Increasing the environmental benefits of autonomous vehicles

Maximal use of automated vehicles helps minimize environmental deterioration.

A specially equipped Lincoln MKZ, based at Mcity, is an open-source connected and automated research vehicle available to U-M faculty and students, startups and others to help accelerate innovation
A specially equipped Lincoln MKZ, based at Mcity, is an open-source connected and automated research vehicle available to U-M faculty and students, startups and others to help accelerate innovation. Image credit: University of Michigan

According to a recent investigation by the University of Michigan, the added weight, electricity requisition and aerodynamic drag of the sensors and computers utilized in autonomous vehicles can lead contributors to their lifetime energy use and greenhouse gas emissions. Notwithstanding, when accumulation from the driving efficiencies linked with self-driving vehicles are factored into the equation, the thorough outcome is a scale down in lifetime energy use and associated greenhouse gas emissions of up to 9 percent collate to the conventional vehicles investigated.

Study co-author Gregory Keoleian, director of the Center for Sustainable Systems at U-M’s School for Environment and Sustainability said, “This study explored the tradeoffs between the increased environmental impacts from adding autonomous vehicle equipped with the expected gains in driving efficiency.”

“Our findings highlight the need to focus on energy efficiency when designing autonomous vehicles so that the full environmental benefits of this emerging, transformative technology can be realized. We hope this work contributes to a more sustainable mobility ecosystem.”

The findings are scheduled for online publication Feb. 15 in the journal Environmental Science & Technology.

This investigation is a thorough assessment of the lifetime contributions of the sensing and computing subsystems in autonomous vehicles to energy use and related greenhouse gas emissions. These vehicles officially recognized as connected and automated vehicles or CAVs mostly consists multiple cameras, sonar, radar, LiDAR, a GPS navigation system, a computer and support structures.

The researchers scrutinized two types of CAVs as those powered by internal combustion engines and battery-powered electric vehicles respectively. The two-vehicle kinds were paired with sensing and computer subsystems of three sizes (small, medium and large) to frame six scenarios.

In this, life-cycle assessment methodology was then utilized to predict lifetime energy use and greenhouse gas emissions for each scenario, from cradle to grave.

The study discovered one salient finding is that autonomous vehicles with electric powertrains have lifetime greenhouse gas emissions that are 40 percent lower than vehicles powered by internal-combustion engines. The lower emissions result from the inefficiencies associated in producing electricity from fuel combustion and a sharper fuel-consumption rises when extra mass is added to a vehicle powered by an internal-combustion engine.

Study lead author Jim Gawron, a graduate student at the U-M School for Environment and Sustainability and at the Ross School of Business said, “We’ve shown in this paper that a battery-electric vehicle is a better platform for CAV components compared to the internal-combustion engine vehicle in terms of minimizing environmental impacts.”

The specialists discovered that the sensing and computing subsystems in connected and automated vehicles could raise a vehicle’s energy use and greenhouse gas emissions by 3 to 20 percent due to rise in power consumption, weight and aerodynamic drag.

But the operational advantages of autonomous vehicles, which consists smoother, more efficient traffic flow, are estimated to outweigh those rise in most cases.

The investigation additionally discovered that:

Wireless data transmissions required for onboard navigation maps are an exceptional contributor to a CAV’s energy use and associated greenhouse gas emissions and the resolution of the maps makes an enormous difference. Standard-definition maps outcome in lifetime greenhouse gas emissions that are 35 percent moves down than the emissions produced when high-definition maps are transmitted over a 4G LTE network.

The amassed weight and power requisition from the onboard computer produce exceptional impacts. For the medium-size sensing and computing subsystem that served as the baseline scenario in the study, the computer invested 45 percent of the weight, consumed 80 percent of the power, and was responsible for 43 percent of the greenhouse gas emissions.

Large, exterior-mounted CAV components can exceptionally increase aerodynamic drag and fuel consumption, potentially offsetting the environmental advantages of autonomous vehicles. Sensing and computing components will continue to be miniaturized and packaged more compactly; but in the near term, the size and shape of exterior-mounted equipment will have tangible impacts.

According to the new study, different caveats accompany the study’s conclusions about the potential environmental benefits of automated vehicles. First, those conclusions are based on the assumption that the operational efficiencies of CAVs can lead to a 14-percent reduction in fuel consumption over conventional vehicles, based on an analysis of antecedent work by the National Renewable Energy Laboratory.

But if the real-world savings from CAV efficiencies are significantly lower than 14 percent, the environmental benefits are diminished or vanish completely.

Also, if the onboard computers require a lot more power than the 200 watts modeled in this study, the net emissions reductions are terminated.

The vehicles investigated in the study are Level 4 connected and automated vehicles, defined as vehicles that can operate in absence of human input or oversight under select conditions. Prototype Level 4 CAVs are among the vehicles being tested at U-M’s Mcity, a public-private R&D initiative leading the transformation to connected and automated mobility.