nach oben

Transportation

Erschienen in:

20.07.2018

A novel approach for systematically calibrating transport planning model systems

verfasst von: Ali Najmi, Taha H. Rashidi, Eric J. Miller

Erschienen in: Transportation | Ausgabe 5/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Calibration of a transport planning model system is a complex process. While trial-and-error methods and modelling expertise are still the backbone of calibration of transport models, analytical approaches automating the calibration process can improve the accuracy of the models. Introducing a model to guide modellers in the calibration process of large-scale transport planning model systems is the core of this study, where a systematic model for choosing the most appropriate models and parameters is discussed. The effectiveness of the proposed model is investigated by comparing three scenarios which are built on the Travel/Activity Scheduler for Household Agents model as a large-scale agent-based model system.

Vorheriger Artikel A fractional perspective to the modelling of Lisbon’s public transportation network

Nächster Artikel The potential of mobility as a service bundles as a mobility management tool

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Al-Aomar, R.: Incorporating robustness into Genetic Algorithm search of stochastic simulation outputs. Simul. Model. Pract. Theory 14, 201–223 (2006). https://doi.org/10.1016/j.simpat.2005.05.001 CrossRef

Appiah, J., Rilett, L.R.: Joint estimation of dynamic origin-destination matrices and calibration of micro-simulation models using aggregate intersection turncount data (2010)

Asakura, Y., Hato, E., Kashiwadani, M.: Origin-destination matrices estimation model using automatic vehicle identification data and its application to the Han-Shin expressway network. Transportation 27, 419–438 (2000). https://doi.org/10.1023/A:1005239823771 CrossRef

Balakrishna, R.: Off-Line calibration of dynamic traffic assignment models. PhD thesis, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology (2006)

Balakrishna, R., Ben-Akiva, M., Koutsopoulos, H.: Offline calibration of dynamic traffic assignment: simultaneous demand-and-supply estimation. Transp. Res. Rec. J. Transp. Res. Board. 2003, 50–58 (2007). https://doi.org/10.3141/2003-07 CrossRef

Bao, Q., Kochan, B., Bellemans, T., Janssens, D., Wets, G.: Investigating micro-simulation error in activity-based travel demand forecasting: a case study of the FEATHERS framework. Transp. Plan. Technol. 38, 425–441 (2015). https://doi.org/10.1080/03081060.2015.1026102 CrossRef

Bliemer, M., Raadsen, M., De Romph, E., Smits, E.: Requirements for traffic assignment models for strategic transport planning: a critical assessment. In: ATRF, pp. 1–25 (2013)

Bowman, J.L., Bradley, M.A., Gibb, J.: The Sacramento activity-based travel demand model: estimation and validation results. In: Proceedings of the European Transport Conference, pp. 1–22. Strasbourg, France (2006)

Cambridge Systematics, I.: FSUTMS-cube framework phase II: model calibration and validation standards. Final report (2008)

Cambridge Systematics, Inc.: Travel Model Validation and Reasonability Checking Manual, 2nd edn. Federal Highway Administration, Washington, DC (2010)

Capelle, T., Sturm, P., Vidard, A.: Formulating LUTI calibration as an optimisation problem: example of tranus shadow price estimation. Procedia Eng. 115, 12–20 (2015). https://doi.org/10.1016/J.PROENG.2015.07.349 CrossRef

Cascetta, E., Postorino, M.N.: Fixed point approaches to the estimation of O/D matrices using traffic counts on congested networks. Transp. Sci. 35, 134–147 (2001). https://doi.org/10.1287/trsc.35.2.134.10138 CrossRef

Castiglione, J., Freedman, J., Bradley, M.: Systematic investigation of variability due to random simulation error in an activity-based microsimulation forecasting model. Transp. Res. Rec. J. Transp. Res. Board. 1831, 76–88 (2003). https://doi.org/10.3141/1831-09 CrossRef

Cools, M., Moons, E., Wets, G.: Calibrating activity-based models with external origin-destination information: overview of possibilities. Transp. Res. Rec. J. Transp. Res. Board. 2175, 98–110 (2010). https://doi.org/10.3141/2175-12 CrossRef

Davidson, W., Donnelly, R., Vovsha, P., Freedman, J., Ruegg, S., Hicks, J., Castiglione, J., Picado, R.: Synthesis of first practices and operational research approaches in activity-based travel demand modeling. Transp. Res. Part A Policy Pract. 41, 464–488 (2007). https://doi.org/10.1016/J.TRA.2006.09.003 CrossRef

Donnelly, R., Erhardt, G.D., Moeckel, R., Davidson, W.A.: Advanced Practices in Travel Forecasting. Transportation Research Board of the National Academies, Washington, DC (2010)

Kackar, R.N.: Off-line quality control, parameter design, and the Taguchi method. In: Dehnad, K. (ed.) Quality Control, Robust Design, and the Taguchi Method, pp. 51–76. Springer, Boston (1989)CrossRef

