sensor, NFC reader, a public data portal Open API system, and deep learning algorithm (YOLOv5). The user inputs the desired bus number through the NFC reader and keypad, and then obtains the location and expected arrival time information of the bus through the Open API real-time data through the voice output entered into the system. In addition, by displaying the bus number as the dot matrix, it can help the bus driver to wait for the visually impaired, and at the same time, a deep learning algorithm (YOLOv5) recognizes the bus number that stops in real time and detects the distance to the bus with a distance detection sensor such as lidar sensor.

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Determining locations of bus information terminals (BITs) in rural areas based on a passenger round-trip pattern (왕복통행 특성을 이용한 지방부 버스정보안내기(BIT) 지점 선정)

  • Kim, Hyoung-Soo;Kim, Eung-Cheol
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.2
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    • pp.1-9
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    • 2012
  • This study proposed a method to determine the number and location of bus information terminals (BIT), which is a device to provide passengers with bus arrival time at bus stops in a Bus Information System (BIS). In low-density area, it is not efficient to survey bus demands such as the number of passengers at all bus stops due to time and cost. This kind of a survey would, however, competently cover all bus stops if performed inside the bus. The number of riding-on and -off passengers is observed for every bus stop, and this data collection is repeated over all day. Data obtained from the survey are aggregated each bus stop. This study defines Utility Index (UI), an aggregate each bus stop. Bus stops are ranked according to UI and determined for a BIT within budget limitation. As a case study, a bus line in Jeju island, Korea, was dealt with. This case showed that the more aggregate the better data quality. This study is expected to contribute to solving a location problem of BITs in a BIS.

Study on the Optimum Route Travel Time for Bus to Improve Bus Schedule Reliability (정시성 확보를 위한 버스노선 당 적정 운행시간 산정 연구)

  • Kim, Min ju;Lee, Young ihn
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.6
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    • pp.112-123
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    • 2017
  • The accurate forecasting of the public transportation's transit and arrival time has become increasingly important as more people use buses and subways instead of personal vehicles under the government's public transportation promotion policy. Using bus management system (BMS) data, which provide information on the real-time bus location, operation interval, and operation history, it is now possible to analyze the bus schedule reliability. However, the punctuality should always be considered together with the operation safety. Therefore, this study suggests a new methodology to secure both reliability and safety using the BMS data. Unlike other studies, we calculated the bus travel time between two bus stops by dividing the total travel length into 6 sections using 5 different measuring points. In addition, the optimal travel time for each bus route was proposed by analyzing the mean, standard deviation and coefficient of variation of the each section's measurement. This will ensure the reliability, safety and mobility of the bus operation.

Prediction of Bus Arrival Time for Efficient Transit Planning (효율적 환승을 위한 버스도착시간의 예측)

  • Byun, Sejung;Lee, Junghoon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.05a
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    • pp.338-339
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    • 2021
  • 본 논문에서는 제주시에서 오픈데이터로 공개한 버스탑승 기록을 기반으로 이용도가 높은 버스노선에 대해 특정정류장에서의 도착시간 예측모델을 구축한다. 버스들의 평균주행 속도, 운행시간대, 교통량 등을 입력으로 한 모델을 Sklearn을 이용하여 생성하고 MAE와 손실율 등의 성능을 분석한다.

Quality Control Scheme of GIS-based Bus Network for Stabilization of BIS - Focusing on Real-Time Public Transportation Information (BIS 안정화를 위한 버스기반정보 GIS DB 품질 관리 방안 - 실시간 환승교통 종합정보 시스템을 사례로)

