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What Are The Challenges To AI Adoption In Transportation? 9 Experts Share Their Insights

  • 29 September 2019
  • Sam Mire

Can you imagine a world radically different from the one you live now, with respect to transportation? If you drive your own car to work, imagine commuting in a bullet train or even on a bike, or simply carpooling. As shifting attitudes and regulations push us closer to this potential reality, we've seen an upward trend in the adoption of the latest technologies to lower emissions, ultimately changing the way we collectively travel.

But this transformation will take time, money, and lots of effort. There are serious challenges to fundamentally altering the means of transportation, and these industry experts weighed in on the greatest of those challenges. Here's what they said:

1. Matt Hill, Chief Science Officer at Rekor Systems

“The #1 challenge to AI adoption in transportation is budgeting for this new technology. Many municipalities find themselves tied down to inferior technology via historical commitments. These commitments typically involved significant startup funds to get off the ground. An example is cities that attempt to adequately enforce congestion management via vehicle weight with expensive proprietary sensors installed within roadways. Another example is toll roads that use costly OCR and RFID infrastructure to collect and enforce tolls. After these commitments re fulfilled, there are limited funds left to explore AI technologies.”


2. Tina Quigley, CEO of the Regional Transportation Commission of Southern Nevada (RTC)

“The #1 challenge is people's willingness to trust AI – especially when considering Autonomous Vehicles. A 2019 AAA survey found 71% of drivers would be too afraid in a fully self-driving vehicle. This is virtually unchanged from last year and up 8 percentage points from 2017. The private and public sectors must come together to help people see the opportunities and experience the technology. First-hand experience and proven results can garner trust. The technology could have amazing benefits, but without social acceptance and trust, it will go nowhere.”


3. Brendan P. Keegan, CEO of Merchants Fleet

“The biggest challenge is the lack of clarity around regulations. Standards around data collection and laws governing how new methods of intelligent transportation, like autonomous vehicles, should act in practice still need to be developed. As more artificial intelligence is incorporated, the questions of driver liability in the case of accidents will also enter a legal grey area. While states are starting to act at the individual level and the Department of Transportation has developed best practices, we lack a national framework to handle these issues.”

 


4. Reid Blackman, CEO at Virtue Consultants

“The most obvious issue with AI in transportation is safety. Slightly less obvious is the need to transparently communicate to consumers why they can trust AI at the wheel. That’s because optimizing for the right safety metrics isn’t enough: consumers don’t know what the engineers do. The issue is aggravated by the proliferation of articles on the famous “trolley problem”: if a car must swerve left or right to avoid hitting three people, and there’s an elderly person to the left and a young child to the right, what should it do? And similarly, “will my car sacrifice my life in an accident to save others?” Companies bringing AI to transportation will need to take the ethics of AI in transportation seriously if they’re going to win the consumer trust they need to drive their bottom line.”


5. Joseph Notaro, Vice President, WW Automotive Strategy & Business Development, ON Semiconductor

AI is bringing enhanced functionalities to transportation. We already have the ability to implement several sensing modalities. Companies like ON Semiconductor (the leading Image Sensor and Ultrasonic semiconductor supplier) are delivering very sophisticated and high performing Image Sensor, Radar, Lidar and Ultrasonic solutions.

AI is needed to make sense of this data and take decisions based on this data. There will be varying grades of AI implementation: Edge AI to optimize local sensor data extraction and reduce latency, Central AI where the main decisions are made and Cloud-based AI to leverage higher computing power and additional data (data from other vehicles, enhanced diagnostics, etc.). All three approaches need to coexist to provide the most efficient (energy, memory), fault-tolerant (redundancy) and performing system.”


6. Alex Shartsis, founder and CEO of Perfect Price

“Like the internet in 2000, AI adoption is in its infancy and it’s all too easy to think that adoption of AI will be slow or not have a big impact – especially with setbacks and recent bad press. This risk is highest for the largest and most complex transport companies who have long been able to get by with large teams of people armed with legacy software.”


7. Hongmo Je, CTO of StradVision

We believe that once public policies are matured enough for AI-driven Autonomous Vehicle technologies to be deployed, public trust will follow suit. But, at the end of the day, this is about changing an entire posture of a nation-wide infrastructure, from cities to inter-state highways. Even if policies are fast to adjust, complete physical infrastructure overhaul, which is crucial for the complete implementation of AI mobility networks, will also take decades or more so the market ought to find ways to identify niche opportunities created in between gradual policy and market overhaul.

Also, although it is proven that deep learning-based algorithms are much more robust when it comes to edge cases and overall reliability, like our brains, the fundamental logics are unknown. Despite that, we are faced with the challenge of delivering very close to 100% accuracy and safety in a real-world environment.”


8. Bryce Johnstone, Automotive Segment Director at Imagination Technologies

It’s hard to say what the main benefit of AI is to transportation because it has such potential to evolve the industry. Personally, I’d say there are two main benefits currently: the reduction of accidents and fatalities, and environmental benefits. “Human error is the leading cause of accidents and fatalities on our road – according to some research, over 90% of car accidents.

A smarter infrastructure will play a critical role in helping increase road safety. Smart roads with sensors will be able to communicate road conditions and even contact the emergency services in the event of an accident. While AI-powered vehicles will be monitor drivers for signs of fatigue and distraction. “The transportation sector is one of the biggest contributors of greenhouse gas emissions. Autonomous and connect electric vehicles will help users transition to ‘on-demand’ vehicle use in the coming years and decades, reducing congestion and unnecessary usage, and encouraging ridesharing.”


9. John Barrus, Director of Business Development at Groq

Increased safety is likely the #1 benefit that AI brings to transportation. AI systems pay attention 100% of the time and run unimpaired. The system doesn’t get distracted or drowsy and performs in a predictable way.”

 

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About Sam Mire

Sam is a Market Research Analyst at Disruptor Daily. He's a trained journalist with experience in the field of disruptive technology. He’s versed in the impact that blockchain technology is having on industries of today, from healthcare to cannabis. He’s written extensively on the individuals and companies shaping the future of tech, working directly with many of them to advance their vision. Sam is known for writing work that brings value to industry professionals and the generally curious – as well as an occasional smile to the face.

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