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1

Small, Kenneth A. Valuation of travel-time savings and predictability in congested conditions for highway user-cost estimation. Washington, D.C: National Academy Press, 1999.

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2

Lipps, Oliver. Modellierung der individuellen Verhaltensvariationen bei der Verkehrsentstehung. Karlsruhe, Germany]: Institut für Verkehrswesen, Universität Karlsruhe, 2001.

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3

Associates, Dowling, Travel Model Improvement Program (U.S.), and Technology Sharing Program (U.S.), eds. Travel model speed estimation and post processing methods for air quality analysis: Final report. [Washington, D.C.]: U.S. Dept. of Transportation, 1997.

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4

Wilson, James F. Estimating traveltimes of boats through bald eagle habitat along the Snake River, northwestern Wyoming, using geographic information system techniques. Cheyenne, Wyo: U.S. Dept. of the Interior, U.S. Geological Survey, 1992.

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5

Schiffer, Robert G. Long-Distance and Rural Travel Transferable Parameters for Statewide Travel Forecasting Models. WASHINGTON, D.C: TRANSPORTATION RESEARCH BOARD, 2012.

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6

Staunton, Michael M. Journey time measurement: For the assessment of major road projects. Dublin: Environmental Research Unit, 1993.

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7

A, Martin William. Travel estimation techniques for urban planning. Washington, D.C: National Academy Press, 1998.

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8

Johnson, Dennis L. 20-year traffic forecasting factors. Pierre, SD: South Dakota Dept. of Transportation, Office of Research, 2000.

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9

National Research Council (U.S.). Transportation Research Board., ed. Capturing the dynamics of travel behavior. Washington, D.C: Transportation Research Board, National Research Council, 1987.

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10

F, Turnbull Katherine, Texas. Dept. of Transportation., and Texas Transportation Institute, eds. Potential of telecommuting for travel demand management. College Station, Tex: Texas Transportation Institute, Texas A&M University System, 1996.

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11

Soriguera Martí, Francesc. Highway Travel Time Estimation With Data Fusion. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48858-4.

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12

National Research Council (U.S.). Transportation Research Board., ed. Urban travel forecasting. Washington, D.C: Transportation Research Board, National Research Council, 1987.

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13

Corporation, Comsis, Institute of Transportation Engineers, United States. Federal Highway Administration, and United States. Federal Transit Administration, eds. Overview of travel demand management measures: Final report. Washington, D.C: U.S. Dept. of Transportation, 1994.

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14

Shawn, Turner, United States. Federal Highway Administration. Office of Highway Information Management., and Texas Transportation Institute, eds. Travel time data collection handbook. Washington, DC: Office of Highway Information Management, Federal Highway Administration, U.S. Dept. of Transportation, 1998.

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15

Donnelly, R. Advanced practices in travel forecasting. Washington, D.C: Transportation Research Board, 2010.

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16

Systematics, Cambridge, and Travel Model Improvement Program (U.S.), eds. Time-of-day modeling procedures: State-of-the-art, state-of-the-practice : final report. Washington, D.C: Travel Model Improvement Program, U.S. Dept of Transportation, U.S. Environmental Protection Agency, 1998.

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17

Kittelson & Associates. Evaluating alternative operations strategies to improve travel time reliability. Washington, D.C: Transportation Research Board, 2013.

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18

Second Strategic Highway Research Program (U.S.), Kimley-Horn and Associates, and Parsons Brinckerhoff, eds. Guide to integrating business processes to improve travel time reliability. Washington, D.C: Transportation Research Board, 2011.

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19

Horowitz, Alan J. Statewide travel forecasting models. Washington, D.C: Transportation Research Board, 2006.

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20

Systematics, Cambridge, Deakin Harvey Skabardonis Inc, United States. Dept. of Transportation., United States. Federal Transit Administration., United States. Federal Highway Administration., United States. Environmental Protection Agency., and Technology Sharing Program (U.S.), eds. The effects of land use and travel demand management strategies on commuting behavior: Final report. Washington, D.C: U.S. Dept. of Transportation, 1994.

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21

Arnold, E. D. Changes in travel in the Shirley Highway corridor, 1983-1986. Charlottesville, Va: Virginia Transportation Research Council, in cooperation with the U.S. Dept. of Transportation, Federal Highway Administration, 1987.

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22

K, Edara Praveen, Guo Jianhua, Smith Brian L. 1967-, McGhee Catherine C, Virginia Transportation Research Council, and Virginia. Dept. of Transportation., eds. Optimal placement of point detectors on Virginia's freeways: Case studies of Northern Virginia and Richmond. Charlottesville, Va: Virginia Transportation Research Council, 2008.

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23

Lau, Lorrie A. Y. Analysis of national and regional travel trends. Washington, D.C: Dept. of Transportation, Federal Highway Administration, 1986.

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24

Washington (State). Dept. of Transportation., Cambridge Systematics, and Puget Sound Regional Council, eds. Final report: PSRC travel model documentation (for version 1.0), updated for congestion relief analysis. [Sammamish, Wash: Cambridge Systematics, 2007.

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25

North, American Travel Monitoring Exhibition and Conference (2000 Middleton Wis ). North American Travel Monitoring Exhibition and Conference, TRB Data Committee's mid-year meetings, August 27-31, 2000, Middleton, WI. Madison, Wis: Wisconsin Dept. of Transportation, 2000.

