Connected Vehicle Technology Gaining Momentum

A watershed moment may be approaching for the connected vehicle market.
The National Highway Traffic and Safety Administration (NHTSA) is about
to start on the path towards mandating connected vehicle technology

As reported by GPS World: During the GPS World connected vehicle webinar, held September 19, I noticed differences in how the audience characterized the 'connected vehicle'. 

The connected vehicle enables information to be exchanged with other vehicles, devices and/or road infrastructure to provide safety, mobility and consumer functionality. 

The devices that are used with the connected vehicle can be nomadic (phone, tablet, personal navigation devices), vehicle embedded and aftermarket devices. Communication options are currently cellular, Wi-Fi or DSRC/WAVE.

Regulation Pushing Connected Vehicle Forward.

 In a recent statement, the National Highway Traffic and Safety Administration (NHTSA) asserts that

connected vehicle technology “can transform the nation’s surface transportation safety, mobility and environmental performance.” NHTSA is expected to start rulemaking on the connected vehicle later this year, which could result in a connected car industry mandate in the U.S. While it could take five or more years for final rules and several more years for rules to take effect, it would be a transformative event. “In six years, I expect to see vehicles widely using the technology,” said Scott McCormick of the Connected Vehicle Trade Association. “Vehicle manufacturers are eager for connectivity in vehicles, but need to understand the regulations that will be in play. This hasn’t been idle time, as vehicle makers are ahead of the game and have already embedded some connected vehicle technology into vehicles that can later be activated.”

The commercial fleet market has been the first adopter of connected vehicle technology as efficiencies provide cost savings, but the automotive market is poised to catch up. “Fleets now have access to actionable intelligence from the field,” said Andrew Maliszewski of Micronet, as well as an industry consultant. “Business decisions are now being made from data, including fuel levels, driver behaviors, vehicle performance, weather and traffic conditions, and even real-time trailer connect/disconnect events.”

Ownership of Data is Tricky.  Some of the data that is produced inside a vehicle will be of great value to marketers. It will reveal personal information, including your driving habits, where you go, and how you react to in-vehicle marketing. David Jumpa of Airbiquity asserts, “There is uncertainty on who will own the data, but the sensory data, such as how you brake and accelerate, would be owned by the vehicle OEM.” When polled, many listeners of the webinar opined that content and app providers, and not vehicle OEMs or data infrastructure companies, will own personal data generated.

Making Money, or Not. The technology of the connected vehicle market hasn’t been easy, but it has been much simpler than finding the revenue models that will support companies in this market. “In the past, the vehicle market would use a tier-one manufacturer to deliver the entertainment solution, including maps and routing,” said Scott Sedlik of Inrix. “That isn’t the case now, and multiple suppliers work together and are also having to carry the risk that the vehicle OEMs had solely carried.” Some of the content and app providers are making money; others are figuring out the right business model. One of the questions that remain is whether the OEMs will pay for in-vehicle services and content. This is a pivot point of business, Sedlik adds.

Mobile App Marketing Cost at High. For brands that proactively market their apps, the cost of acquiring a loyal user increased in July to $1.80 according to Fiksu’s Cost per Loyal User Index. This is a jump of 30 cents from June, falling just a penny short of the December 2011 price of $1.81. Fiksu attributes the cost rise to brands leveraging Facebook’s mobile app ads, which target consumers based on app and games access on smartphones.

Mobile Map Usage. More than 60 percent of iOS users accessed Apple Maps at least once during the previous 30 days, reports Mobidia. That isn't too surprising given that it comes installed on the phone. However, 20 percent of iOS users accessed Google Maps during the same period — impressive, since the user has to go to the effort of installing the software. Google Maps usage is heavy, although not as heavy as Apple Maps use.  55 percent of iOS users that use Google Maps, use it weekly; 80 percent of Apple Maps users use it weekly. Not bad, Google.  Google, which recently acquired Waze has embraced the 'crowdsourced mapping' and near-real-time road conditions approach to digital map data; a trend that appears to be spreading among other map vendors as well.

Radio Dot System to Provide In-Building Wireless Carrier Coverage

As reported by PC World: Ericsson says it has a small solution to the big problem of weak mobile service in enterprises.

On Wednesday, the world’s largest cellular network vendor introduced a radio that can fit in the palm of your hand and hook up to a full-size base station via conventional LAN cables. The so-called 'Radio Dot System', due to ship late next year, will let carriers fill large and medium-sized buildings with strong voice and data signals while keeping their equipment and management costs low, Ericsson said.

