• Title/Summary/Keyword: travel time method

Search Result 460, Processing Time 0.029 seconds

A Study of the Value of Travel Time Reliability (통행시간 신뢰성 가치에 관한 연구)

  • Cho, Hanseon
    • International Journal of Highway Engineering
    • /
    • v.15 no.4
    • /
    • pp.155-165
    • /
    • 2013
  • PURPOSES : Benefits for improvement of travel time reliability obtained from construction of new highways should be considered as a major factor in the feasibility study for highway constructions. The purpose of this study is to develop a method of estimation for the value of travel time reliability. METHODS : Highway type (urban/rural highway) and traffic flow type(interrupted/uninterrupted) was considered to estimate he value of travel time reliability. And Double-bounded Dichotomous Choice among Contingent Valuation Method(CVM) was applied to survey the willingness-to-pay of drivers when travel time reliability is improved. Finally the value of travel time reliability was estimated using the results of survey and logit model. The value of travel time reliability was estimated considering travel objectives, time constraint travel and non-time constraint travel. RESULTS: The value of travel time reliability of business trip is higher than that of non-business trip. The value of travel time reliability of time constraint travel is higher than that of non-time constraint travel. The value of travel time reliability in urban area is higher than that in rural area. CONCLUSIONS: It was concluded that the proposed method in this study is more realistic and proper to estimate the value of travel time reliability because it reflects the situations of time constraint travel and non-time constraint travel.

A study on the determination of Ultrasonic Travel Time by Norm Phase-Time Method (위상시간법에 의한 초음파전파시간의 결정에 관한 연구)

  • 이은방
    • Journal of the Korean Institute of Navigation
    • /
    • v.18 no.4
    • /
    • pp.137-146
    • /
    • 1994
  • In this paper, a new algorithm to measure the ultrasonic travel time is proposed, which is fundamental to estimate distance depth and volume in several media. Pulse wave has been used to measure travel time of transmitted signal. However, due to the characteristic of transducer and propagation, the received signal is so distorted that it is difficult to measure travel time, which is propagation, the received signal is so distorted that it is difficult to measure travel time, which is to be time difference between transmitted and received signals. In this proposed method, transmitted and received signal are transformed respectively into norm phase newly designed by this paper and displayed on phase-time curve. And travel time is simply determined by the arithmetic numerical mean of time difference at the identical norm phase on the phase-time curves of transmitted and received signals. This method has several features; firstly, travel time is calculated analytically with high accuracy by least square error method, secondly, it is useful to compare the difference of signal magnitude for time information, thirdly, noise and discrete errors are relatively small, finally, the measurement accuracy is not influenced by D.C. bias. In particular, this method is useful and applicable to measuring very short distance and sound speed with high accuracy.

  • PDF

A Study of Travel Time Prediction using K-Nearest Neighborhood Method (K 최대근접이웃 방법을 이용한 통행시간 예측에 대한 연구)

  • Lim, Sung-Han;Lee, Hyang-Mi;Park, Seong-Lyong;Heo, Tae-Young
    • The Korean Journal of Applied Statistics
    • /
    • v.26 no.5
    • /
    • pp.835-845
    • /
    • 2013
  • Travel-time is considered the most typical and preferred traffic information for intelligent transportation systems(ITS). This paper proposes a real-time travel-time prediction method for a national highway. In this paper, the K-nearest neighbor(KNN) method is used for travel time prediction. The KNN method (a nonparametric method) is appropriate for a real-time traffic management system because the method needs no additional assumptions or parameter calibration. The performances of various models are compared based on mean absolute percentage error(MAPE) and coefficient of variation(CV). In real application, the analysis of real traffic data collected from Korean national highways indicates that the proposed model outperforms other prediction models such as the historical average model and the Kalman filter model. It is expected to improve travel-time reliability by flexibly using travel-time from the proposed model with travel-time from the interval detectors.

