Navigant Research Blog

For Self-Driving Cars, Automakers Consult Silicon Valley

— December 10, 2014

The fully autonomous vehicle (AV) is coming, and early models will be on roads sometime around 2020.  To reach this milestone, automakers are turning to Silicon Valley for its expertise in connected devices, the Internet of Things, and human-machine interfaces.  A recent tour of the 18-month-old Nissan Research Center (NRC-SV) in Sunnyvale, California underscored the importance of this trend in relation to the automotive industry’s development of the AV of the future.

While some autonomous drive systems that rely on cameras, lasers, and sensors, such as lane keeping and automatic braking, don’t require vehicle connectivity, the fully autonomous vehicle will.

Reaction Time

The fact that AVs are likely to be far safer than non-autonomous, human-driven vehicles has been well-established.  However, to provide the type of near guaranteed safety the auto industry and customers require, the fully autonomous vehicle described by NRC-SV Director Martin Sierhuis will be “the most complex system in the world.”

For starters, the fully autonomous vehicle needs to be able to communicate with other vehicles and infrastructure, anticipate/predict human and non-human (animal) behavior, be personable, constantly observe and relay information back to the Internet, and act quickly upon information received from all these sources.

Watch for Deer

Information on weather conditions, traffic congestion, and road construction are valuable assets to other vehicles and, in an ideal system, can be transferred seamlessly.  Further, observations made by vehicles can be used to maintain a near real-time map of the world, given changes to road infrastructure.  However, the most valuable pieces of information will be on how AV predictive systems can be improved and how AVs fail.

A major challenge for AVs is the unpredictability of the world.   The awkward four-way stops, the sudden trajectory deviations, the deer on the side of the road, the ear buds-wearing bicyclists in downtown San Francisco, etc. all have to be accounted for.  To function effectively, an AV must be able to predict both human and animal behavior better than humans do.  Predictions are based on data; as more data is accumulated on humans through AVs, they will in turn be better able to predict human behavior and, therefore, safer in the more pedestrian-centric urban environments.

The above are all examples in which the sharing of information from AV to AV will avoid catastrophe; however, it must be assumed that failures will eventually happen.  Yet, the silver lining will be that when the AV eventually does fail, the circumstances of that failure will be shared, and the overall system will learn from it.  As Sierhuis explained, “The same accident will never occur again.”


How EVs Can Aid the Smart Grid

— December 8, 2014

The plug-in electric vehicles (PEVs) available today can help grid operators manage the grid – although few in use actually do.  This is not too much of a problem now, but as more PEVs populate roads, utilities are likely to become increasingly concerned with managing and making use of these mobile assets.  Today’s PEVs represent a significant increase in residential electricity demand and, if unmanaged, could cause problems with distribution-level transformers and could drastically increase demand during peak hours when PEV owners return from work and plug in their vehicles.  The effect would force utilities to make upgrades to distribution networks that would likely be passed on in the form of higher rates to consumers.

Contrarily, PEVs also represent an increase in load that could be used to capture renewable electricity generation and help balance generation with demand, theoretically making electricity marginally cheaper and cleaner.

This latter scenario would likely decrease electric bills, as the utility would be able to provide more energy through the existing infrastructure, thus avoiding transformer capacity upgrades.  Most of the technologies to accomplish this process have already been developed, and multiple companies and organizations, such as GreenLots, PowerTech Labs, and the Electric Power Research Institute (EPRI), are busy testing respective platforms for future deployment.  However, to achieve such a paradigm, utilities need to develop demand response (DR) programs that are both simple and compelling to the consumer – not an easy task.

Thin Margins

A PEV owner’s understanding of why the charging of his or her car should be scheduled or managed by the utility is not fundamental to the owner’s participation in any given utility DR program.  However, the price at which the PEV owner will choose to participate in the program is.  In other words, the more money saved, the more PEV owners will be willing to participate.  Given that, there is a problem: driving on electricity is really cheap.

Most battery electric vehicles in use have an operating efficiency of around 3 miles/kWh, and the average residential electricity price in the United States is around $0.13/kWh.  This means that if the average electric vehicle is driven 1,000 miles in a month, energy costs will be slightly over $40.  This low energy cost means the actual savings from participation in a DR program would also be low and might not justify the investment from the utility or the energy aggregator for the smart charging infrastructure.

On the other hand, investment costs are zero for the PEV owner, as much of the necessary system elements already come standard on PEVs.  They will likely be low for utilities and/or energy aggregators depending on how many vehicles participate.  Additionally, the costs and savings equation will vary widely across the United States, based on a utility’s ability to balance the grid without PEVs.  The trick for utilities and energy aggregators will be to make DR compelling enough to attract future PEV owners who may be less tech-savvy than initial PEV adopters.


