Automated vehicles have the potential to bring about transformative safety, mobility, energy, and environmental benefits to the surface transportation system. Given the complexity of these impacts, a modeling framework is needed to ensure that they are adequately captured. This report updates the earlier Framework from our and summarizes the safety, mobility, energy/emissions, and travel behavior (user response) modeling.
In this study, there were two scenarios with baseline (human) driving with the default Wiedemann 99 car following algorithm, one at a low traffic volume and the other at high volume (1,500 and 3,000 vehicles per lane per hour) and two scenarios without Wiedemann 99 oscillations at low and high volume.
On average, autonomous vehicles perform the same or produce fewer emissions than human drivers. The greatest benefits from autonomous vehicles include a 32 percent reduction in oxides of Nitrogen (NOx) for low-volume conditions and a 17 percent reduction in NOx for high-volume conditions.
In the low-volume condition, human drivers only produced 1.8 kg of Carbon monoxide (CO) compared to 4.4 kg CO for autonomous vehicles. This is expected because a human drivers can perform aggressive operating modes better than autonomous vehicles, and CO has an inverted relationship to speed. In the high-volume condition autonomous vehicles produce about seven percent fewer CO emissions than human drivers.
For both roadway conditions, autonomous vehicles consumed less energy than human drivers, consuming 43 percent and 20 percent less fuel in the low volume and high volume conditions, respectively. Combined with the emissions data, this indicates that there can be a trade-off in assessing benefits from autonomous vehicles since the scenario with the largest decrease in fuel consumption showed the largest dis-benefit in emissions.