While traditional cellular networks are built around large outdoor “macro” cells, most mobile use happens indoors. To accommodate all that voice and data demand, mobile operators have long installed DAS (distributed antenna systems) throughout buildings and more recently have used small indoor cells, which are miniature versions of the macro cells on towers outside.

However, buying and installing the specialized DAS equipment is expensive, and managing and coordinating a collection of small individual cells around a building is complicated, Ericsson CTO Ulf Ewaldsson said. Among other things, small cells sharing the same spectrum with macro base stations have to turn down their power if they are in danger of interfering with the bigger cell, he said.

Ericsson plans to solve those problems by putting the core components of a macro cell into a building and spreading the radio parts of the cell throughout the rooms as Radio Dots. The Dots are disk-shaped units that weigh just 300 grams. The core unit, called the baseband, will be able to manage as many as 96 Radio Dots as one large cell. Another radio platform, called an IRU (indoor radio unit) will sit in between the dots and the baseband and house some other radio components. The system can be used for both 3G WCDMA and 4G LTE.

“We’re splitting the radios in a new way,” Ewaldsson said. “We put as little as possible in a radio dot that can do the radio transmission and the antenna piece on a wall.”

As demand for coverage or capacity in the building grows, carriers will have many options for scaling up the system because all the dots are logically managed as one base station, Ewaldsson said. Also, the full-size macro baseband that the dots share will have a complete set of features, instead of the subset that’s included in small cells, and can be more easily updated, he said.

Ericsson claims a Radio Dot System could cut installation time by 70 percent and capital cost by 60 percent compared with a DAS. For one thing, the links between elements will use the same type of Category 5, 6, and 7 copper cables used for conventional LANs, which are less expensive than the fiber-optic wiring typically used with a DAS, Ewaldsson said.

Enterprises may look to the Radio Dots when it comes time to replace a DAS, Ovum analyst Daryl Schoolar said. The system may also be an attractive DAS alternative because it could economically be deployed in just part of a building, rather than requiring the scale that a DAS needs, he said. But there are also other ripe opportunities for boosting indoor coverage, he said.

“It really could cover a lot of areas out there today,” Schoolar said. “The prime real estate for the small cell is really going to be indoors ... because so much stuff goes on indoors.”

However, the very BYOD trend that is bringing employees’ own mobile devices into the workplace could make Radio Dots less attractive in some cases.

“What Ericsson is showing is a very operator specific solution, but if you have a deployment area where workers are spread out among four different mobile operators, the value of that solution is diminished,” Schoolar said. “Also it locks a business into a specific operator, and that business may want more flexibility.”

With a DAS, by contrast, it’s typically easier to bring multiple carriers into the system, said Peter Jarich of Current Analysis. A Radio Dot System would be easier to install as an overlay, but in new construction, including a DAS is not as big a burden, Jarich said.

At least two major carriers are interested in Radio Dots. AT&T is participating with Ericsson in Wednesday’s announcement, and Verizon Wireless also plans to test the system. “We have seen it, we like it and we look forward to testing and trialing it,” Verizon spokesman Tom Pica said via email.

Geomagnetism to Help Map Buildings GPS Doesn't Reach

Instead of using Wi-Fi signals to triangulate a device’s
location, IndoorAtlas tracks variations in the Earth’s
magnetic field to pinpoint location within a building.

As reported by GigaOM: IndoorAtlas has entered the increasingly crowded indoor mapping and navigation space, definitely has a trick up its sleeve that sets it apart from other location-based technology companies. Instead of using Wi-Fi or Bluetooth signals to triangulate a device’s location within a building, it’s using the Earth’s geomagnetic field.

Our smartphones share one thing in common with many animals: they have internal compasses that can orient themselves to the Earth’s magnetic field. And just as animals can detect local variations in that magnetic field to find their way around, our phones’ digital compasses can do the same. Structures and even furniture within buildings such as metal shelves naturally produce those geomagnetic anomalies, and by logging those anomalies on a map, they can be used to pinpoint a device — and its owner’s — exact location indoors.

