MOTOR Magazine

A MOTOR Magazine Newsletter
January 23, 2017

Contributed by Bob Chabot
Five Tech Trends That Will Drive the Automotive Industry Forward in 2017

Like shops and technicians, OEMs are being firehosed by technology

New technology continues to pour into the automotive industry at an unprecedented rate. While some have developed and matured over many years before being adopted by the auto industry, others are more disruptive, emerging more suddenly and driven by fast-shifting demands and pressures. Regardless of origin, early adopters often serve as a crystal ball for which trends will take root in the industry. Here’s a glimpse at some trends expected to gain traction in 2017.

IBM demonstrates how blockchain technology can be used to track a vehicle and its information from manufacture to being leased to end-of-life. (Video — IBM)

OEMs Embrace Authentication and Cybersecurity
“Blockchain” technology first came to light as the secure asset-transferring process underpinning the Bitcoin protocol. It has since evolved to become one of the strongest forms of security the electronic world has to offer today. It has the attention of regulators, IT firms, financial institutions and even the automobile industry, which is often cautious in adopting breakthrough technologies.

“Security is the core of blockchain technology,” explained Haskell Garfinkel, a principal of PriceWaterhouseCoopers. “It leverages cryptography, digital transactions, databases and other elements to establish a system of checks and balances with cloud servers validating and recording everything. Automotive financial services is a prime application that blockchain could streamline while offering enhanced security and reduced administration costs. For example, Toyota Financial Services is already exploring the use of blockchain technology for its leasing and purchasing programs.”

“Blockchain architecture allows a distributed network of legitimate industry participants to simultaneously share records, reach consensus and validate transactions without the need for a central authority or middleman,” noted Mahbubul Alam, chief technology officer for the Movimento Group. “Just consider the supply chain community as an example. Counterfeit parts in conventional vehicles are already problematic; the advent of autonomous vehicles and intelligent transportation systems will create even more issues. The legitimate transfer of vehicle data, software and information between automakers and the aftermarket is another.”

“For example, OEMs must currently take a leap of faith and trust that parts from tier one suppliers, let alone the smaller manufacturers who supply the tier one firms, are what they say they are. But blockchain technology can create a trust protocol that really can be trusted by all parties. Every vehicle, every component and every part receives its own unique identity as part of the supply chain and distributed ledger system, from manufacture to scrapyard. Blockchain technology ensures that within the supply chain, everyone knows what parts were created, how many, who built them, what has happened to them and other key data. As OEMs and suppliers gain a better understanding of blockchain in 2017, look for the technology [to be] adopted for these and other applications.

The mass of Big Data continues to grow exponentially, as the types of data and number of data sources for each type increase. Competent analysis is essential to determining what data is really needed to make better decisions. (Image — Deloitte Touche Tohmatsu Limited)

Big Data and Predictive Analytics Will Spur Proactive Care
Expect the use of Big Data and predictive analytics tools to blossom in 2017. Predictive analytics — which uses many techniques from data mining, statistics, modeling, machine learning and artificial intelligence to analyze current data — make predictions about the future.

Mobile phones, other smart devices and telematics are now enabling data to be generated at an accelerating volume and velocity. Collecting vehicle information isn’t new, but harvesting connected data, analyzing it and applying that information to already accumulated knowledge about the operating surroundings of the vehicle at any given moment is innovative.

Being able to make decisions based on Big Data is critical in dealing with the realities of cost pressures, market shifts, consumer behavior, service repair and more. It allows OEMs to gain real-time insights about customer preferences and experiences to then adjust manufacturing processes, tweak marketing campaigns, minimize inventory, streamline supply chains and more.

For example, predictive analytics can benefit consumers and service repair professionals by enabling cheaper insurance for safe drivers, a reduction of “what if” inventories having to be kept close at hand, and fewer and less costly breakdowns. In the case of the latter, needed software updates will be proactive and often repair the car, or warn the driver that immediate service is needed, before something breaks down. In addition, with potential problems identified and fixed early, vehicles will last longer, which positively impacts vehicle owners, those who service older aged vehicles, as well as automakers trying to build brand loyalty.

Big data also provides car manufacturers with crucial insight into vehicle systems and new technologies, notably how they perform under certain conditions within the environment and certain driving patterns. This then helps car manufacturers to solve many of the problems that the driver may end up encountering. The end results facilitate an improved driving and service experiences.

For example, BMW has developed big data analytics platforms that combine data from prototypes that have been tested numerous times with vehicle data and reports from early buyers to identify weaknesses in new models so they can be corrected before more units are produced, and sooner than in the past. Data evaluation previously took months to finish, but big data analysis has helped BMW reduce error rates and warranty costs, as well as integrate the findings into other vehicle production processes.

Artificial intelligence and machine learning technology are helping automakers and tier one suppliers develop vehicles capable of learning the art of driving. For example, a number of OEMs are already using NVIDIA Corp.’s open AI platform in their self-driving vehicle programs. (Video — NVIDIA Corp.)

Artificial Intelligence Will Improve Security
Modern vehicle networks today use anti-virus and other common software security technologies to identify known threats and try to quarantine some of the unknown ones. However, these measures aren’t ideal in a dynamic area where new threats continually pop up. This cat-and-mouse approach needs an overhaul; artificial intelligence (AI) and machine learning technologies are just the thing to deliver it.

AI is concerned with the development of computers and software that are capable of intelligent behavior equal to or better than humans. Machine learning is a subset of AI, and its major concern is the construction of algorithms that can learn from both supervised and unsupervised data. Supervised learning is preferred when data is already identified, labeled and categorized. Unsupervised learning is used when just raw data is available and it is necessary to figure out patterns.

