Connected and automated vehicles (CAVs) are poised to reshape transportation and mobility by replacing humans as the driver and service provider. While the primary stated motivation for vehicle automation is to improve safety and convenience of road mobility, this transformation also provides a valuable opportunity to improve vehicle energy efficiency and reduce emissions in the transportation sector. Progress in vehicle efficiency and functionality, however, does not necessarily translate to net positive environmental outcomes. Here, we examine the interactions between CAV technology and the environment at four levels of increasing complexity: vehicle, transportation system, urban system, and society. We find that environmental impacts come from CAV-facilitated transformations at all four levels, rather than from CAV technology directly. We anticipate net positive environmental impacts at the vehicle, transportation system, and urban system levels, but expect greater vehicle utilization and shifts in travel patterns at the society level to offset some of these benefits. Focusing on the vehicle-level improvements associated with CAV technology is likely to yield excessively optimistic estimates of environmental benefits. Future research and policy efforts should strive to clarify the extent and possible synergetic effects from a systems level to envisage and address concerns regarding the short- and long-term sustainable adoption of CAV technology.

With the likelihood of autonomous vehicle technologies in public transport and taxi systems prior to privately-owned vehicles increasing, their actual impact on commuting in realworld road networks is insufficiently studied. In this study, an agent-based model is developed to simulate how commuters travel by autonomous taxis (aTaxis) in real-world road networks. The model evaluates the travel costs and environmental implications of substituting conventional personal vehicle travel with aTaxi travel. The proposed model is applied to the City of Ann Arbor, MI to demonstrate the effectiveness of aTaxis. Our results indicate that to meet daily commute demand with wait times less than 3 minutes, the optimized autonomous taxi fleet size is only 20% of the conventional solo-commuting personal car fleet. The commuting cost decreases by 38%, and daily vehicle utilization increases from 14 minutes to 92 minutes. In case of utilizing internal combustion engine aTaxis, energy consumption, GHG emissions, and SO2 emissions are respectively 16%, 25%, and 10% higher than conventional solo commuting, mainly due to unoccupied repositioning between trips. Given the emission intensity of the local electricity grid, the environmental impacts of electric aTaxis do not show significant improvement over conventional vehicles.

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Connected and automated vehicles (CAVs) are expected to yield significant