AGV travel time estimation for an AGV-based transport system (AGV기반 운반체계에서의 차량이동시간에 관한 연구)

  • 구평회;장재진
    • Proceedings of the Korean Operations and Management Science Society Conference
    • /
    • 2000.04a
    • /
    • pp.5-8
    • /
    • 2000
  • Vehicle travel time (empty travel time pius loaded travel time) is a key parameter for designing AGV-based material handling systems. Especially, the determination of empty vehicle travel time is difficult because of the stochastic nature of the empty vehicle locations. This paper presents a method to estimate vehicle travel times for AGV-based material transport systems. The model considers probabilistic aspects for the travel time and vehicle location under random vehicle selection rule and nearest vehicle selection rule. The estimation of empty travel time is of major effort. Simulation experiments are used to verify the proposed travel time model, and the simulation results show that the presented model provides reasonable travel time estimations.

  • PDF

Model of Simultaneous Travel time and Activity Duration for worker with Transportation Panel Data

  • Kim Soon-Gwan
    • Proceedings of the KOR-KST Conference
    • /
    • 1998.09a
    • /
    • pp.160-167
    • /
    • 1998
  • Recent world-wide interest in activity-based travel behavior modeling has generated an entirely new perspective on how the profession views the travel demand process. This paper seeks to further promote the case of activity-based travel behavior models by providing some empirical evidence of relationship between travel time and activity duration decision for worker with transportation panel data. The travel time from home to work and from work to home, without activity involvement, is estimated by the Ordinary Least Squares (OLS) method. And, the travel time to and from the selected activity and the activity duration are modeled simultaneously by the Three Stage Least Squares (3SLS) method due to the endogenous relationship between travel time and activity duration. Two kinds of models, OLS and 3SLS, include selectivity bias corrections in a discrete/continuous framework, because of the inter-relationship between the choice of activity type/travel mode (discrete) and the travel time/activity duration (continuous). Estimation is undertaken using a sample of over 1300 household two-day trip diaries collected from the same travelers in the Seattle area in 1989. The behavioral consequences of these models provide interesting and provocative findings that should be of value to transportation policy formulation and analysis.

  • PDF

An Expressway Path Travel Time Estimation Using Hi-pass DSRC Off-Line Travel Data (하이패스 DSRC 자료를 활용한 고속도로 오프라인 경로통행시간 추정기법 개발)

  • Shim, Sangwoo;Choi, Keechoo;Lee, Sangsoo;NamKoong, Seong J.
    • Journal of Korean Society of Transportation
    • /
    • v.31 no.3
    • /
    • pp.45-54
    • /
    • 2013
  • Korea Expressway Corporation has been utilizing vehicles equipped with dedicated short range communication (DSRC) based on-board equipment (OBE) for collecting path travel times. A path based method (PBM) estimates the path travel time using probe vehicles traveling whole links on the path, so it is not always possible to obtain sufficient samples for calculating path travel time in the DSRC system. Having this problem in utilizing DSRC for travel time information, this study attempted to estimate path travel time with the help of a link based method (LBM) and examined whether the LBM can be used for obtaining reliable path travel times. Some comparisons were made and identified that the MAPE difference between the LBM and the PBM estimates are less than 3%, signaling that LBM can be used as a proxy for PBM in case of sparse sample conditions. Some limitations and a future research agenda have also been proposed.

Link Travel Time Estimation Using Uncompleted Link-passing GPS Probe Data in Congested Traffic Condition (혼잡상황에서 링크미통과 GPS 프로브데이터를 활용한 링크통행시간 추정기법 개발)

