Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles, Volume 2: Guidance (2018) / Chapter Skim
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Pages 30-37
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30 Forward-looking planning activities typically seek to evaluate and choose from among a set of candidate decision options. For transportation planners, this can include choices about expanding highway capacity, extending or enhancing transit service, creating bike lanes, and prioritizing system upgrades and maintenance.
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Planning in the Context of Uncertainty 31 variability and uncertainty of the network's performance under different circumstances. Travel that takes place on transportation facilities is highly variable, flexible, and malleable.
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32 Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles Overview of Planning Processes Predictive Analysis, or Agreeing on Assumptions Most traditional planning methods seek to (a) reduce uncertainty by requiring agreement on assumptions about the current and future conditions under which a plan must perform, and (b)
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Planning in the Context of Uncertainty 33 and then stress-test the options under a wide range of plausible conditions, without requiring a decision or agreement upon which conditions are more or less likely. They evaluate the decision options repeatedly, under many different sets of assumptions.
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34 Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles planning to develop their own, more localized future CAV scenarios. State and regional agencies may use this illustrative scenario planning process to anticipate likely issues and challenges they will face due to CAV adoption, and therefore to help visualize and understand their planning options, including developing or changing institutional and operational responses and policies.
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Planning in the Context of Uncertainty 35 Quantitative Methods for Managing Deep Uncertainty In response to the difficulty of linking scenarios to policy choices, many have turned to alternative methods for decision making under deep uncertainty. As described earlier, deep uncertainty exists when decision makers do not know or do not agree on the models that describe relationships between key drivers and outcomes, the probabilities of key variables, or how to value the desirability of different outcomes.
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36 Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles Dynamic Adaptive Pathways Planning Another approach is dynamic adaptive pathways planning (DAPP; Haasnoot et al.
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Planning in the Context of Uncertainty 37 Perhaps the most significant challenges to implementing quantitative methods of managing uncertainty arise because these methods represent a new way of thinking about how near-term actions can best manage future risks. Analysts are generally trained in predictive thinking, and the decision makers they inform often expect predictive quantitative information.
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