Tesla Direct Sales Banned in Another State

— October 28, 2014

In mid-October, Michigan governor Rick Snyder signed legislation that effectively bans Tesla’s direct-to-consumer sales business model in the state.  Direct sales of cars are also currently banned in Texas, Maryland, Virginia, and Arizona, and limitations are in place in Georgia and Colorado.  Despite these setbacks, Tesla has overcome battles in Minnesota, Massachusetts, North Carolina, and recently New Jersey.

The reason Tesla’s sales model has been banned has been explained many times, including past Navigant Research blogs, found here and here.  The most critical factor is that Tesla’s direct model leaves established car dealerships out of the business transaction.  This supposedly gives Tesla an advantage over other automakers (like General Motors, which supports the Tesla bans) that must sell their vehicles through dealerships.

As Tesla sales continue to grow, state laws protecting dealerships will come into sharper focus.  Automakers and dealers will have to adapt to legislative reforms accordingly.  Given that, it’s harder to imagine a future where Tesla is forced to sell through dealers than to envision one in which all automakers are able to set up similar direct-to-consumer sales models as they see fit.  Some automakers are already adding more direct pathways for consumers to communicate directly with the automaker on vehicle specifications and deliveries.

Time to Evolve

Under these changing conditions, automotive retail must adapt to the new, information-based, time-efficient market or become structurally obsolete.  Consumers now have more knowledge, power, and control over their vehicle purchases than ever before, and future car buyers will be far more autonomous.  Greater transparency around vehicle costs, automaker inventories, and financing mechanisms enabled by the Internet shifts the bargaining chips heavily in the consumer’s favor.

The disconnect between established dealers and automakers and the new tech-savvy, well-informed consumers will only become more pronounced if state dealer associations focus on campaigning against Tesla rather than pushing industry adaptation.


In Ethanol, Cellulosic Coming to Push Out Corn

— October 20, 2014

The last few months have been big for cellulosic biofuels in the United States.  The first of three commercial-scale cellulosic ethanol plants to come online this year, Project Liberty, opened in Iowa in September.  In July, the U.S. Environmental Protection Agency (EPA) expanded the definition of the cellulosic biofuels pathway to include biogas used for transportation via compressed natural gas (CNG), liquefied natural gas (LNG), or electricity.  At full capacity, Project Liberty will produce 25 million gallons annually; the two other plants scheduled to open this year will run at 25 and 30 million gallons, respectively.  If the plants are successful, this could be the beginning of cellulosic ethanol supplanting corn-based ethanol’s hold in the U.S. biofuels market.

Cellulosic ethanol’s major advantage over corn-based ethanol is that its feedstock is organic material waste rather than food/grain.  This avoids controversial issues regarding food vs. fuel and minimizes the conversion of arable land to farm land, which experts contend makes cellulosic ethanol far more environmentally sustainable and less politically divisive than corn-based ethanol.  The disadvantage of the fuel is that it’s ethanol.

Flat Gas

Ethanol’s end market is gasoline, primarily used for light duty vehicles in the United States and Brazil.  It can only supply up to 10% of the fuel in a vast majority of the vehicles in use in the United States due to regulatory constraints and reluctance on the part of automakers and fuel retailers to adopt higher ethanol-gasoline blends.  If gasoline consumption in the United States was growing, this aspect wouldn’t be a problem, but it’s not.

In Navigant Research’s reports, Global Fuels Consumption and Light Duty Vehicles, it is estimated that light duty vehicles account for 94% of gasoline consumption in the United States.  Over the next 10 years, the light duty vehicle fleet will become far more energy efficient, thanks to vehicle electrification, vehicle lightweighting, and engine downsizing.  The end result is that the amount of gasoline-ethanol blends consumed in 2023 will likely be 12% less than 2014 levels.

The Cellulosic Edge

Consumption of ethanol is driven by the Renewable Fuel Standard (RFS), which mandates specific volumes of biofuels be blended into the fuel supply.  The standard is adjusted each year to reflect anticipated industry production volumes by biofuel pathway, so that biofuels producers can be assured their product will be purchased by blenders.

Given cellulosic ethanol’s sustainability appeal over conventional ethanol, and the limited market in which these pathways compete, and despite the high cost of cellulosic compared to conventional ethanol, it’s likely that annual adjustments to the RFS will ensure that cellulosic production feeds into the U.S. fuel pool at the expense of conventional ethanol.  That means that the EPA may be inclined to lower conventional ethanol mandates against increases in cellulosic capacity – making cellulosic more valuable to blenders than conventional ethanol.  As a result, conventional U.S. ethanol will likely become an export fuel, going to foreign markets that currently make up a little over 45% of the global market.


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