  • Ju, Yong-Jin;Ham, Chang-Hak
    • Journal of Korean Society for Geospatial Information Science
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    • v.20 no.1
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    • pp.33-41
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    • 2012
  • BIS is an arrival guidance system which is able to supply passengers with bus service condition via Kiosks at a bus stop, internet and mobile service through pinpointing bus location in real time. It is very significant to improve the quality of traffic information by quality control of GIS-based bus network so as to maintain navigational information and to implement reliable BIS. Therefore this study aims to build criteria to quantitatively evaluate data quality of the product in accordance with the process in bus network data and to suggest guideline of quality control. To achieve this, we have categorized geometric and logical errors occurring during constructing bus network database by giving a specific case study on TAGO and set up sectional guideline and procedures to examine database for systematic and coherent quality control management. Proceeding from what has been said above, the outcome of our research leads to quality guarantee for objective and reliable bus network database and is fully expected to bring benefit of providing a more accurate public transportation information and improving reliability of BIS through preventing a variety of errors in system operation in advance.

The Analysis of Priority Output Queuing Model by Short Bus Contention Method (Short Bus contention 방식의 Priority Output Queuing Model의 분석)

  • Jeong, Yong-Ju
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.2
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    • pp.459-466
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    • 1999
  • I broadband ISDN every packet will show different result if it would be processed according to its usage by the server. That is, normal data won't show big differences if they would be processed at normal speed. But it will improve the quality of service to process some kinds of data - for example real time video or voice type data or some data for a bid to by something through the internet - more fast than the normal type data. solution for this problem was suggested - priority packets. But the analyses of them are under way. Son in this paper a switching system for an output queuing model in a single server was assumed and some packets were given priorities and analysed. And correlation, simulating real life situation, was given too. These packets were analysed through three cases, first packets having no correlation, second packets having only correlation and finally packets having priority three cases, first packets having no correlation, second packets having only correlation and finally packets having priority and correlation. The result showed that correlation doesn't affect the mean delay time and the high priority packets have improved mean delay time regardless of the arrival rate. Those packets were assumed to be fixed-sized like ATM fixed-sized cell and the contention strategy was assumed to be short bus contention method for the output queue, and the mean delay length and the maximum 버퍼 length not to lose any packets were analysed.

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Design and Implementation of Bus notification using IoT and location information (IoT 및 위치 정보를 활용한 버스 알리미 설계 및 구현)

  • Lee, Yeeun;Kim, Eunyoung;Yun, Hyejin;Kim, Jiyoun;Kwon, Koojoo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.292-295
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    • 2020
  • In the modern society, people can easily reach destination by using the rapidly developed public transportation services. Recently, location information is provided through the network, but this is useless to the weak people on transportation like the handicapped. This paper proposes a bus alert terminal system equipped with the arrival information of public buses based on location information and distance measurement sensor. By using this system, we look forward to providing more convenient and accessible services for the weak people on transportation.

A Study on Traffic Analysis Using Bus Information System (버스정보시스템을 이용한 교통흐름 분석에 관한 연구)

  • Kim, Hong Geun;Park, Chul Young;Shin, Dong Chul;Shin, Chang Sun;Cho, Yong Yun;Park, Jang Woo
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.9
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    • pp.261-268
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    • 2016
  • One of the most comfortable transportation in our day to day life is the bus, which provides real time information. In order to obtain reliable information on the arrival time of this information, BIS (Bus Information System) needs to analyse the main factor for the traffic environment. To manage the system, regional information analysis by local municipalities should be prioritized. In this paper, we analyse the features that are expected to affect traffic environment by commuting the travel to school, market, tourism and other influences around Suncheon-si, which has the facilities for education, tourism and urban locality. Data cleaning is performed on the DB information that is being collected from characterization BIS, which is organized by day of the week, day and month, to analyse the key factors of the traffic flow. If this is utilized by applying a key factor to the real time information, it is expected to provide more reliable and accurate information.

Long-Term Arrival Time Estimation Model Based on Service Time (버스의 정차시간을 고려한 장기 도착시간 예측 모델)

  • Park, Chul Young;Kim, Hong Geun;Shin, Chang Sun;Cho, Yong Yun;Park, Jang Woo
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.7
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    • pp.297-306
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    • 2017
  • Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.