• Title/Summary/Keyword: bus travel

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Develpment of Analysis and Evaluation Model for a bus Transit Route Network Design (버스 노선망 설계를 위한 평가모형 개발)

  • Han, Jong-Hak;Lee, Seung-Jae;Kim, Jong-Hyeong
    • Journal of Korean Society of Transportation
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    • v.23 no.2
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    • pp.161-172
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    • 2005
  • This study is to develop Bus Transit Route Analysis and Evaluation Model that can product the quantitative performance measures for Bus Transit Route Network Design. So far, in Korea, there are no so many models that evaluate a variety of other performance measures or service quality that are of concern to both the transit users and operator because of lower-level bus database system and transit route network analysis algorithm's limit. The BTRAEM in this research differ from the previous approach in that the BTRAEM employs a multiple path transit trip assignment model that explicitly considers the transfer and different travel time after boarding. And we develop input-output data structure and quantitative performance measure for the BTRAEM. In the numerical experimental applying BTRAEM to Mandl transit network, We got the meaningful results on performance measure of bus transit route network. In the future, we expect BTRAEM to give a good solution in real transit network.

A Study on Travel Pattern Analysis and Political Application using Transportation Card Data: In Gyeonggi-Do Case (교통카드자료를 이용한 통행패턴분석과 정책활용방안 연구 -경기도를 중심으로-)

  • Bin, Miyoung;Moon, Juback;Joh, Chang-Hyeon
    • Journal of the Economic Geographical Society of Korea
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    • v.15 no.4
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    • pp.615-627
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    • 2012
  • This study analyzed the travel pattern with respect to use of public transportation by using transportation card data and presented the measures that can be used in a traffic policy. Transportation card data targeted Gyeonggi-Do area and as a utilization plan, a scenario that when a traffic policy decision maker improves bus stop facilities, the person selects a target site by using several variables that can be obtained from transportation card data was set and analyzed. The analysis result showed that K means cluster analysis which is decision making methodology and CHAID(Chi-squared automatic interaction detection) were used and it can be used usefully in policies in significance level of p <0.01. Also, based on these results, this study presented policy implications to be improved to actually use transportation card data in policies.

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A Study on the Analysis of Spatial Characteristics with Respect to Regional Mobility Using Clustering Technique Based on Origin-Destination Mobility Data (기종점 모빌리티 데이터 기반 클러스터링 기법을 활용한 지역 모빌리티의 공간적 특성 분석 연구)

  • Donghoun Lee;Yongjun Ahn
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.1
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    • pp.219-232
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    • 2023
  • Mobility services need to change according to the regional characteristics of the target service area. Accordingly, analysis of mobility patterns and characteristics based on Origin-Destination (OD) data that reflect travel behaviors in the target service area is required. However, since conventional methods construct the OD data obtained from the administrative district-based zone system, it is hard to ensure spatial homogeneity. Hence, there are limitations in analyzing the inherent travel patterns of each mobility service, particularly for new mobility service like Demand Responsive Transit (DRT). Unlike the conventional approach, this study applies a data-driven clustering technique to conduct spatial analyses on OD travel patterns of regional mobility services based on reconstructed OD data derived from re-aggregation for original OD distributions. Based on the reconstructed OD data that contains information on the inherent feature vectors of the original OD data, the proposed method enables analysis of the spatial characteristics of regional mobility services, including public transit bus, taxi and DRT.

Study on the Social Value of Public Transport Comfort in Financial Investment Projects (재정투자사업의 쾌적성에 대한 사회적 가치 연구 : 광역버스의 차내 혼잡을 중심으로)

  • Heo Eun Jin;Kim Sung Soo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.1
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    • pp.52-64
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    • 2023
  • This paper concentrated on estimating the travel time value of individual regional bus passengers in various in-vehicle crowding conditions. In the analysis model, the traffic-selection data of individual transportation passengers based on smart-card data were used. Variables which reflect the level of in-vehicle crowding and the variables of in-vehicle travel time that reflect the level of in-vehicle crowding were included in the model using Box-Cox transformation. The result of this paper indicates that the travel time value experienced by individual users would increase as the in-vehicle crowding level increases. The smart card data used in this paper is considered to have significant implications in terms of conducting more sophisticated and realistic qualitative research to reflect the values of variables for in-vehicle traffic hours and in-vehicle crowding levels, which previously had limitations in observation and quantification. It is expected that the effects of improvement measures for reducing congestion on regional buses can be considered quantitatively by applying the estimation results of crowding multiplier.

A Proposal for expansion of the low-floor bus based on analysis of living area for the handicapped mobility people in Seoul Using R (R을이용한 서울시 교통약자 생활권 분석에 따른 저상버스 확대 제안)

  • Yun, Sang-hee;Kim, Jeong-joon;Jeon, Gwang-il
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.6
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    • pp.195-201
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    • 2017
  • As of 2016, the total traffic usage of handicapped people were 24.8%. Buses (25.6%) have the highest rate of travel, with the exception of "walking (33.5%)" as the main means of transportation for these handicapped people. Therefore, the Seoul Metropolitan Government expanded the low-floor bus, which is a means of transportation for the underbelly, to 30% by 2015, but the satisfaction level of mobility improvement of the underbelly was only 2% To 55%. In fact, increasing the percentage of low-floor buses is merely a superficial solution, and there are many restrictions on solving fundamental problems with limited budgets. Therefore, in this study, we use statistical analysis R, with a simple data manipulation and visualization function, to grasp the living area and life pattern of handicapped people in Seoul city.

