Stories
Slash Boxes
Comments

SoylentNews is people

Uber Pulls Self-Driving Cars After First Fatal Crash of Autonomous Vehicle

posted by Fnord666 on Monday March 19 2018, @10:31PM   Printer-friendly
from the bound-to-happen dept.

vux984 writes:

A self-driving Uber SUV struck and killed a pedestrian in Tempe, Arizona. It was in autonomous mode at the time of the collision, with a vehicle operator behind the wheel. Uber has suspended testing of its self-driving cars.

http://money.cnn.com/2018/03/19/technology/uber-autonomous-car-fatal-crash/index.html
https://www.nytimes.com/2018/03/19/technology/uber-driverless-fatality.html
https://finance.yahoo.com/news/self-driving-uber-kills-arizona-171055918.html
https://www.npr.org/sections/thetwo-way/2018/03/19/594950197/uber-suspends-self-driving-tests-after-pedestrian-is-killed-in-arizona
https://www.wsj.com/articles/uber-suspends-driverless-car-program-after-pedestrian-is-struck-and-killed-1521480386
https://www.theverge.com/2018/3/19/17139518/uber-self-driving-car-fatal-crash-tempe-arizona
https://techcrunch.com/2018/03/19/uber-self-driving-test-car-involved-in-accident-resulting-in-pedestrian-death/

I couldn't find any good analysis of the liability situation here.

Original Submission

 
This discussion has been archived. No new comments can be posted.
Uber Pulls Self-Driving Cars After First Fatal Crash of Autonomous Vehicle | Log In/Create an Account | Top | 84 comments | Search Discussion
Display Options Threshold/Breakthrough Mark All as Read Mark All as Unread
The Fine Print: The following comments are owned by whoever posted them. We are not responsible for them in any way.

  • (Score: 3, Informative) by takyon on Tuesday March 20 2018, @03:43AM

    by takyon (881) <takyonNO@SPAMsoylentnews.org> on Tuesday March 20 2018, @03:43AM (#655261) Journal

    Stanford Researchers Develop Non-Line-of-Sight LIDAR Imaging Procedure [soylentnews.org]

    NLOS [(Non Line Of Sight)] imaging reconstructs the shape and albedo of hidden objects from multiply scattered light. Despite recent advances, NLOS imaging has remained impractical owing to the prohibitive memory and processing requirements of existing reconstruction algorithms, and the extremely weak signal of multiply scattered light. Here we show that a confocal scanning procedure can address these challenges by facilitating the derivation of the light-cone transform to solve the NLOS reconstruction problem. This method requires much smaller computational and memory resources than previous reconstruction methods do and images hidden objects at unprecedented resolution. Confocal scanning also provides a sizeable increase in signal and range when imaging retroreflective objects.

    --
    [SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]
    Starting Score:    1  point
    Moderation   +1  
       Informative=1, Total=1
    Extra 'Informative' Modifier   0  
    Karma-Bonus Modifier   +1  
    Total Score:   3