Indoor navigation remains one of the last frontiers of digital cartography because buildings block the GPS signals we depend on to determine location. A raft of companies have sprung to try and fill that radio silence with Wi-Fi signals, the idea being that most public buildings are rife with Wi-Fi networks. By measuring the signal strength and direction of known access points, a phone can plot its location within a few meters. Many of the big internet and networking companies have developed or bought scooped indoor Wi-Fi location technologies to start mapping buildings, and Apple is using similar techniques with iBeacon, which uses Bluetooth Low Energy as proximity-based location tool.

Instead of relying on external networks, though, Indoor Atlas has created a mapping platform that lets would-be cartographers and developers use their smartphone compasses to record the geomagnetic characteristics of any given locale. That data is then plotted onto a pre-generated digital map, which can then be used to create indoor location-based apps. They could take the form of, say, a mall way-finding app, or it could become an extension of a turn-by-turn navigation provider’s directions service – telling users where they need to go after they've parked their cars.

IndoorAtlas didn’t reveal exactly how precise its technology is, but it claimed it could place a user within a specific aisle and section of a grocery store. So it may not be able to tell if you’re standing right in front of the Weetabix, but it can definitely send you a notification – or a coupon – when you get close. The company said the technology is now available to developers on its website.

Wallet.AI Aims to Serve Up Location-Based Financial Advice

As reported by MIT Technology Review:  While navigating this increasingly connected world, you leave a trail of data about where you go, what you buy, and who you interact with. If you use a smartphone, this trail intensifies with every tweet and Foursquare check-in.

This may alarm some people, but Omar Green sees it as key to a smarter way to manage finances than a spreadsheet or piece of paper.

Green is founder and CEO of personal finance startup Wallet.AI, which is among a growing number of app makers incorporating so-called 'contextual awareness' into their software. The company is building software that includes a mobile app to sort through your data trail and, combined with insights about your spending habits, offer up timely financial advice. It might range from warning you not to spend more than $20 a day if you want to make rent at the end of the month to, perhaps, nudging you during a daily Starbucks run to get a drip coffee rather than your usual vanilla latte.

Green, who previously worked as director of strategic mobile initiatives for financial software company Intuit and built contextually aware phone software at a previous startup, likens the approach to the quantitative trading methods used by many financial firms; these methods incorporate lots of data to help traders make rational, nonemotional decisions.

“That was one of the ‘ahas’ I had,” Green says. “Let’s think about what it means to build a machine that can do some of this for me.”

With a user’s permission, wallet.AI will gather many kinds of information from the handset’s built-in sensors, and the social networks and financial transactions a user lets it access. Wallet.AI would analyze this data remotely, and distill it into tips it can serve up at specific times and places.

The San Francisco-based company is still keeping many details under wraps, but says it hopes to have a product out in about a year. Green expects this will be sold to financial institutions who can offer it to their clients and, perhaps, to consumers via app stores.

For now, Wallet.AI is focused on building a prototype, which it is testing with a small group of customers. Eventually, he expects to have cloud software chomping on data sets built up by users, determining different insights about their finances. “Anything we can use to help you make better decisions,” Green says.

If Wallet.AI can help, he figures, consumers will be willing to let Wallet.AI track sensitive personal information and glean ambient data from the world around them, and pay for it. The company is likely to face skepticism from some potential customers, though, who are wary of sharing data with yet another service, even if it can mean saving some cash.

So says Rick Oglesby, a payments analyst with Aite Group. He could see Wallet.AI appealing to financial institutions, such as banks, who may be interested in offering it to their customers in the hopes that it will help them stand out from the competition. Even if banks feel comfortable with it, though, it’s not yet known if consumers will want it. “Some people just want to shop and not think about money, but some people want to think about money all the time,” he says.

The Need for Integrated Telematics

Telematics adds increasing value beyond insurance
risk valuation, when used for real-time liability analysis
and driving operational improvement; which can help to
actively decrease accident fraud.

As reported by Actuarial Post: As well as enabling drivers to lower their premiums, data-rich telematics devices offers insurers tremendous potential that extends beyond traditional areas of risk, discounting and pricing. For this reason, many companies are now looking to sophisticated data technologies to become their ‘eyes and ears’ on the ground.

 There is no doubt as to the growing importance of telematics. As the concept of the ‘connected vehicle’ continues to emerge, it is estimated that, by 2025, 600 million cars globally will have embedded telematics. The result will be that vehicles will represent 5% of all connected devices, compared to just 0.1% today.

 As a result, telematics has become a key industry issue, with providers offering a variety of solutions tailored to the insurance market. Yet despite the inevitable hype around the potential benefits to be gained, too many companies remain stifled by a traditional departmental approach to data management, constrained by concerns over legal issues of data ownership, privacy and the cost of data storage.

