Study finds autonomous vehicles may plausibly nearly double, or nearly halve, road transport GHGs depending on the scenario
A study by a team from the University of Leeds (UK), University of Washington (USA) and Oak Ridge National Laboratory has found that vehicle automation might plausibly reduce road transport GHG emissions and energy use by nearly half—or nearly double them—depending on the scenario.
The researchers also found that many potential energy-reduction benefits may be realized through partial automation, while the major energy/emission downside risks appear more likely at full automation. In a paper describing the study published in the journal Transportation Research Part A, the authors also presented implications for policymakers and identify priority areas for further research.
|Changes in energy intensity per kilometer, travel demand, and total road transport energy consumption for light-duty (LDV) and heavy-duty vehicles (HDV) under varying automation scenarios. Wadud et al.Click to enlarge.|
Automation per se is unlikely to significantly affect energy consumption, but is expected to facilitate myriad other changes in the road transportation system that may significantly alter energy consumption and GHG emissions. For example, automated vehicles may enable the adoption of energy-saving driving practices, and facilitate changes in the design of individual vehicles or the transportation system as a whole that enable reductions in energy intensity. Fully automated, self-driving cars can offer on-demand mobility services and change vehicle ownership and travel patterns. However, they are also likely to substantially change the in-vehicle experience and the cost of drivers’ time in the vehicle (perceived cost for private drivers, and actual cost for commercial drivers), which could lead to more demand for travel by car and modal shift away from public transport, passenger train and air travel. Freight truck travel could also increase. These travel demand and energy intensity related changes would have large total energy and carbon implications.
Researchers, analysts, and policymakers must begin considering the impacts of vehicle automation on future travel and energy demand, and on the efficacy of different policies and technologies intended to mitigate the effects, if they are adverse from societal perspectives. Given the potentially large influence of vehicle automation on travel behaviour, mobility, traffic capacity and end-use energy efficiency, any study on mitigating energy consumption or carbon emissions from the transport sector is likely to miss the mark if the impacts of vehicle automation are not understood. As such, there is a need to get a sense of how automation may affect travel and energy use, by how much, and to identify opportunities to support and guide an environmentally beneficial transition toward vehicle automation.—Wadud et al.
The study had four main goals, the authors said:
To review key mechanisms through which automation may affect transportation energy consumption, including travel demand as a major mechanism;
To estimate quantitatively the potential magnitudes of these effects, providing bounds on these effects in the context of total road transport energy demand and emissions;
To develop several scenarios to illustrate plausible ranges of overall future energy and carbon impacts of vehicle automation; and
To identify key leverage points for policymakers at which vehicle automation can be directed toward the goal of reducing energy consumption and carbon emissions.
The study does not attempt to predict definitive changes in energy consumption due to vehicle automation.
The researchers used the “ASIF” framework, which expresses transport carbon emissions in terms of 10 the major drivers, in their analysis:
Emissions = Activity Level · Modal Share · Energy Intensity · Fuel Carbon Content
The ASIF framework makes explicit the fact that use-phase emissions from a transportation mode depend on the overall level of travel activity; the fraction of that travel conducted in that mode; the average energy consumption per kilometer in that mode; and the carbon intensity of fuels used by that mode.
The researchers also developed several scenarios to explore the potential range of overall impacts that automation may have on energy consumption and carbon emissions over the long term.
In terms of energy intensity effects, the researchers found that vehicle automation may reduce the energy intensity of vehicle travel by enabling more efficient operations, facilitating a shift away from the owner-driver model of personal mobility, and altering the size, weight, and efficiency of vehicles. Related effects include:
- Congestion mitigation
- Automated eco-driving
- Changing highway speeds
- De-emphasis on performance
- Improved crash avoidance
- Vehicle right-sizing
- Increased feature content
However, they also found that vehicle automation could increase transportation energy consumption by increasing vehicle travel, as a response to a sharp reduction in generalized travel costs. Travel demand may also grow as automation makes private vehicle travel accessible to demographic groups who do not drive now or drive less than they might otherwise. Automation can also allow wider-scale adoption of carsharing or on-demand mobility services. Related effects include:
- Increased travel from reduced cost of driver’s time
- Increased travel due to new user groups
- Changes in mobility service models
The analysis also suggested that automation could encourage a change in the carbon intensity of fuels used.
Ultimately, we should not view vehicle automation through rose-colored glasses. The ultimate effect of automation on travel and energy demand may be positive or negative, and we cannot yet say which. Clear-headed analysis, evaluation, and adaptive policymaking provide the greatest chance of realizing the full benefits of automation and minimizing the costs.—Wadud et al.
The authors suggest that policymakers could focus less on accelerating the introduction of complete automation and more on promoting aspects of automation with positive environmental outcomes. For example, regulators could encourage standardization of car networking protocols to allow vehicles to communicate with each other on the road and therefore deliver benefits such as platooning.
The researchers warn that, if a high level of automation becomes the norm, it may be necessary to financially intervene in transport decisions. For example, self-driving cars’ navigation and communication systems could be used as a basis for road pricing schemes to control congestion and reduce overall travel demand.
Wadud, Z, MacKenzie, D and Leiby, P (2015) “Help or hindrance? The travel, energy and carbon impact of highly automated vehicles.” Transportation Research Part A: Policy and Practice (In Press)