Skip to main content

Intel outlines AV limits of perception

CES 2021: Intel boss Amnon Shashua suggests radar and Lidar as redundant add-ons
By Ben Spencer January 12, 2021 Read time: 2 mins
Shashua: 'You have to be 1,000 times better than these statistics'

What is an acceptable failure rate of a vehicle's perception system?

And how does this influence the development and regulation of autonomous vehicles (AVs)?

These were among the key areas covered by Professor Amnon Shashua, senior vice president of Intel and chief executive officer of Mobileye at this week's CES 2021 event.

In an online session, Shashua revealed the company measures failure rate in terms of hours of driving. 

“If we google, we will find out that about 3.2 trillion miles a year in the US are being travelled by cars and there are about six million crashes a year,” he said.

“So divide one by another, you get: every 500,000 miles on average there is a crash.”

“Let's assume that 50% it's your fault in a crash, so let's make this one million and let's divide this by 20 miles per hour on average, so we get about once every 50,000 hours of driving we'll have a crash,” he added. 

Shashua then applied this level of performance to a scenario involving a robotic machine and the deployment of 50,000 cars. 

“It would mean that every hour on average, will have an accident that is our fault because it’s a failure of the perception system,” he continued.

“From a business perspective this not sustainable, and from a society perspective, I don't see regulators approving something like this so you have to be 1,000 times better than these statistics.”

Mobileye is acutely aware of this, having just announced it will be testing AVs in new cities this year: Detroit, Tokyo, Shanghai, Paris and (pending regulation) New York City.

From a technological point of view, Shashua insisted it is “so crucial to do the hard work” and not combine all the sensors at the beginning and carry out a “low-level fusion – which is easy to do”.

“Forget about the radars and Lidars, solve the difficult problem of doing an end-to-end, standalone, self-contained camera-only system and then add the radars and Lidars as a redundant add-on,” he concluded. 

For more information on companies in this article

Related Content

  • C-ITS in the EU: ‘It has got a little tribal recently’
    April 16, 2019
    As the C-ITS Delegated Act begins its journey through the European policy maze, Adam Hill looks at who is expecting what from this proposed framework for connected vehicles – and why some people are insisting that the lawmakers are already getting things wrong
  • Knowing when to slow down
    August 8, 2018
    Level 2 driver assistance vehicles have little problem reading fixed metal signs at the roadside - but it’s a different story with VMS in tunnels, finds Alan Dron. Following a series of hands-free driving tests in tunnels, an Australian road authority believes that car manufacturers have to up their game before vehicles have the required levels of competence to consistently perform ‘assisted driving’ tasks. The trials, in the state of Victoria late last year, tested the ability of several vehicles to stay
  • Zuora: MaaS comes to the masses
    April 28, 2020
    The shift from ownership to usership in the subscription economy provides opportunities for the whole of the mobility sector for the next decade and beyond, says John Phillips of Zuora
  • Waymo opens AV dataset to researchers
    September 3, 2019
    Waymo is making its Waymo Open Dataset for autonomous vehicles (AVs) available to the research community for free. Waymo is hoping the data will help researchers make advances in 2D and 3D perception and progress in areas such as domain adaptation and behaviour prediction. The company says each segment of driving data captures 20 seconds of continuous driving, allowing researchers to develop models to track and predict the behaviour of other road users. This dataset covers dense and suburban environmen