Fusing Loop Detector and Probe Vehicle Data to Estimate Travel Time Statistics on Signalized Urban Networks

This article presents a methodology that integrates cumulative plots with probe vehicle data for estimation of travel time statistics (average, quartile) on urban networks. The integration reduces relative deviation among the cumulative plots so that the classical analytical procedure of defining the area between the plots as the total travel time can be applied. For quartile estimation, a slicing technique is proposed. The methodology is validated with real data from Lucerne, Switzerland and it is concluded that the travel time estimates from the proposed methodology are statistically equivalent to the observed values.

[1]  Carlos F. Daganzo,et al.  Fundamentals of Transportation and Traffic Operations , 1997 .

[2]  R. Jayakrishnan,et al.  Bayesian Mixture Model for Estimating Freeway Travel Time Distributions from Small Probe Samples from Multiple Days , 2009 .

[3]  Nour-Eddin El Faouzi.  Data fusion in road traffic engineering: an overview , 2004 .

[4]  Nagui M. Rouphail,et al.  OVERFLOW QUEUES AND DELAYS WITH RANDOM AND PLATOONED ARRIVALS AT SIGNALIZED INTERSECTIONS , 1994 .

[5]  Ashish Bhaskar,et al.  Analytical modeling and sensitivity analysis for travel time estimation on signalized urban networks , 2008 .

[6]  Stephen G. Ritchie,et al.  Field Investigation of Advanced Vehicle Reidentification Techniques and Detector Technologies - Phase 1 , 2002 .

[7]  R Akcelik,et al.  THE HIGHWAY CAPACITY MANUAL DELAY FORMULA FOR SIGNALIZED INTERSECTIONS , 1988 .

[8]  Donald J Dailey,et al.  A statistical algorithm for estimating speed from single loop volume and occupancy measurements , 1999 .

[9]  N. Rouphail,et al.  Estimation of delays at traffic signals for variable demand conditions , 1993 .

[10]  Nagui M. Rouphail,et al.  Data Fusion Algorithm for ADVANCE Release 1.5 , 1995 .

[11]  Keechoo Choi,et al.  A Data Fusion Algorithm for Estimating Link Travel Time , 2002, J. Intell. Transp. Syst..

[12]  黒田 孝次,et al.  Highway Capacity Manual改訂の動向--テイラ-教授の講演より , 1984 .

[13]  Nagui M. Rouphail,et al.  ANALYSIS OF CORRELATION BETWEEN ARTERIAL TRAVEL TIME AND DETECTOR DATA FROM SIMULATION AND FIELD STUDIES , 1994 .

[14]  J. Wielinski,et al.  Annual Meeting of the Transportation Research Board , 2010 .

[15]  C P Young.  A RELATIONSHIP BETWEEN VEHICLE DETECTOR OCCUPANCY AND DELAY AT SIGNAL-CONTROLLED JUNCTIONS , 1988 .

[16]  R Akcelik,et al.  Travel time functions for transport planning purposes: Davidson's function, its time dependent form and alternative travel time function , 1991 .

[17]  Nagui M. Rouphail,et al.  TOWARD THE USE OF DETECTOR OUTPUT FOR ARTERIAL LINK TRAVEL TIME ESTIMATION: A LITERATURE REVIEW , 1994 .

[18]  A. Bhaskar.  A methodology (CUPRITE) for urban network travel time estimation by integrating multisource data , 2009 .

[19]  John W. Polak,et al.  Modeling Urban Link Travel Time with Inductive Loop Detector Data by Using the k-NN Method , 2005 .

[20]  Donald R. Drew,et al.  TRAFFIC DYNAMICS: METHOD FOR ESTIMATING FREEWAY TRAVEL TIMES IN REAL TIME FROM FLOW MEASUREMENTS , 1996 .

[21]  Nour-Eddin El Faouzi.  Data-driven aggregative schemes for multisource estimation fusion: a road travel time application , 2004 .

[22]  Hojjat Adeli,et al.  Neural network model for rapid forecasting of freeway link travel time , 2003 .

[23]  Xiaoyan Zhang,et al.  Short-term travel time prediction , 2003 .

[24]  P Tisato.  Suggestions for an improved Davidson travel time function , 1991 .

[25]  H E Gault.  AN ON-LINE MEASURE OF DELAY IN ROAD TRAFFIC COMPUTER-CONTROLLED SYSTEM , 1981 .

[26]  Tschangho John Kim,et al.  Development and evaluation of a hybrid travel time forecasting model , 2000 .

[27]  Eleni I. Vlahogianni,et al.  Temporal Evolution of Short‐Term Urban Traffic Flow: A Nonlinear Dynamics Approach , 2008, Comput. Aided Civ. Infrastructure Eng..

[28]  Eleni I. Vlahogianni,et al.  Short‐term traffic forecasting: Overview of objectives and methods , 2004 .

[29]  Heinz Spiess,et al.  Technical Note - Conical Volume-Delay Functions , 1990, Transp. Sci..

[30]  Elsevier Sdol,et al.  Transportation Research Part C: Emerging Technologies , 2009 .

[31]  R Akcelik.  A NEW LOOK AT DAVIDSON'S TRAVEL TIME FUNCTION , 1978 .

[32]  Khaled Hamad,et al.  Near‐Term Travel Speed Prediction Utilizing Hilbert–Huang Transform , 2009, Comput. Aided Civ. Infrastructure Eng..

[33]  Hashem R Al-Masaeid,et al.  Short-Term Prediction of Traffic Volume in Urban Arterials , 1995 .

[34]  Hao Liu,et al.  Prediction of urban travel times with intersection delays , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[35]  S. Robinson.  The development and application of an urban link travel time model using data derived from inductive loop detectors , 2007 .

[36]  Laurence R. Rilett,et al.  Spectral Basis Neural Networks for Real-Time Travel Time Forecasting , 1999 .

[37]  Liping Fu,et al.  Reducing bias in probe-based arterial link travel time estimates , 2002 .

[38]  Tsu Chin,et al.  California Partners for Advanced Transit and Highways (PATH) , 2004 .

[39]  Der-Horng Lee,et al.  Calibration-free arterial link speed estimation model using loop data , 2001 .

[40]  Donald J Dailey,et al.  ITS DATA FUSION , 1996 .

[41]  H. Spiess.  CONICAL VOLUME-DELAY FUNCTIONS , 1990 .

[42]  Karthik K. Srinivasan,et al.  Determination of Number of Probe Vehicles Required for Reliable Travel Time Measurement in Urban Network , 1996 .

[43]  Der-Horng Lee,et al.  Probe Vehicle Population and Sample Size for Arterial Speed Estimation , 2002 .

[44]  H. M. Zhang,et al.  Link-Journey-Speed Model for Arterial Traffic , 1999 .

[45]  Peter C. Nelson,et al.  Application of fuzzy logic and neural networks for dynamic travel time estimation , 1999 .