Abstract
Connected and automated vehicle (CAV) technologies could transform the transportation system over the coming decades, but face vehicle and systems engineering challenges, as well as technological, economic, demographic, and regulatory issues. The authors have developed a system dynamics model for generating, analyzing, and screening self-consistent CAV adoption scenarios. Results can support selection of scenarios for subsequent computationally intensive study using higher-resolution models. The potential for and barriers to large-scale adoption of CAVs have been analyzed using preliminary quantitative data and qualitative understandings of system relationships among stakeholders across the breadth of these issues. Although they are based on preliminary data, the results map possibilities for achieving different levels of CAV adoption and system-wide fuel use and demonstrate the interplay of behavioral parameters such as how consumers value their time versus financial parameters such as operating cost. By identifying the range of possibilities, estimating the associated energy and transportation service outcomes, and facilitating screening of scenarios for more detailed analysis, this work could inform transportation planners, researchers, and regulators.
Original language | American English |
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Pages (from-to) | 84-94 |
Number of pages | 11 |
Journal | Transportation Research Record |
Volume | 2673 |
Issue number | 5 |
DOIs | |
State | Published - 1 May 2019 |
Bibliographical note
Publisher Copyright:© National Academy of Sciences: Transportation Research Board 2019.
NREL Publication Number
- NREL/JA-6A20-72017
Keywords
- automated vehicles
- connected vehicles
- smart vehicles
- system dynamics
- technology
- transportation systems
- vehicle adoption