Previous Blogs

October 23, 2018
Oracle Makes Case as Cloud Computing Provider

October 16, 2018
Arm and Intel Partner to Ease IoT Challenges

October 9, 2018
Top Goals and Challenges for AI in Business

October 2, 2018
Are Leather and LTE the Future of PCs?

September 25, 2018
Microsoft and Partners Evolve the Modern Enterprise Desktop

September 18, 2018
AI Application Usage Evolving Rapidly

September 11, 2018
The Many Paths and Parts to 5G

September 4, 2018
Tech Content Needs Regulation

August 28, 2018
Survey: Real World AI Deployments Still Limited

August 21, 2018
Nvidia RTX Announcement Highlights AI Influence on Computer Graphics

August 14, 2018
The Shifting Nature of Technology at Work

August 7, 2018
The Beauty of 4K

July 31, 2018
The Future of End User Computing

July 24, 2018
5G Complexity to Test Standards

July 17, 2018
California Data Privacy Law Highlights Growing Frustration with Tech Industry

July 10, 2018
Dual Geographic Paths to the Tech Future

July 3, 2018
The Changing Relationship Between People and Technology

June 12, 2018
The Business of Business Software

June 5, 2018
Siri Shortcuts Highlights Evolution of Voice-Based Interfaces

May 29, 2018
Virtual Travel and Exploration Apps Are Key to Mainstream VR Adoption

May 22, 2018
The World of AI Is Still Taking Baby Steps

May 15, 2018
Device Independence Becoming Real

May 8, 2018
Bringing Vision to the Edge

May 1, 2018
The Shifting Enterprise Computing Landscape

April 24, 2018
The "Not So" Late, "And Still" Great Desktop PC

April 17, 2018
The Unseen Opportunities of AR and VR

April 10, 2018
The New Security Reality

April 3, 2018
Making AI Real

March 27, 2018
Will IBM Apple Deal Let Watson Replace Siri For Business Apps?

March 20, 2018
Edge Servers Will Redefine the Cloud

March 13, 2018
Is it Too Late for Data Privacy?

March 6, 2018
The Hidden Technology Behind Modern Smartphones

February 27, 2018
The Surprising Highlight of MWC: Audio

February 20, 2018
The Blurring Lines for 5G

February 13, 2018
The Modern State of WiFi

February 6, 2018
Wearables to Benefit from Simplicity

January 30, 2018
Smartphone Market Challenges Raise Major Questions

January 23, 2018
Hardware-Based AI

January 16, 2018
The Tech Industry Needs Functional Safety

January 9, 2018
Will AI Power Too Many Smart Home Devices?

January 2, 2018
Top Tech Predictions for 2018

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TECHnalysis Research Blog

November 6, 2018
Automotive Tech Now Focused on Safety

By Bob O'Donnell

After years of hype and inflated expectations, it’s clear that the mania around fully autonomous cars has cooled. In a refreshing, and much needed change, we’re starting to see companies like Nvidia, Intel/Mobileye, and Arm now talk much more about the opportunities to enable enhanced safety for occupants in cars supporting advanced technologies.

It’s not that the tech industry is giving up on autonomy—as recent announcements about new rounds of trials from Lyft, Uber, and others, as well as advanced new chip designs clearly illustrate—but the timeframes for commercial availability of these advancements are starting to get pushed out to more realistic mid-2020 or so dates. Even more importantly, the messaging coming from critical component players is shifting away from roads packed with Level 5 fully autonomous cars within a few years, to ways that consumers can feel more comfortable with and safer in semi-autonomous cars.

Over the last few weeks, Nvidia, Intel, and Arm have all discussed research reports and technology advancements in the automotive market that are focused primarily on security, with the technology providing a supporting role. Nvidia, for example, released a comprehensive study called “The Self-Driving Safety Report” that provides a view into how the company incorporates safety-related technology and thinking into all aspects of its automotive product developments. The report covers everything from AI-based design, to data collection and analysis, to simulation and testing tools, all within a context of safety-focused concerns.

Intel, for their part, released a comprehensive study on what they termed the Passenger Economy this past summer, but recently touted some findings from the report that focus on the relatively slow consumer acceptance for self-driving cars due to concerns around safety. Essentially, while 21% of US consumers say they’re ready for an autonomous car now, it’s going to be 50 years before 63% consumers believe they become the norm. To address some of these concerns, Intel is touting its Responsibility-Sensitive Safety (RSS) model, which it describes as a mathematical model for autonomous vehicle safety. The idea for RSS is to develop a set of industry standards for safety that can then be used to reassure consumers in a transparent way about how autonomous cars will function. Recently, Intel announced that Baidu had chosen to adopt the RSS model for its autonomous driving efforts in China.

Back in late September, Arm announced a new program called Safety Ready that ties together a number of the company’s security and safety technologies into a unified structure that, while not limited to the automotive market, is very well-suited for it. Safety Ready incorporates both chip IP designs and software that are focused on applications where functional safety is critical and allows the company to meet the key automotive-related functional safety certifications, including ISO 26262 and ASIL-D. At the same time, the company also introduced a new automotive-specific chip design called the Cortex-A76AE that integrates a capability called Split-Lock that allows a dual-core CPU to either function as two individual components doing separate tasks or two single components running in lockstep, where one can take over immediately if the other fails. As in many automotive applications, redundancy of functions is key for safety concerns and the Split-Lock capability of this new design brings it to digital components as well.

While it may seem that all these announcements are a somewhat dramatic shift from how the tech industry had been talking about autonomous cars, in reality they are simply part of a maturing perspective on how this market will develop. In addition, they’re based on some practical realities that many in the autonomous automotive industry have started to recognize. First, as research has continued to show, most consumers are still very leery of autonomous car features and aren’t ready to trust cars that take over too much control.

Second, the level of difficulty and technical challenge in getting even basic autonomy features to work in a completely safe, reliable way is now recognized as being even harder than it was first believed. Even semi-autonomous cars integrate an extraordinarily complex combination of advanced technologies that includes AI and machine learning, advanced sensors and fusing of sensor data, and intelligent mapping, all of which have to work together seamlessly to ensure a safe, high-quality driving experience. There’s no doubt that we will start to get there, but for now, it’s reassuring to see companies focus on the critical safety enhancements that assisted driving features can bring, as we look further out to the world of full autonomy.

Here's a link to the column:

Bob O’Donnell is the president and chief analyst of TECHnalysis Research, LLC a market research firm that provides strategic consulting and market research services to the technology industry and professional financial community. You can follow him on Twitter @bobodtech.

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