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Title: Anticipating Changes in Travel Demand Resulting from the Adoption of Highly Automated Vehicles: A Comparative Analysis of Urban Transportation Transitions During the Machine Age and Information Age
Accession Number: 01663347
Record Type: Component
Abstract: The potential disruption of urban transportation systems by the introduction and widespread adoption of highly automated vehicles is anticipated, but uncertain. Current literature predicts a likely scenario of an incentive for vehicle miles travelled to increase, but there is not yet a consensus. This paper provides a comparative analysis, through a systems perspective, to juxtapose the shift from horse-drawn carriage to the automobile in the Machine Age, against the experienced and predicted impact of a shift from automobile to highly automated vehicle in the Information Age. In each case, a widening of transportation options occurred, beginning prior to the introduction of the dominant mode and technology. Once established, the automobile released unmet travel demand, becoming the default mobility choice and reshaping streets, cities, and travel patterns – all which in turn created systems that reinforced its hegemony. Should highly automated vehicles supplant the automobile as the modal choice for the majority of urban passenger trips, whether in a “shared” format or under the existing private ownership model, it is hypothesized that the highly automated vehicle shall follow a similar pattern of releasing unmet travel needs and becoming the focal point in reordered transportation and urban systems.
Supplemental Notes: This paper was sponsored by TRB committee ABE50 Standing Committee on Transportation Demand Management.
Report/Paper Numbers: 18-06537
Language: English
Authors: Shi, Hong Yun (Eva)Lanyon, RyanKhan, FahadPagination: 17p
Publication Date: 2018
Conference:
Transportation Research Board 97th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; References
TRT Terms: Subject Areas: Highways; Planning and Forecasting; Policy
Source Data: Transportation Research Board Annual Meeting 2018 Paper #18-06537
Files: TRIS, TRB, ATRI
Created Date: Jan 8 2018 11:41AM
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