Navigant Research Blog

With Predictive Navigation, Smart Cars Find Their Own Way

— December 15, 2014

The flood of available data from many sources – traffic updates, GPS, onboard sensors, etc. – will change the ways in which we’ll get around in the coming years.  One tangible manifestation, happening now, is predictive navigation.

From Google to Bosch to Volkswagen, a range of companies in the automotive and technology industries are starting to harness the power data to provide personalized real-time guidance and enhanced vehicle control that could lead to reduced congestion and fuel consumption – and, eventually, to hybrid powertrains that automatically adjust the balance between battery and engine output based on upcoming terrain.

Go This Way

Data about where and when we travel and how fast we go is collected through a combination of built-in systems, such as General Motors’ OnStar and Hyundai’s BlueLink, and brought-in systems, specifically smartphone apps.  Every time a driver launches a navigation app, such as Waze, Google Maps, or TomTom, information about speed and location is transmitted back to the cloud and aggregated with other factors, such as weather forecasts, construction sites, and local events, to determine where backups are occurring or are likely to occur and to provide real-time feedback.   The macro data can be combined with local data about individual driver habits to automatically provide alerts about traffic backups and alternate routes before you turn the key.

Google has provided these predictive alerts for more than 2 years as part of the Google Now functionality on Android phones.  At a recent innovation workshop at its Wolfsburg, Germany headquarters, Volkswagen showed off its own in-car solution to provide alternative route suggestions even when drivers don’t need to use the navigation for common destinations.  Other automakers, including General Motors, have been testing solutions for plug-in electric vehicles, like the Chevrolet Volt, that will automatically preserve electric power for the last portion of a drive home through a residential area or even use up some of the low-charge buffer when the system predicts it will be plugged in soon.

Shortest Is Not Necessarily Most Efficient

Mercedes-Benz is now utilizing topographic map data as an input to the plug-in hybrid powertrain available in its S500 luxury sedan.  When the system detects that the vehicle is approaching the crest of hill, it will automatically shift the power distribution away from the internal combustion engine to the electric motor and then recover energy to the battery on the downhill side.   Ford has been researching eco-routing solutions for both plug-in and traditional vehicles that will calculate routes that use less total energy even though they may cover more total distance.

Everyone that drives in urban areas is well aware of the frustrations of sitting through several cycles of a traffic light while trying to make a left turn.  For the past decade, package delivery company UPS has been using big data and electronic maps to provide its drivers with customized daily routes specifically designed to keep left-turns to a minimum.   By using right turns whenever possible, even if it means going further, UPS had saved more than 10 million gallons of gasoline and reduced carbon emissions by 100,000 metric tons by 2012.

 

Street Lights Add EV Charging

— December 11, 2014

Sometimes a solution forms at the intersection of two challenges that may not seem, at first glance, to have anything in common.  For example, cities are perpetually seeking ways to increase revenue, and many owners of electric vehicles (EVs) want access to ubiquitous charging infrastructure.

Enter the new concept of retrofitting street lights with money-saving LEDs and EV charging ports.  City managers are moving toward central control of street lights by adding a control node, which enables them to reduce cost and integrate the lights with other systems, as my colleague Jesse Foote recently wrote.  With smart street lighting technology (as covered in Navigant Research’s report, Smart Street Lighting) in place, EV charging capabilities can also be added to street lights, creating a new revenue stream for municipalities.

A Light and a Charge

Among the first pilots of this combination are occurring in the cities of Munich in Germany, Aix-en-Provence in France, and Brasov in Romania.  BMW has two such lights at its headquarters in Munich and will add a series of enhanced lights in the city next year.  A consortium called Telewatt, led by lighting manufacturer Citelum, is similarly installing LED street lights with EV charging in Aix-en-Provence.  In Romania, local company Flashnet has integrated its inteliLIGHT management platform with an EV charger.

Motorists can pay for the EV charging using a mobile phone app.  Cities that have regulations allowing them to provide EV charging services can gain revenue to help balance the books.  They can also balance the additional power demand of EVs within their overall power management system.  Placing a Level 1 or Level 2 charging outlet on a light pole reduces the installation cost of bringing power to the curb, which otherwise can be several times greater than the cost of the equipment.  Cities that install these systems will help drive demand for EVs, which has the added benefit of increasing urban air quality.

This is another example of the integration of seemingly disparate city services into a smart city.  As detailed by Navigant Research’s Smart Cities Research Service, the move toward integrating power, water, transportation, waste, and building management will yield considerable savings while improving the quality of urban life for city dwellers.

 

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.”

 

Utilities Could Accelerate the E-Truck Market

— December 9, 2014

In November, a group of 70 U.S. utilities announced a major commitment to buying plug-in vehicles (PEVs), an initiative that could have a major impact on the plug-in truck market in the United States.  At a White House ceremony, a group of investor-owned utility executives committed to spending 5% of their annual fleet budgets on PEVs.  This reportedly will total around $50 million annually spent on PEVs.

It’s no surprise that utilities support the use of PEVs in their fleets, since it allows them to shift fuel budgets from petroleum to their own power.  But the reality of utility adoption of PEVs is that, while a handful of very forward-looking utilities, such as Pacific Gas & Electric and Florida Power & Light, have been fairly aggressive about integrating PEVs into their fleets, many others have tried one or two or have been looking to see the results of trials from the first movers.

Trucks, Not Cars

With this joint commitment, utilities can have a much bigger impact on the U.S. market for PEVs. But the best way to spend the money to really move the market for PEVs forward will be to spend it on trucks, not on passenger cars.  Passenger cars offer more bang for the buck, and create fewer headaches since passenger car PEVs have already been proven in the consumer market.  But for that reason, there is considerably less need for utility purchases to push the market.  $50 million would buy around 1,700 Nissan LEAFs, for example.  That is less than 2.0% of the total PEVs that Navigant Research projects to be sold in the United States in 2014 in its report, Electric Vehicle Market Forecasts.

If utilities invest in electric trucks, they could have a much bigger impact.  Plug-in trucks are still in the pilot, demonstration or very early commercial stage, as discussed in Navigant Research’s report, Hybrid and Electric Trucks.  This market suffers from low overall volumes and a splintered market, with many small niches to fill, including urban delivery vans, bucket trucks, service vehicles, and suburban or long-distance delivery.  One reason so many e-truck companies come and go is the challenge of achieving sufficient volume to bring down costs through economies of scale.  If utilities team up to place larger orders for plug-in trucks, they can have a real impact on the market.

Market Maker

For example, $50 million could buy around 250 plug-in bucket trucks with electric power takeoff, one of the more promising applications for plug-in trucks.  While that number may seem small, companies targeting this space are currently seeing orders in the tens – and these are still largely supported by government funding.  Whatever the application, a combined effort to place larger orders for plug-in trucks could have a major impact on this still-struggling market – and  could pay off for utilities that will benefit from using more fuel efficient trucks should this market succeed.

 

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