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University of Texas at Austin
The introduction of shared autonomous vehicles (SAVs) in cities could potentially increase the number of vehicle miles traveled (VMT). The implementation of dynamic ride-sharing (DRS) systems could limit this increase and potentially result in a net reduction in VMT.
This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.
Connected and fully automated or autonomous vehicles (CAVs) are becoming increasingly viable 23 as a technology and may soon dominate the automotive industry. Once CAVs are sufficiently 24 reliable and affordable, they will gain greater market penetration, generating significant economic 25 ripple effects throughout many industries. This paper synthesizes and expands upon analysis from 26 multiple reports on the economic effects of CAVs across 13 different industries and the overall 27 economy.
This paper models the market potential of a fleet of shared, autonomous, electric vehicles (SAEVs) 20 by employing a multinomial logic mode choice model in an agent-based framework and different 21 fare settings.
Trikes can be a major competitor in the CDB delivery market as it can navigate bike lanes and be parked more freely.
Autonomous vehicles (AVs) represent a potentially disruptive yet beneficial change to our transportation system. This new technology has the potential to impact vehicle safety, congestion, and travel behavior. All told, major social AV impacts in the form of crash savings, travel time reduction, fuel efficiency and parking benefits are estimated to approach $2000 to per year per AV, and may eventually approach nearly $4000 when comprehensive crash costs are accounted for. Yet barriers to implementation and mass-market penetration remain. Initial costs will likely be unaffordable. Licensing and testing standards in the U.S. are being developed at the state level, rather than nationally, which may lead to inconsistencies across states. Liability details remain undefined, security concerns linger, and without new privacy standards, a default lack of privacy for personal travel may become the norm. The impacts and interactions with other components of the transportation system, as well as implementation details, remain uncertain. To address these concerns, the federal government should expand research in these areas and create a nationally recognized licensing framework for AVs, determining appropriate standards for liability, security, and data privacy.
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