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Author: Publisher: ISBN: Category : Algorithms Languages : en Pages : 126
Book Description
Many current traffic management schemes are tested and implemented using traffic simulation. An Origin- Destination (OD) matrix is an ideal input for such simulations. The underlying travel demand pattern produces observed link counts. One could use these counts to reconstruct the OD matrix. An offline approach to estimate a static OD matrix over the peak period for freeway sections using these counts is proposed in this research. Almost all the offline methods use linear models to approximate the relationship between the on-ramp and off-ramp counts. Previous work indicates that the use of a traffic flow model embedded in a search routine performs better than these linear models. In this research, that approach is enhanced using a microscopic traffic simulator, AIMSUN, and a gradient-based optimization routine, MINOS, interfaced to estimate an OD matrix. The problem is highly non-linear and non-smooth, and the optimization routine finds multiple local minima, but cannot guarantee a global minima. However, with a number of starting "seed" matrices, an OD matrix with a good fit in terms of reproducing traffic counts can be estimated. The dominance of the mainline counts in the OD estimation and an identifiability issue is indicated from the experiments. The quality of the estimates improves as the specification error, introduced due to the discrepancy between AIMSUN and the real-world process that generates the on-ramp and off-ramp counts, reduces.
Author: Publisher: ISBN: Category : Algorithms Languages : en Pages : 126
Book Description
Many current traffic management schemes are tested and implemented using traffic simulation. An Origin- Destination (OD) matrix is an ideal input for such simulations. The underlying travel demand pattern produces observed link counts. One could use these counts to reconstruct the OD matrix. An offline approach to estimate a static OD matrix over the peak period for freeway sections using these counts is proposed in this research. Almost all the offline methods use linear models to approximate the relationship between the on-ramp and off-ramp counts. Previous work indicates that the use of a traffic flow model embedded in a search routine performs better than these linear models. In this research, that approach is enhanced using a microscopic traffic simulator, AIMSUN, and a gradient-based optimization routine, MINOS, interfaced to estimate an OD matrix. The problem is highly non-linear and non-smooth, and the optimization routine finds multiple local minima, but cannot guarantee a global minima. However, with a number of starting "seed" matrices, an OD matrix with a good fit in terms of reproducing traffic counts can be estimated. The dominance of the mainline counts in the OD estimation and an identifiability issue is indicated from the experiments. The quality of the estimates improves as the specification error, introduced due to the discrepancy between AIMSUN and the real-world process that generates the on-ramp and off-ramp counts, reduces.
Author: Yao Wu Publisher: ISBN: Category : Algorithms Languages : en Pages : 106
Book Description
This report examined several methods for estimating Origin-Destination (OD) matrices for freeways using loop detector data. Least squares based methods were compared in terms of both off-line and on-line estimation. Simulated data and observed data were used for evaluating the static and recursive estimators. For off-line estimation, four fully constrained least squares methods were compared. The results showed that the variations of a constrained least squares approach produced more efficient estimates. For on-line estimation, two recursive least squares algorithms were examined. The first method extends Kalman Filtering to satisfy the natural constraints of the OD split parameters. The second was developed from sequential quadratic programming. These algorithms showed different capabilities to capture an abrupt change in the split parameters. Practical recommendations of the choice of different algorithms are given.