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26

Dowling, Richard G. Incorporating travel-time reliability into the congestion management process: A primer. Washington, DC: United States Department of Transportation, Federal Highway Administration, 2015.

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27

Kralich, Susana. Accesibilidad hogar-trabajo en el Gran Buenos Aires: Un estudio de caso en el partido de La Matanza. Buenos Aires: Instituto de Geografía, Universidad de Buenos Aires, Facultad de Filosofia y Letras, 1993.

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28

Great Britain. Department of Transport., ed. Journey times survey 1996: Inner and central London. London: Stationary Office, 1997.

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29

Hyŏn, Pak. Yebi tʻadangsŏng chosa chaengchŏm yŏnʼgu. Sŏul Tʻŭkpyŏlsi: Hanʼguk Kaebal Yŏnʼguwŏn, 2006.

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30

Singer, Jeremiah P. Travel time on arterials and rural highways: State-of-the-practice synthesis on rural data collection technology : rural data collection technology. Washington, DC: U.S. Department of Transportation, Federal Highway Administration, 2013.

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31

Singer, Jeremiah P. Travel time on arterials and rural highways: State-of-the-practice synthesis on arterial data collection technology ; arterial data collection technology. Washington, DC: U.S. Department of Transportation, Federal Highway Administration, 2013.

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32

Dailey, Daniel J. Improved estimates of travel time from real time inductance loop sensors: Final technical report, Research Project T9233, Task 5, "Improved Travel Time Estimates". [Olympia, WA?]: Washington State Dept. of Transportation, Washington State Transportation Commission, Transit, Research, and Intermodal Planning (TRIP) Division in cooperation with the U.S. Dept. of Transportation, Federal Highway Administration, 1993.

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33

Arnold, E. D. Congestion on Virginia's urban highways. Charlottesville, Va: Virginia Transportation Research Council, in cooperation with the U.S. Dept. of Transportation, Federal Highway Administration, 1988.

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34

Goodchild, Anne L. Service time variability at the Blaine, Washington, international border crossing and impact on regional supply chains. Bellingham, Wash: Border Policy Research Institute, Western Washington University, 2007.

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35

Purvis, Charles L. Bay Area travel forecasts: Congestion management program databook #1 : regional summary. Oakland, Calif: Metropolitan Transportation Commission, 1991.

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36

Chui, Margaret K. The value of travel time: New estimates developed using a speed-choice model. College Station, Tex: Texas Transportation Institute, Texas A&M University System, 1986.

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37

Kropman, J. A. De betekenis van de verplaatsingstijdfactor: Vergelijking van auto- en treinverplaatsingen op de corridor Dordrecht-Rotterdam. Nijmegen: Instituut voor Toegepaste Sociale Wetenschappen, 1993.

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38

Nerhagen, Lena. Travel demand and value of time: Towards an understanding of individuals choice behavior. Gothenburg: Dept. of Economics, Gothenburg University, 2001.

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39

Lapparent, Matthieu de. L' analyse de la valeur du temps dans les déplacements professionnels: De l'approche classique à l'introduction d'incertitude sur les temps de transport. Arcueil: INRETS, 2005.

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40

Metropolitan Washington Council of Governments. and National Capital Region Transportation Planning Board., eds. The 1985 zone level Washington transit network. [Washington, D.C.]: Metropolitan Washington Council of Governments, National Capital Region Transportation Planning Board, 1986.

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41

Rakha, Hesham. Transit signal priority project, phase II: Field and simulation evaluation results. Charlottesville, Va: Virginia Transportation Research Council, 2006.

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42

Chen, Huey-Kuo. Dynamic travel choice models: A variational inequality approach. Berlin: Springer, 1999.

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43

Office, General Accounting. Airline scheduling: Airlines' on-time performance : report to congressional requesters / United States General Accounting Office. Washington, D.C: The Office, 1990.

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44

Ryan, Jeffrey T. Valuation of temporary transportation facility use losses. Helena, MT: Montana Dept. of Transportation, 2002.

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45

Peter, Schütte Franz, Kreibich Volker, and North Rhine-Westphalia (Germany). Ministerium für Stadtentwicklung und Verkehr., eds. Reisezeitverkürzung im öffentlichen Personennahverkehr. Dortmund: Institut für Landes- und Stadtentwicklungsforschung des Landes Nordrhein-Westfalen, 1991.

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46

National Research Council (U.S.). Transportation Research Board., ed. Visibility and highway navigation. Washington, D.C: Transportation Research Board, National Research Council, 1986.

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47

Cardwell, David B. Analysis of the District of Columbia labor force accessibility to work: Summary report. Washington, D.C: Metropolitan Washington Council of Governments, National Capital Region Transportation Planning Board, 1985.

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48

Rodriguez, Carlos G. Transportation planning data for urbanized areas based on the 1980 census. Washington, D.C: The Division, 1985.

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49

Rodier, Caroline J. Verifying the accuracy of land use models used in transportation and air quality planning: A case study in the Sacramento, California, region. San Jose, CA: Mineta Transportation Institute, College of Business, San José State University, 2005.

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50

Rodier, Caroline. Verifying the accuracy of regional models used in transportation and air quality planning. San Jose, CA: Mineta Transportation Institute, College of Business, San José State University, 2003.

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