  • Sim, Sang-U;Choe, Gi-Ju
    • Journal of Korean Society of Transportation
    • /
    • v.24 no.5 s.91
    • /
    • pp.7-18
    • /
    • 2006
  • Data for travel information Provision are regularly aggregated to Provide travel time information in a reliable and convenient manner and to manage traffic data and information efficiently. In most of practices in Korea, the GPS based travel time data are mainly aggregated every 5 minutes As a result, some probes can't pass by a link within aggregation interval and thereby create uncompleted link passing data. But these data are mostly generated during the congested times and therefore a method that uses such uncompleted link passing data are required. This study estimated queue dissipation length, green time and cycle that use GPS spot speed and developed a link travel time estimation method using such uncompleted link passing data. It also presents method and the overall process of using such data to estimate link travel time in a more accurate manner. As a result, MAPE 1.98% and MAE 4.75 sec of link travel time accuracy improvement has been reported, which is not much different from the real link travel time. The method Proposed here would be an alternative to increase the amount of GPS probe data, especially in congested urban arterial case.

Expressway Travel Time Prediction Using K-Nearest Neighborhood (KNN 알고리즘을 활용한 고속도로 통행시간 예측)

  • Shin, Kangwon;Shim, Sangwoo;Choi, Keechoo;Kim, Soohee
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.34 no.6
    • /
    • pp.1873-1879
    • /
    • 2014
  • There are various methodologies to forecast the travel time using real-time data but the K-nearest neighborhood (KNN) method in general is regarded as the most one in forecasting when there are enough historical data. The objective of this study is to evaluate applicability of KNN method. In this study, real-time and historical data of toll collection system (TCS) traffic flow and the dedicated short range communication (DSRC) link travel time, and the historical path travel time data are used as input data for KNN approach. The proposed method investigates the path travel time which is the nearest to TCS traffic flow and DSRC link travel time from real-time and historical data, then it calculates the predicted path travel time using weight average method. The results show that accuracy increased when weighted value of DSRC link travel time increases. Moreover the trend of forecasted and real travel times are similar. In addition, the error in forecasted travel time could be further reduced when more historical data could be available in the future database.

A Study on the Static Correction for the First Arrival Travel-time of the Cross-well Seismic Data (시추공 탄성파 초동주시 기록의 정보정 연구)

  • Lee, Doo-Sung
    • Geophysics and Geophysical Exploration
    • /
    • v.14 no.2
    • /
    • pp.146-151
    • /
    • 2011
  • A method to evaluate and to reduce the source- and receiver- consistent noise in a cross-well travel time data was proposed. These systematic noises, which can cause some serious effects on the result of a travel time tomography, can be considered as the source and receiver statics. The method evaluates the statics through a curve-fitting of the first arrival travel times in the common source and common receiver gathers. Feasibility study was conducted on a synthetic data which simulates the cross-well travel time tomography to detect a small scale tunnel in a uniform background medium. First arrival travel times at a given source and receiver points are computed by a raytracing method, and the source consistent- and receiver consistent noises are added to the record. In case of the added noise with rms amounting to 25% of the maximum expected anomalous travel time delays, it is confirmed that the method successfully extracted the noise at the 7th step of iteration.

Estimation of Predictive Travel Times Using Ubiquitous Traffic Environment under Incident Conditions (유비쿼터스 환경에서 돌발상황 발생 시 예측적 통행시간 추정기법)

  • Park, Joon-Hyeong;Hong, Seung-Pyo;Oh, Cheol;Kim, Tae-Hyeong;Kim, Won-Kyu
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.8 no.2
    • /
    • pp.14-26
    • /
    • 2009
  • This study presented a novel method to estimate travel times under incident conditions. Predictive travel time information was defined and evaluated with the proposed method. The proposed method utilized individual vehicle speeds obtained from global positioning systems (GPS) and inter-vehicle communications(IVC) for more reliable real-time travel times. Individual vehicle trajectory data were extracted from microscopic traffic simulations using AIMSUN. Market penetration rates (MPR) and IVC ranges were explored with the accuracy of travel times. Relationship among travel time accuracy, IVC ranges, and MPR were further identified using regression analyses. The outcomes of this study would be useful to derive functional requirements associated with traffic information systems under forthcoming ubiquitous transportation environment

  • PDF