Author: Riad Ahmad Mustafa Publisher: ISBN: Category : Geographic information systems Languages : en Pages : 0
Book Description
The 4-step Travel Demand Model is usually based on roadway networks, which exclude roads of lower functional classification and are comprised of coarse traffic analysis zones (TAZs). Coarse zones (mostly in rural areas) tend to yield a higher percentage of intrazonal trips, which are not accounted for because the travel demand model can only capture those trips across the zone boundaries, resulting in fairly high model estimation errors. The special attention given to rural zones in this dissertation is motivated by the fact that they significantly influence the modeling accuracy and network-wide traffic volume assignability, especially to lower functional classification roads (locals and collectors). In an effort to overcome the shortcomings of the traditional model, this dissertation developed a GIS-based high-fidelity travel demand model (HFTDM) zonal enhancement framework capable of generating finer-grained spatial resolution TAZs. The resulting TAZs are more uniform in size and capable of determining both trip productions and attractions and can be used to achieve network-wide traffic volume estimation with improved accuracy to include local and collector roads. The developed (HFTDM) zonal enhancement framework was not expected to produce accurate traffic estimates on all links in the road network due to the lack of local travel surveys used to calibrate at each stage of the modeling process. To develop the TAZ structure enhancement procedure, the dissertation presents a methodological, systematic, GIS-based framework by integrating the travel demand modeling software platform, remotely-sensed images, parcel-based digital property maps, AZTool aggregation algorithm, and areal interpolation technique. This dissertation developed an HFTDM zonal enhancement framework for the Greater Fredericton Area (GFA) in the province of New Brunswick based on well-designed 10 individual-TAZ structure resolutions. The developed HFTDM zonal enhancement framework showed a general trend of network-wide incremental improvement in both modeling accuracy and assignment coverage capability along with increasing study area zonal resolution from coarse-grained to finer-grained zones. The case study showed that increasing the GFA spatial resolution from the coarsiest TAZ structure at Census Tract (CT) level (27 CT TAZs) to the finest TAZ structure at 4252 “fine” TAZs resulted in an improvement to modeling accuracy represented by an increase in the coefficient of determination, R2, by 0.4092 (from 0.2490 to 0.6582) and an improvement in traffic assignment coverage by 46% (from 29% to 75%).
Author: University of Minnesota. Intelligent Transportation Systems Institute Publisher: ISBN: Category : Intelligent Vehicle Highway Systems Languages : en Pages : 64
Author: Winnie Daamen Publisher: CRC Press ISBN: 1482228718 Category : Mathematics Languages : en Pages : 261
Book Description
A single source of information for researchers and professionals, Traffic Simulation and Data: Validation Methods and Applications offers a complete overview of traffic data collection, state estimation, calibration and validation for traffic modelling and simulation. It derives from the Multitude Project-a European Cost Action project that incorpo
Author: Publisher: Transportation Research Board ISBN: 0309214009 Category : Traffic estimation Languages : en Pages : 170
Book Description
TRB’s National Cooperative Highway Research Program (NCHRP) Report 716: Travel Demand Forecasting: Parameters and Techniques provides guidelines on travel demand forecasting procedures and their application for helping to solve common transportation problems.
Author: Michael Behrisch Publisher: Springer ISBN: 3319150243 Category : Technology & Engineering Languages : en Pages : 240
Book Description
This contributed volume contains the conference proceedings of the Simulation of Urban Mobility (SUMO) conference 2014, Berlin. The included research papers cover a wide range of topics in traffic planning and simulation, including open data, vehicular communication, e-mobility, urban mobility, multimodal traffic as well as usage approaches. The target audience primarily comprises researchers and experts in the field, but the book may also be beneficial for graduate students.
Author: Keith M. Chase Publisher: Transportation Research Board ISBN: 0309129427 Category : Transportation Languages : en Pages : 90
Book Description
" TRB's second Strategic Highway Research Program (SHRP 2) Report S2-C20-RR-1: Freight Demand Modeling and Data Improvement documents the state of the practice for freight demand modeling. The report also explores the fundamental changes in freight modeling, and data and data collection that could help public and private sector decision-makers make better and more informed decisions. SHRP 2 Capacity Project C20, which produced Report S2-C20-RR-1, also produced the following items: A Freight Demand Modeling and Data Improvement Strategic Plan, which outlines seven strategic objectives that are designed to serve as the basis for future innovation in freight travel demand forecasting and data, and to guide both near- and long-term implementation: A speaker's kit, which is intended to be a "starter" set of materials for use in presenting the freight modeling and data improvement strategic plan to a group of interested professionals; and; A 2010 Innovations in Freight Demand Modeling and Data Symposium " -- publisher's description
Author: 
Author: 
Author: Yao Wu
Author: Riad Ahmad Mustafa
Author: University of Minnesota. Intelligent Transportation Systems Institute
Author: David S. Kriger
Author: Winnie Daamen
Author: Kuo-Shian Lin
Author: 
Author: Michael Behrisch
Author: Keith M. Chase