 Insurers are isolating ‘black box’ telemetry data within data silos and in some cases are not even bringing data in-house, as their goal is simply to establish customer driving scores as the basis of setting commercially-competitive premiums. By focusing on telematics as a way to secure operational improvement, they are missing out on the consequential value which telematics can offer.

 With tools available to enable the business to look at telematics in the broader context of other customer and context data within the business, the time has come to broaden the focus beyond the operational value of better pricing and segmentation.

 Beyond Telematics

 As in other areas of insurance, companies are trying to find out as much information as they can about their customers.In achieving this objective, the advent of telematics means that they can now gain a much clearer perspective on each individual’s behavior behind the wheel, including speeds, braking and other driving habits.

 This is extremely valuable but can only present part of the picture in developing premiums and responding to claims more effectively. Every insurer has a lot of other valuable customer and context data sitting within the business, yet this has remained hidden when making critical judgments around setting premiums and assessing culpability in the event of a claim.

 In responding to this, it is now possible to link telematics data with near-real-time customer behavioral and lifestyle information, images and other contextual data, in order to take into account everything relevant to the interaction with that customer. Technology solutions can bring together telematics data with other relevant information in order to make more informed assessments on all aspects of the customer relationship.

 Traditional data warehousing solutions can be integrated with a discovery platform as part of a unified data architecture. For the first time, this allows the business to access and analyse different data types and styles –multi-structured data – in a way that was simply not possible using data warehousing tools in isolation.

 By putting together a comprehensive picture of individuals and their lifestyles, this enables the insurer to create a more competitive personalized premium which more accurately reflects the level of risk in each case.

 At the same time, the greater analytic value of this approach will also reduce the growing number of fraudulent ‘cash for crash’ claims, for example, by identifying those behaviors which might indicate a higher potential risk. Greater customer insights also enable the creation of more targeted cross-sell and up-sell opportunities, into such areas as life insurance.

 An integrated approach

 Insurance companies now understand the need to make best use of telematics data, in order to maintain and improve their competitiveness. Yet to-date, very few have recognized that the real ‘win’
 here is to be able to analyse this information at a more granular level and in a broader context.

 They typically already hold all this information within the business. The adoption of a robust unified discovery platform takes the business substantially closer to the ideal 360 degree customer view, by pulling together telematics with established customer data, newer behavioral information around how the customer interacts with the business online and other social behaviors. And in so doing, this means that the insurer can achieve a significantly better return on their often substantial telematics investment.

 This broader approach also impacts dramatically on usage-based insurance (UBI) or ‘pay for how you drive’ programs. Again, telematics provides real insights into the behaviors and driving patterns of insured customers, yet leveraging this data in conjunction with non-telematic information delivers much greater benefits.

 For example, in the event of an accident, this enables the business to better assess a customer’s liability for the purposes of settlement and/or litigation. Apportioning liability in claims can be complex, as it is typically based on the statements of the parties involved and those of eyewitnesses, which may not always be objective nor accurately reflect events as they actually occurred.

 Comparing objective telematics data from all the vehicles involved makes allocation of liability much easier, enabling the process to resolved more quickly and efficiently. Yet by adding the ability to query traditional claims, policy information and weather and traffic conditions at the same time, this would go much further in presenting a complete picture of the circumstances around the claim.

 Determination of liability could be made solely by running a query, avoiding the time and expense of taking statements. By cutting expenses and resolving claims more quickly, the cost of settlements would be reduced and customer satisfaction levels raised.

 Benefits for all

 The race is on for insurers to get the most from the rich vein of data telematics offers, in order to make the most effective and informed decisions. Yet as in many other aspects of the business, this can only truly be achieved through moving away from yesterday’s silos to a more transparent centralized view of all aspects of the customer journey.

 By incorporating telematics within a broader unified delivery platform, the insurer can increase retention rates, improve operational efficiencies and cut fraud, while the customer benefits from a faster, more personalized response to claims and other interactions with the business. Everybody wins.

Left-hand Turns Can Cost You

As reported through Yahoo! News: With a delivery fleet of 96,173 package cars, vans, tractors, and motorcycles, the United Parcel Service or UPS knows a great deal about efficient driving.