Miller, E., Roorda, M.: Prototype model of household activity-travel scheduling. Transp. Res. Rec. J. Transp. Res. Board. 1831, 114–121 (2003). https://doi.org/10.3141/1831-13 CrossRef

Najmi, A., Duell, M., Ghasri, M., Rashidi, T.H., Waller, S.T.: How should travel demand and supply models be jointly calibrated? Transp. Res. Rec. J. Transp. Res. Board. (2018). https://doi.org/10.1177/0361198118772954 CrossRef

NCHRP: Travel Demand Forecasting: Parameters and Techniques. National Academies Press, Washington, DC (2012)

NYMTC 2010: Base Year Update and Validation of the NYMTC. Parsons Brinckerhoff, New York (2014)

NZ Transport Agency: Transport Model Development Guidelines. NZ Transport Agency, Wellington (2014)

Omrani, R., Kattan, L.: Demand and supply calibration of dynamic traffic assignment models. Transp. Res. Rec. J. Transp. Res. Board. 2283, 100–112 (2012). https://doi.org/10.3141/2283-11 CrossRef

Omrani, R., Kattan, L.: Simultaneous calibration of microscopic traffic simulation model and estimation of origin/destination (OD) flows based on genetic algorithms in a high-performance computer. In: 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), pp. 2316–2321. IEEE (2013)

Park, S.H., Antony, J.: Robust Design for Quality Engineering and Six Sigma. World Scientific, Singapore (2008)CrossRef

Parsons Brinckerhoff: The MORPC travel demand model validation and final report (2005)

Peace, G.S.: Taguchi Methods: A Hands-On Approach. Addison-Wesley, Boston (1993)

Phadke, M.S.: Quality Engineering Using Robust Design. Prentice Hall, Englewood Cliffs NJ (1989)

Rao, R.S., Kumar, C.G., Prakasham, R.S., Hobbs, P.J.: The Taguchi methodology as a statistical tool for biotechnological applications: a critical appraisal. Biotechnol. J. 3, 510–523 (2008). https://doi.org/10.1002/biot.200700201 CrossRef

Rasouli, S., Timmermans, H.: Uncertainty in travel demand forecasting models: literature review and research agenda. Transp. Lett. 4, 55–73 (2012). https://doi.org/10.3328/TL.2012.04.01.55-73 CrossRef

Rezaeestakhruie, H.: Analytical Error Propagation in Four-Step Transportation Demand Models. http://espace.library.uq.edu.au/view/UQ:499811 (2017)

Roorda, M.J., Miller, E.J., Habib, K.M.N.: Validation of TASHA: a 24-h activity scheduling microsimulation model. Transp. Res. Part A Policy Pract. 42, 360–375 (2008). https://doi.org/10.1016/J.TRA.2007.10.004 CrossRef

Roy, R.K.: A Primer on the Taguchi Method. Society of Manufacturing Engineers, ‎Dearborn (1990)

Taguchi, G.: Introduction to Quality Engineering: Designing Quality into Products and Processes. Asian Productivity Organization, Tokyo (1986)

Train, K.E.: Discrete Choice Methods with Simulation. Cambridge University Press, Cambridge (2003)CrossRef

Travel Modelling Group (TMG): GTAModel V4.0, Design. Background and Calibration. Toronto, Travel Modelling Group (TMG) (2015)

Wisconsin Department of Transportation (WisDOT): Traffic Forecasting, Travel Demad Models, and Planning Data Transportation Planning Manual. Wisconsin Department of Transportation (WisDOT), Wisconsin (2018)

Wysk, R.A., Niebel, B.W., Cohen, P.H., Simpson, T.W.: Manufacturing Processes: Integrated Product and Process Design. McGraw, New York (2000)

Zandieh, M., Amiri, M., Vahdani, B., Soltani, R.: A robust parameter design for multi-response problems. J. Comput. Appl. Math. 230, 463–476 (2009). https://doi.org/10.1016/J.CAM.2008.12.019 CrossRef

Titel: A novel approach for systematically calibrating transport planning model systems
verfasst von: Ali Najmi
Taha H. Rashidi
Eric J. Miller
Publikationsdatum: 20.07.2018
Verlag: Springer US
Erschienen in: Transportation / Ausgabe 5/2019
Print ISSN: 0049-4488
Elektronische ISSN: 1572-9435
DOI: https://doi.org/10.1007/s11116-018-9911-6

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 5/2019

An optimization model for integrated transit-parking policy planning

A study on route choice preferences for commuter and non-commuter bicyclists: a case study of Kharagpur and Asansol, India

Investigating inter-generational changes in activity-travel behavior: a disaggregate approach

How does travel satisfaction sum up? An exploratory analysis in decomposing the door-to-door experience for multimodal trips

Correction to: The role of travel demand and network centrality on the connectivity and resilience of an urban street system

Survey design for exploring demand for Mobility as a Service plans

Premium Partner