Value of Travel Time Reliability in Transportation Decision Making: Proof of Concept—Portland, Oregon, Metro (2014) / Chapter Skim
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Pages 29-39
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29 C h a p t e r 5 5.1 Metro Dynust Dynamic traffic assignment Model establishment and Calibration For this project, Metro staff created a DynusT regional DTA model. Significant effort went into converting, coding, and debugging the regional model.
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30 Emme volumes 4 pm – 6 pm D yn u sT v o lu m es 4 p m – 6 p m Figure 5.1. Comparison of 4 p.m.
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31 Table 5.1. AM Peak-Period Travel Time Comparison Between DynusT and Emme Zone No.
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32 Figure 5.4. Southwest Corridor study area shown in coral.
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33 County, Washington) and SMART (Southern Metro Area Regional Transit)
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34 2. The transit dwell information produced by FAST-TrIPs can be used for the DynusT run in order to account for the delay at transit stops.
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35 separately using the corresponding fake automobile demand to produce the midday (12 to 1 p.m.) and peak afternoon (4 to 6 p.m.)
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36 Figure 5.9. Difference in AM peak-period SOV automobile travel times for Southwest Corridor zone pairs (weighted by trips)
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37 Figure 5.10. Difference in midday SOV automobile travel times for Southwest Corridor zone pairs (weighted by trips)
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38 Figure 5.11. Difference in AM peak-period total transit travel times for Southwest Corridor zone pairs (weighted by trips)
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39 Figure 5.12. Difference in midday total transit travel times for Southwest Corridor zone pairs (weighted by trips)
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