WAGA Fox 5 News interviewed UPS dispatch supervisor Matthew Frost to learn about some of the Fortune 500 company’s driving tips. Matthew said, “A lot of the managers here and supervisors here, they train their kids when they get of driving age and they train them the same way that we train our drivers here to keep ‘em safe.

Because these are proven methods that work.” After 6 years behind the wheel of a brown truck, Matthew now helps plan out the drivers’ routes. “When we design routes, as we put them together, we want to try to design it where the drivers are taking a right-hand turn as many as possible.” The company has found that right-hand turns are not only safer, but they’re also more efficient. It’s a tip that AAA agrees with. By using routing technology and avoiding idling at lights for left-hand turns, UPS was able to avoid 98 million minutes of idle time in a year; an estimated fuel savings of about $980,000 per year.

Other tips by the delivery giant include leaving at least one car length between you and the car stopped ahead of you to allow for reaction time. They advise using your eyes to scan the road and your mirrors. The dispatch supervisor said, “We train our drivers to check a mirror every five to eight seconds. Then check back to the front, then check another mirror, back to the front.” In addition to all of that, the drivers are given training drills to keep their minds sharp.

Matthew told WAGA that UPS has, "110,000 drivers. We log 3 billion miles a year and we average less than one accident per 1 million miles." That safe driving record is enforced with drivers undergoing 1 week of the company’s training after which they are allowed to get behind the wheel of a truck.

UPS is proud of their Circle of Honor club with 6,400 drivers who all have 25 years or more of safe driving.

How Nissan Will Roll Out Self-Driving Cars: Fricking Lasers

As reported by ReadWrite: It was an improbably futuristic scene: A man standing on a sunbaked tarmac in Irvine, Calif., next to a Nissan Leaf electric car, pushed a button on the hatchback’s key fob. The Leaf, unassisted by human intervention or preprogrammed maps, crawled at about five miles per hour through rows of parked vehicles, detected an SUV pulling out of a space, paused, and allowed the SUV to pull away. Then it moved past the now-vacated parking spot, slowed into position, glided back into the space, and powered down.

A moment later, the man pushed the button again, and the Leaf fetched itself, reversing its previous steps, and returned to the man’s side.

This isn't science fiction. I watched this all myself, dumbfounded, just a little over a week ago.

Was this self-parking demonstration a bit of razzle-dazzle that will never make it into the vehicles in dealer lots? Maybe not.

To witness this scene, I drove 45 miles in a 2014 Infiniti Q50 sedan from LAX to the decommissioned El Toro Marine Corps Air Station. (That's where Nissan held its month-long Nissan 360 technology showcase.) The Q50 was equipped with the luxury car’s $3,200 tech package , which pushes the nicely appointed vehicle’s price over $50,000.

The relevant features of the teched-up Q50 are Intelligent Cruise Control and Active Lane Control. The technology allowed me to travel at highway speeds along short, straight stretches of the 405 and the 5, with my foot off the pedals and my hands at my side.

Take that, Google! The search engine is investing an unknown amount in self-driving cars, and those prototypes have driven millions of miles. Google promises to offer the technology to consumers by 2018, but the Q50 is on sale today.

Proto-Automation

The Q50’s camera located in front of the rearview mirror, along with its image-processing system, can read lines and dashes on the roadway.  When the vehicle gets close to the white paint separating lanes, the car gently nudges the steering wheel in the direction of safety.  But here’s a problem that I experienced: When the car approached the white line to the left, it overcorrected, sending me across the lane to the right-side boundary, where the camera and computer nudged me back again across the lane to the left line.  With my hands off the steering wheel, the Q50 became a careening, 3,500-pound ping-pong ball. 

In fairness, the visual guidance technology in the Q50 is not meant to fully automate driving.  It’s intended to play an assist role, which according to Infiniti—Nissan’s upscale division—reduces driver fatigue and otherwise enhances the vehicle’s luxury feel. It worked as intended.

Similarly, the Q50’s Forward Assist technology was effective.  Set the cruise control to, say, 65 miles per hour, and lift your foot off the accelerator.  That’s plain ol’ cruise control, right?  But thanks to a radar system behind the front bumper, the car can detect the speed of cars ahead in the same lane, and automatically slow down the Q50 to match their pace—all the way down to a complete stop, only to resume acceleration when the car ahead gets going. This is an increasingly common automotive feature, usually called adaptive cruise control.  A related safety feature rapidly and automatically applies brakes when the vehicle in front comes to a screeching halt.

