Navigant Research Blog

Cloud Connections Bolster In-Vehicle Systems

— January 26, 2015

With the average transaction prices of new vehicles in the United States hitting nearly $35,000 at the end of 2014, drivers can be grateful that the cars they purchase are also more durable and reliable than ever before. The average age of the more than 200 million vehicles on the road in the United States today is now nearly 11.5 years.  However, that longevity has a big potential downside: as computing and communications technology marches on to improve safety, efficiency, and reliability, many of those existing cars will be incapable of participating in these advances.  Luckily, cloud computing could come to the rescue.

According to Navigant Research’s report, Autonomous Vehicles, full-function self-driving vehicles aren’t expected to be available in significant volumes until late in the 2020s.  Until the fully self-driving car arrives, we’ll have a steady stream of incremental improvements in advanced driver assistance systems.  Thanks to increasing connectivity in vehicles, we’re also less likely to be stuck with the capability that was built-in when the vehicle rolled off the assembly line.

No Car Left Behind

General Motors (GM) and Audi are among the manufacturers that are already building 4G LTE radios into many of their new vehicles.  When this capability is combined with advanced new microprocessors from companies like NVIDIA and Qualcomm, vehicles will be able to leverage cloud computing infrastructure to get smarter as they age, rather than being left behind.

At the 2015 Consumer Electronics Show in Las Vegas, NVIDIA unveiled a new generation 256-core processor, called the Tegra X1, along with electronic control units powered by this advanced chip.  One of the problems that driver assistance and autonomous systems have to solve is being able to recognize and distinguish the objects detected by all of the sensors on new vehicles.  The human brain is remarkably adept at distinguishing the nuances between an animal and pedestrian or an ambulance and a delivery van.

Detection before Failure

This sort of image recognition is far more difficult for a computer, so the Tegra X1 is designed to collect image data from its 12 camera inputs and transmit it back to data centers where it can be aggregated with information from other vehicles.  By combining data from many vehicles, the object recognition can be dramatically improved, and updated image libraries can be fed back to vehicles for improved onboard sensing ‑ even without changing hardware.

GM is also harnessing the power of the cloud to provide drivers with predictive diagnostic information for their vehicles using OnStar.  Available for more than a decade, OnStar provides subscribers with vehicle health reports when faults are detected.  Now, by monitoring critical systems such as the battery, starter, and fuel pump and sending this information back to the cloud, OnStar is able to detect subtle changes in performance that have previously been shown to be precursors to component failures.  The OnStar Driver Assurance system can then notify the driver so that an impending problem can be corrected before the driver is left stranded on the side of the road.  This predictive diagnostic system will be available on several of GM’s 2016 model year vehicles.

As automakers roll out new infotainment interfaces, such as Apple CarPlay and Google’s Android Auto, drivers will also benefit from improved voice recognition that leverages massive data centers run by these technology companies.  More robust and reliable voice control will help reduce driver frustration and keep their attention on the road ‑ at least until the car can take over completely.

 

Sensor Technology Not Yet Ready for Self-Driving Cars

— December 30, 2014

According to Navigant Research’s report, Autonomous Vehicles, some limited self-driving vehicles will arrive by 2020, but widespread adoption of full-function autonomous vehicles won’t happen until at least the late 2020s.  Over the next 15 years, manufacturers are expected to continue making incremental progress with more capable assist systems and semi-autonomous systems, such as the Super Cruise system recently announced by General Motors and the Advanced Highway Driving Assist from Toyota.

Many of the vehicles sold today already contain most of the essential building blocks to enable them to operate autonomously.  However, a new study from AAA indicates those pieces are not yet all that reliable or consistent.  Based on that, it’s reasonable to deduce that we cannot yet trust those systems for full automation, and drivers must remain fully engaged in vehicle operation.

AAA recently conducted a series of tests of blind spot monitoring and lane departure warning systems and found that the performance can vary widely among different vehicles and under different conditions.  “AAA’s tests found that these systems are a great asset to drivers, but there is a learning curve,” says John Nielsen, AAA’s managing director of Automotive Engineering.

Enhancement, Not Replacement

Automakers have always marketed these features as assist systems meant to augment rather than replace the control of an attentive driver.  For example, the lane-keeping assist that is part of many such systems can automatically provide some correction to help prevent the vehicle from drifting out of a lane.  However, these systems typically also monitor the driver using sensors in the steering wheel or torque feedback in the steering column to prevent hands-off driving.