A Study on the GIS Analysis Techniques for Finding an Catchment Area by Public Transport at Railway Stations Using Transport Cards Big Data (교통카드 빅 데이터를 활용한 철도역의 대중교통 연계영향권 설정을 위한 GIS 분석 기법 연구)

  • Jin, Sang Kyu;Kim, Hawng Bae
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.36 no.6
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    • pp.1093-1099
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    • 2016
  • Currently, there are 499 metropolitan subway stations in Korea, but there are not many studies on the influence zone of linkage between railway station and public transport. Existing studies have been studied almost in terms of accessibility.. In addition, the existing research on the influence zone of linkage using survey data and statistics, there is a limit to the theoretical basis and analysis techniques. In this paper, we propose a new method to select on the influence zone of linkage, It is a GIS analysis technique using the spatial data of the railway station user as the large data of the traffic card. We applied the GIS analysis technique for select the influence zone of linkage based on the travel time of the network for each public transportation system. As a result, it was confirmed that the influence of the link of 15 minutes on the local bus, 20 minutes on the city bus and 25 minutes on the intercity bus were clearly distinguished according to the difference in network access time.

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.

A Heuristic Optimal Path Search Considering Cumulative Transfer Functions (누적환승함수를 고려한 경험적 최적경로탐색 방안)

  • Shin, Seongil;Baek, Nam Cheol;Nam, Doo Hee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.3
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    • pp.60-67
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    • 2016
  • In cumulative transfer functions, as number of transfer increase, the impact of individual transfer to transfer cost increase linearly or non linearly. This function can effectively explain various passengers's travel behavior who choose their travel routes in integrated transit line networks including bus and railway modes. Using the function, it is possible to simulate general situations such that even though more travel times are expected, less number of transfer routes are preferred. However, because travel cost with cumulative transfer function is known as non additive cost function types in route search algorithms, finding an optimal route in integrated transit networks is confronted by the insolvable enumeration of all routes in many cases. This research proposes a methodology for finding an optimal path considering cumulative transfer function. For this purpose, the reversal phenomenon of optimal path generated in route search process is explained. Also a heuristic methodology for selecting an optimal route among multiple routes predefined by the K path algorithm. The incoming link based entire path deletion method is adopted for finding K ranking path thanks to the merit of security of route optimality condition. Through case studies the proposed methodology is discussed in terms of the applicability of real situations.

Characteristics Analysis of Traffic Flow in BRT section according to Market Penetration Rates of Autonomous Vehicles (자율주행자동차 혼입률에 따른 BRT 구간 교통류 특성 분석)

  • Do, Myungsik;Chae, Un Hyeok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.44 no.4
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    • pp.531-544
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    • 2024
  • The purpose of this study is to analyze traffic flow characteristics according to the market penetration rate (MPR) of autonomous vehicles (AV) on road sections where bus rapid transit (BRT) is actually operating. Furthermore, the maximum traffic volume was set through estimation of future traffic demand, and traffic flow characteristics were analyzed through traffic simulation for each scenario considering of a combination of BRT introduction and AV's MPR. To test statistical significance, Kruskal-Willis test and Jonckheere-Terpstra test were used to examine the impact of the market penetration rate of Autonomous vehicles on travel time and delay time etc. At the same time, the existence of the order relationship among travel time data according to the market penetration rate of autonomous vehicle was examined. As a result of the analysis, it was founded that the travel time significantly decreased as the MPR of AV increases in both intermittent flow and continuous flow environments. In particular, in the case of continuous flow, the law of increasing returns was satisfied in the effect of increasing travel speed and reducing travel time as the MPR of AV increases. The results of this study are expected to be used as a basic information for design plans for road reconstruction and space utilization after the commercialization of AV in the future.

Arrival Time Estimation for Bus Information System Using Hidden Markov Model (은닉 마르코프 모델을 이용한 버스 정보 시스템의 도착 시간 예측)

  • 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.4
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    • pp.189-196
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    • 2017
  • BIS(Bus Information System) provides the different information related to buses including predictions of arriving times at stations. BIS have been deployed almost all cities in our country and played active roles to improve the convenience of public transportation systems. Moving average filters, Kalman filter and regression models have been representative in forecasting the arriving times of buses in current BIS. The accuracy in prediction of arriving times depends largely on the forecasting algorithms and traffic conditions considered when forecasting in BIS. In present BIS, the simple prediction algorithms are used only considering the passage times and distances between stations. The forecasting of arrivals, however, have been influenced by the traffic conditions such as traffic signals, traffic accidents and pedestrians ets., and missing data. To improve the accuracy of bus arriving estimates, there are big troubles in building models including the above problems. Hidden Markov Models have been effective algorithms considering various restrictions above. So, we have built the HMM forecasting models for bus arriving times in the current BIS. When building models, the data collected from Sunchean City at 2015 have been utilized. There are about 2298 stations and 217 routes in Suncheon city. The models are developed differently week days and weekend. And then the models are conformed with the data from different districts and times. We find that our HMM models can provide more accurate forecasting than other existing methods like moving average filters, Kalmam filters, or regression models. In this paper, we propose Hidden Markov Model to obtain more precise and accurate model better than Moving Average Filter, Kalman Filter and regression model. With the help of Hidden Markov Model, two different sections were used to find the pattern and verified using Bootstrap process.