For instance, cybersecurity systems predicated on these technologies are self-adapting and self-defending. They enable computers to learn without being explicitly programmed, and become more adept upon being exposed to new data. They also create ways to guard against new threats without any humans needing to program the system to identify specific incoming threats.

“We must also stop getting the user/owner to fix security,” stated cybersecurity expert Bruce Schneier. “Requiring the user or owner to update software, firmware or hardware is archaic. Usable security means creating security that works, despite what people do. Machine learning and artificial intelligence are enablers for this; they will facilitate security updates to be implemented automatically so users don't have to remember or do anything to their computers, vehicles or other devices.”

Look for OEMs and suppliers to begin using these technologies in 2017, particularly in regards to vehicle safety and communication networks. Case in point? “Machine learning and artificial intelligence give cars superhuman abilities to analyze and learn from hundreds of thousands, even millions, of driving situations to learn better than any human being can,” explained Peter Steiner, managing director of Audi Electronics Venture. “These systems learn from hundreds of thousands, even millions, of such situations that can be stored, analyzed and improved from, which will enable autonomous vehicles to learn even better than a human being can. In deploying sophisticated advanced driver assistance features increasingly based on these technologies, Audi has seen a strong uptake among its buyers.”

Expect DSRC and cellular 5G technologies to evolve into a new Cellular V2X standard for automobiles. (Video — Qualcomm.)

Advanced Communication Protocols Will Improve Safety
In early December 2016, the U.S. Department of Transportation issued a proposed rule that would advance deployment of vehicle-to-vehicle (V2V) technologies and make it the first country to make V2V communication on all new light-duty vehicles mandatory. According to the DoT, the process from publication of the proposed rule to a Federal Motor Vehicle Safety Standard (FMVSS) usually takes about one year. Two years after that the phase-in period begins: 50 percent of new vehicles in the first year (must be compliant, 75 percent in the second year and 100 percent from the third year on. In other words, if the proposed rule is adopted, expect implementation to begin in 2019.

The sudden push toward V2V communications is being powered by two technologies: (1) Dedicated Short Range Communications (DSRC), an older established technology; and (2) A new 5G automotive cellular standard. Industry experts expect the two technologies will likely be blended into a single system solution that will be introduced the next few years. Qualcomm’s new Cellular V2X system is one example.

In regards to security and privacy, DSRC-based V2V technology requires messages sent to and from vehicles to be encrypted and authenticated. In addition, these systems can be retrofitted to older model vehicles for between $100-$300, which will help facilitate a wider-ranging transition to safer connected vehicles.

But the latency of stand-alone DSRC and 4G or older cellular systems is a limiting concern. DSRC signal take 100-120 milliseconds to communicate, small but too slow for some new advanced accident prevention safety technologies. These require a much shorter latency period — 1-millisecond, which is essentially real time — to be effective in preventing or minimizing all accidents, another goal of federal regulators.

Fortunately, the hybrid DSRC/5G solutions being developed, such as Qualcomm’s Cellular V2X system, meet the 1-millisecond requirement. In addition, hybrid DSRC/5G solutions are more reliable: They operate over longer distances than DSRC alone, and are able to communicate by satellite should vehicles be too far from existing cell towers.

The availability of DSRC today allows automakers to prepare for and implement V2V in time to comply with a new FVMSS mandate. In fact, V2V capability will be implemented this year. Cadillac has announced its 2017 models will include Cohda Wireless’ DSRC-based V2V system at manufacture. (Note that Cohda hardware and software products are used in 65 per cent of all V2V and V2X field trials worldwide.) Look for other automakers to equip luxury models first, then other models. And as DSRC/5G technology is perfected and real time dependent safety systems are introduced, look for a transition to the more functional hybrid systems in the years ahead.

Ford spokesman Raj Nair comments on the automaker's plans to introduce autonomous vehicles for ride-sharing and production series customers. (All images — Ford Motor Co.)

Autonomous, Networked Vehicles Will Reshape Transportation
Just a few years ago, driverless cars were unheard of. Now, they’re on the road, albeit in small, but growing numbers. Expect 2017 to see a flurry of new AV functionality introduced.

Ford Motor Co., for example, has announced its plan to mass-produce ride-sharing autonomous vehicles by 2021, and production series autonomous vehicles shortly thereafter. General Motors has begun testing an autonomous version of its plug-in extended range Bolt. Michigan recently passed legislation allowing AVs — without a driver, steering wheel and brake/accelerator pedals — on public roads for testing purposes. In addition, the National Highway Transportation Safety Administration has introduced model legislation for governing AVs, in a bid to get 50 states on the same page.

Next generation AVs are already emerging. Ford introduced its next-gen Fusion Hybrid autonomous vehicle at the 2017 Consumer Electronics Show earlier this month. Raj Nair, Ford executive vice president for Product Development, shared, “The new Fusion AV uses the Ford’s current AV platform and virtual driver system but we’ve added new computer hardware, advanced electronic controls and upped the processing power. For example, the Fusion AV features new LiDAR sensors that have a sleeker design and more targeted field of vision. This enables the car to now use just two sensors rather than four, while still getting just as much data as before.”

“The connected AV is already a reality,” shared James F. Hines, research director for Gartner Inc. “By 2020, there will be a quarter billion connected vehicles on the road equipped with automated driving capabilities. But the proportion of new vehicles equipped with new autonomous functionality and advanced capabilities will increase dramatically. This will create opportunities for application processors, graphics accelerators, displays and human-machine interface technologies. It will change how vehicles are made, how they’re driven and how they are maintained.”

[Editor's note: Visit for the latest diagnostic and service insights.]

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