Driving Back to the Future

These early manifestations of autonomous driving technologies already seem unremarkable.  But what’s surprising is that the fully automated Leaf on display in Irvine uses the same exact camera, image-processing technology, and radar found in the Q50.

“To find objects that are approaching from far away very fast, radar is the best technology,” explained Tetsuya Iijima, general manager of intelligent transportation systems engineering at Nissan. “But unlike the driver-assisting features on the Q50, fully automated technology can’t make any excuses to the customer.”
So Iijima and his team of engineers employ more serious automagical mojo: six laser scanners that surround the car.  And not just the fixed broad-beam or one-dimensional lasers already used in auto-safety systems from Continental and other suppliers. These are three-dimensional ones that scan left, right, up, and down, to make a full spatial rendering of all road objects on the fly.  Three radars are still used, one in front and two in back, as well as five cameras that can read speed-limit signs (to modulate speed according to the highway rules) and the color of traffic signals (to know when to stop and go at an intersection). 

Add 12 sonars, and you now have a Leaf electric car that can travel autonomously and safely on highways—and do that cool robotic-parking trick as well.  Iijima demonstrated those two feats in two separate vehicles—each equipped with precisely the same hardware, but programmed for either highway travel or automated parking.  Nissan executives said that these automated features will go on sale in 2020—and will become available a few years later in a wide range of models.

The Secret Sauce: Fricking Laser Scanners

Several carmakers already offer features similar to the ones available in the Infiniti Q50, and are making claims about fully automated driving coming in the not-too-distant future—although most do not give timetables.

The reason Nissan thinks it can set a date is that it has committed to laser technology.
“We believe that we are leading this technology," said Iijima. "Other companies still have not decided to use a laser scanner. We have come to the conclusion that laser scanners are required. The image is a regular three-dimensional picture. Each point has depth information.”

The Google car uses a relatively large roof-mounted LIDAR system, using 64 lasers in a spinning 360-degree turret to create a high-resolution map accurate to about 11 centimeters, according to Popular Science.   The autonomous Leaf embeds six fixed laser scanners—around the car in corner body panels and into rear-passenger doors—each one providing resolution to 1 centimeter, according to Nissan.

Iijima declined to identify the companies that Nissan is considering to supply the three-dimensional laser hardware or what it might cost. Nissan is developing its own software that filters all the various inputs, and integrates the data into steering-wheel position, acceleration levels, and braking. It’s Big Data on wheels. The intricate integration of hardware and software will take an alliance of companies, according to Iijima.

But Nissan has ruled out one type of technology, at least for the next few years—intelligent GPS-based geographical mapping, in the vein of Google Maps or Nokia’s Here. The info gathered from those mapping services is not detailed enough, according to Iijima. Also forget vehicle-to-vehicle or vehicle-to-infrastructure communications that will take decades to penetrate across enough cars and roadways to become useful.

The cool self-parking car, unlike similar systems unveiled from Audi and Volvo, does not require GPS or any sensors or transmitters applied to the pavement.  Instead, as Iijima believes, vehicle automation should work with on-board sensors.  (Nonetheless, Nissan is working on a parallel development using precise maps that will enable cars to run autonomously in more challenging city environments.)  For now, Nissan is only talking about tackling the simpler challenge of highway driving and automated parking.

The Beginning Of The End Of Driving

Iijima outlined some limitations to the system: a max speed of 80 miles per hour and difficulty in extreme weather conditions, like a snowstorm.  He said that his work now focused on increasing processing power, reducing cost, and shrinking the size of the hardware that currently occupies the entire hatch space—down to about the size of a shoebox that could fit into the engine compartment.

The software, which Nissan developed in-house with unnamed partners, is not unusual.

“It’s C++,” Iijima said with a chuckle.  And ironically, the most important required infrastructure is … white paint.  “The white line defines the road,” he said.  “It’s minimal infrastructure.”

What’s at stake with this program?  Big stuff. The promise of zero fatalities.  The ability for elderly and disabled people to gain mobility.  More efficient use of fuel and roadways.  And nothing less than a complete transformation of the relationship between car and driver.

“When the driver is no longer necessary, there is no need for cars to be owned by individuals,” he said. He envisions a world of shared autonomous mobility robots roaming global roadways by 2030.  Yet, there’s no single finish line set to be crossed in the distant future, but rather a slow and steady supplanting of human drivers by onboard computers, cameras, radar, sonar and lasers.