The top 7 trends in the auto industry for 2017

The top 7 trends in the auto industry for 2017

In an industry such as automotive where technology is pouring in at an unprecedented rate, incipient trends are multiplying like vehicles on the roadways at rush hour. Some trends for 2017 are
inevitable given developments in recent years while others are more disruptive, bleeding into multiple areas. Consider how Uber disrupted the taxi market and fundamentally changed the transportation sector.

Trends emerge first among early adopters so watching their behavior is a good crystal ball. The good news for automotive OEMs and the vast array of related companies involved in this business is that there will likely be more funding available next year to develop new technologies embraced by these early adopters and refine current ones due to political and financial forces. This should make 2017 an exciting year for the industry — and therefore, for consumers.

The most provocative trends are those on the disruptive side.  What will we see in that arena in 2017?

Auto suppliers discover sizzling blockchain

A super-hot technology now getting intense attention in the tech space is blockchain; the first auto suppliers will begin using it in 2017.

In the automotive business, where the supply chain — with all its potential for counterfeit parts and related issues — is so important, blockchain technology can create a trusted, accurate protocol for this supply chain.

This establishes a system of checks and balances for the whole supply chain community, with cloud servers validating and recording everything.

Augmented reality will assist driver safety and impact areas from designing to repair

While virtual reality creates a simulated world, augmented reality adds specific, created elements to the real world via technology. Perhaps the most prominent example of AR is the addictive Pokémon GO game for smartphones.

In the auto industry, some AR solutions should begin to appear in 2017, starting with smart head-up displays and infotainment displays followed by apps for repair shops.

Cars are complicated machines, so AR can help mechanics visualize what needs to be fixed before touching a wrench. Another area for AR is in designing or selecting a car where various vehicle elements — from the overall shape to the seats and interior features — can be pre-seen, thus saving extensive time and money. Certainly, prototyping isn’t anything new in the automotive sector, but AR takes it to a whole new level.

Saving money and increasing safety through 3D printing

Next year, 3D printing will begin to appear in other areas, such as basic car construction done by mainstream carmakers and new players like Local Motors, a low-volume manufacturer of open-source vehicles. After all, 3D printing makes it cost-effective to build things, challenging today’s fundamental approach to car design.



Currently, cars are designed to withstand three, four or five crashes and last perhaps seven and a half years. But 3D printing enables the industry to build a car on a solid chassis with an outer body designed for a single crash, then cost effectively replace that while leaving the basic vehicle skeleton/structure in place. It could disrupt our concept of accident repair.

We can build bodies that deliver amazing safety, but only for a single crash. After that, a new body is created. Imagine how the same car might be rebuilt and recycled over its lifetime to serve different lifestyles — rebuilding the convertible bought when you are young into the wagon needed later for a family lifestyle with kids, dogs and strollers.

Autonomous vehicles continue to drive the industry

2017 will see a flurry of new autonomous functionality appearing in almost every new car.

Autonomous capabilities like self-parking and adaptive cruise control will be available from virtually every auto OEM in new vehicles.

This movement is unstoppable and, while driverless cars themselves won’t populate the road in 2017, the direction seems clear. Don’t forget that Ford already announced its plan to mass-produce autonomous vehicles by 2021. Tesla and Google are also making inroads into producing road-legal driverless cars.

Just one example of a big step forward next year will be some high-profile trials of techniques like platooning, in which convoys of driverless vehicles follow each other to reduce congestion. Let’s hope that the Florida incident involving Tesla remains an outlier in the evolution toward a driverless future.

Machine learning-based vehicle cybersecurity

The cat-and-mouse game that defines existing vehicle security features could use an overhaul and the recent resurgence in artificial intelligence technologies is just the thing to deliver it.

Today, the networks on wheels that are modern cars use anti-virus and other common software security technologies that identify known threats and try to quarantine some of the unknown ones. But this isn’t ideal in a dynamic area where new threats continually pop up.

Machine learning in the AI space lets computers learn without being explicitly programmed, getting more adept when exposed to new data. These cybersecurity systems are self-adapting and self-defending, creating ways to guard against new threats without any humans needing to program the system to identify specific incoming trouble.

Among early adopters, these solutions should start appearing next year.

Collaborative monetization to see exponential growth

While it goes in a different direction than the auto industry’s traditional go-it-alone approach of vertical integration years ago, today’s world demands that auto companies collaborate in areas outside their space and seek ways to make new profits from disrupting trends.

Next year will see more of such activities, like using car- and ride- sharing as a means to create new residual value in their cars and engage with a new consumer demographic.

More auto OEMs will make moves like creating leasing organizations and dealer networks that are able to deal with partial ownership and vehicle servicing. And importantly, with the right offering, they can reach new drivers and create brand-specific loyalty.

Many of the car-sharing business models will act as a pay by the minute or mile, or a combination of the two, where OEMs will still own the physical asset. This will allow the OEM to amortize car cost across many transactions, not just a single sale — creating better profitability options.

Predictive analytics will help OEMs and consumers

The reliance on advanced software and big data to help transcend a volatile industry will pick up its pace next year, particularly in the area of predictive analytics, which uses many techniques from data mining, statistics, modeling, machine learning and artificial intelligence to analyze current data to make predictions about the future. Such intelligent technology will be critical in dealing with the realities of cost pressures, competition, globalization, market shifts and volatility.

From web browsing data on select auto sales sites to give OEMs real-time insights about customer preferences in order to adjust production schedules to tweaking marketing campaigns, minimizing inventory and streamlining supply chains, the use of predictive analytics tools will blossom in 2017.

But predictive analytics will also help consumers, from cheaper insurance for safe drivers to fewer breakdowns. In the case of the latter, needed updates will be proactive and repair the car before it breaks. In addition, with potential problems identified and fixed early, vehicles will last longer, which positively impacts car owners as well as people who rent cars or do ride sharing.

Source : TechCrunch.  Com