In 2004, DARPA’s (www.darpa.mil) Grand Challenge offered $1Million to the team able to navigate 150 miles using “driverless” technology.  All teams failed.

In 2019, autonomous vehicle (AV) technologies now appear to be the next horseless carriage revolution. Headlines read….  

Automobile manufactures are offering connected and autonomous vehicles. “

“Autonomous ride sharing services are available in Singapore.”

“Autonomous vessels are navigating the fjords of Norway. “ 

“Expect 5G wireless networks and cloud infrastructures to facilitate higher speed network connections for AVs.”

The headlines are accurate to some extent. AVs in certain scenarios are capable of self-driving.  Depending upon AI, cameras, LiDAR (radar), Machine Leaning, 3D mapping, sensors and other technologies to function properly.  This reality is pressuring transportation organizations to find use cases. As these vehicles and vessels now rely more on hardware and software than engines.

Begin with these recommendations:

  1. Attend transportation specific conferences, such as, AV19 Conference (www.automotive-iq.com/)
  2. Focus on Levels 2-4 for Autonomous Technology and Advanced Driver Assist Systems.  
  3. Follow Enablers and Manufactures. Enablers, include, AutoX (www.autox.ai), Nvidia (www.nvidia.com)  TuSimple (www.tusimple.com) and Waymo (www.waymo.com) Manufactures include BMW (www.bmw.com) and Tesla (www.tesla.com).
  4. Follow Legislative Enactments. (www.ncsl.org) A State-by-State analysis suggests human supervision is required.
  5. Track Federal Safety Regulations. Preparing for the Future of Transportation: Automated Vehicles 3.0

Next, develop expertise for navigation, cyber security and privacy. Nothing is failsafe.

Any use case must integrate human supervision into navigation and reaction to objects. AV navigation relies upon (AI, geofencing and 3D maps). This geographically limits cargo, delivery or passenger routing for many use cases. Humans have no limitations.

Imagine the unexpected deer crossing the snow-covered highway. With only seconds to alter course. Humans may react faster in such scenarios.

Identify vulnerabilities. Treat AVs as a user interface. This means you will need to examine results for collision avoidance and cyber security testing and simulation on public roads.  

Privacy. Conform data management practices (collecting, managing and analyzing) data to the evolving Automotive Consumer Privacy Protection Principles. (see.www.autoalliance.org). This is a beginning baseline for data collection use and consent. For example, what, if any, privacy ramifications emerge for occupants using AV ride sharing services?

Then determine if AV use cases reduce costs or improve operations.

Hint: Pursue semi-autonomous vehicles/vessels able to operate within human-assisted guidelines. For example, cargo convoys, last mile delivery scenarios or geofenced carriers, taxis and vessels.

What Do You Think?

 Author Disclosure

I am the author of this article and it expresses my own opinions. I have no vested interest in any of the products, firms or institutions mentioned in this post. Nor does the Analyst Syndicate. This is not a sponsored post.

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