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This report estimates ranges of potential effects of connected and automated vehicle (CAV) technologies on vehicle miles traveled (VMT), vehicle fuel efficiency, and costs to consumers. Analysis combining the VMT and efficiency effects under assumed high CAV market penetration produces national-level impact ranges for fuel use and, by extension, greenhouse gas emissions, since fuel switching (i.e., from gasoline to alternative fuels) is not considered. The analysis of CAV costs to consumers draws upon the potential changes to VMT and vehicle efficiency, plus available data and assumptions on CAV technology cost projections. Figure ES-1 illustrates the overall structure of the analysis to determine ranges of potential CAV effects on VMT and vehicle efficiency, and combine these to evaluate impact ranges for national light-duty vehicle (LDV) fuel use and for CAV technology costs to consumers. Figure ES-1. Visualization of the analysis process for the report The travel demand and efficiency impact range estimates draw upon results from previous studies that evaluated various CAV technology effects on conventional vehicle operation. The VMT impact calculations include vehicle occupancy assumptions to translate between person miles traveled (PMT) and VMT. The efficiency calculations rely on literature-reported values for different CAV feature impacts on fuel consumption rates (e.g., due to vehicle-to-infrastructure communication / coordination, vehicle platooning, etc.), and also include a first-order disaggregation of each feature's impact in different driving situations (i.e., city vs. highway driving and travel at peak vs. off-peak times). The relative impacts are then weighted by the amount of driving that takes place in those different situations. The analysis combines the ranges of CAV technology effects on VMT and fuel consumption rates over the total U.S. LDV stock. These calculations produce lower-and upper-bound estimates of potential total U.S. LDV fuel use (and greenhouse gas emission) impacts for three CAV scenarios relative to a present-day base scenario. The present-day base scenario represents fuel use by the current U.S. on-road light-duty vehicle fleet, consisting of essentially all vi

Commonly, the NO x emissions rates of diesel vehicles have been assumed to remain stable over the vehicle's lifetime. However, there have been hardly any representative long-term emission measurements.

It is anticipated that in the near future, the penetration rate of vehicles with some autonomous capabilities (e.g., adaptive cruise control, lane following, full automation, etc.) will increase on roadways. This work investigates the potential reduction of vehicular emissions caused by the whole traffic stream, when a small number of autonomous vehicles (e.g., 5% of the vehicle fleet) are designed to stabilize the traffic flow and dampen stop-and-go waves. To demonstrate this, vehicle velocity and acceleration data are collected from a series of field experiments that use a single autonomous-capable vehicle to dampen traffic waves on a circular ring road with 20 to 21 human-piloted vehicles. From the experimental data, vehicle emissions (hydrocarbons, carbon monoxide, carbon dioxide, and nitrogen oxides) are estimated using the MOVES emissions model. This work finds that vehicle emissions of the entire fleet may be reduced by between 15% (for carbon dioxide) and 73% (for nitrogen oxides) when stop-andgo waves are reduced or eliminated by the dampening action of the autonomous vehicle in the flow of human drivers. This is possible if a small fraction (∼5%) of vehicles are autonomous and designed to actively dampen traffic waves. However, these reductions in emissions apply

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