Advanced Driver Assist Sensors: Ford Fusion

 

 

(Source: Ford Motor Co.)

Similarly, blind spot monitoring sensors don’t negate the need to check mirrors regularly while driving.  The sensitivity and field of view of each vehicle depends on where the manufacturer has positioned the sensors behind the rear bumper cover.  Each of the vehicles tested by AAA would detect vehicles or cyclists in the adjacent lanes at different times.

My own experience driving a wide variety of vehicles equipped with both types of assists has been as spotty as the results from AAA indicate.  Lane departure systems use digital cameras and sophisticated image processing algorithms to look for lane markers painted on the pavement, and all of the systems currently on the market only function at speeds above 35 mph to 40 mph.   The problem arises when the lane markers aren’t clearly visible or don’t exist at all.  On a rural road or residential street with no markings, you’re completely on your own.

Alerts and Alarms

Another problem is the lack of consistency in how alerts are presented to drivers by different manufacturers.  Vehicles can have audible, visual, haptic alerts, or a combination of these.  Sometimes, the systems are overly sensitive and trigger so many alerts that drivers are tempted to disable the system to avoid being annoyed, thus defeating the purpose.  Other times, the monitors don’t provide an alert until it’s too late to be useful.

Sensing systems will need to be robust enough to provide accurate warnings or control inputs under all driving conditions, and designers will have to develop human-machine interfaces that provide information to drivers without being overwhelming.

 

Modular Mobile Phones Could Connect Vehicles

— December 23, 2014

If you drive to work or school or the grocery store, there’s a good chance that your vehicle is at least 11 years old and probably runs just fine.  If, on the other hand, you dig an 11-year old cell phone out of your junk drawer, there’s a good chance it won’t even start up and if it does, it might not have a network to connect to.

That dichotomy between vehicle longevity and electronic obsolescence will pose an increasing problem going forward as our vehicles become more connected to the world around us.  Connectivity is likely to be one of the key building blocks toward a world of automated driving (as described in Navigant Research’s report, Autonomous Vehicles), and an idea from a young Dutch designer that’s being brought to reality with the help of Google could be an important part of the solution.

In mid-2013, Dave Hakkens created a modular phone concept called Phonebloks that would enable users to pick and choose the components that make up their communication devices.  By swapping out modules for cameras, processors, batteries, displays, and other components, consumers could upgrade only the pieces they needed, reducing electronic waste and prolonging the life of the devices.  Google engineers subsequently picked up on the idea and launched Project Ara to help bring Hakkens’ concept to reality.

Keep the Vehicle, Toss the Phone

The Project Ara team has developed a novel magnetized mechanical interface to hold the modules together and provide the electrical interconnects that enable the whole system to work.  In October 2014, Google demonstrated a working prototype Ara phone running Android.  However, as Hakkens acknowledges, the idea doesn’t have to be restricted to the devices we carry in our pockets.

In 1996, General Motors launched OnStar, the first successful vehicle telematics system with a built-in cellular radio that enabled customers to get their cars remotely unlocked or automatically call for assistance in the event of an accident.  Unfortunately, those early systems used the first-generation analog cellular network, and by 2007, they were permanently disconnected as the network was decommissioned.  Mechanically, those vehicles still had many years of useful life left in them, but it would have been impractical to replace the OnStar systems with newer technology.  That pace of change in wireless communications is not expected to slow down anytime soon, as we’ve already moved past 3G into 4G wireless in the 7 years since the original OnStar shutdown.

Insert Here

If it works, Project Ara could provide the solution to the conundrum of long-lived vehicles and changing communications technology.  Google has not responded to a request for comment on the project, but if the company follows its past practice with Android and Chrome, it would not be surprising to see Google either open-source or license the interface on reasonable terms.  This would enable automakers to incorporate one or more Ara-style slots in the vehicle while companies such as Qualcomm or Samsung produce new radio modules to support updated networks or capabilities.  Manufacturers could even produce aftermarket systems to allow the installation of Ara modules into existing vehicles, enabling them to join in with the expanded connected vehicle ecosystem.

Decoupling the communications technology from the vehicle lifecycle could enable drivers to keep existing vehicles on the road while gaining the potential safety and efficiency benefits powered by ever-more affordable and capable electronic systems.  What seemed like a fairly simple idea from Dave Hakkens could ultimately have a much wider impact on society.

 

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.

 

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