Toyota, NTT to invest $3.3 bln on development of AI platform (updated)

NTT

31/10/2024 06:11

(Adds details from statement, background in paragraphs 3-9)
       TOKYO, Oct 31 (Reuters) - Toyota Motor  7203.T  and
Nippon Telegraph and Telephone (NTT)  9432.T  plan to invest a
total 500 billion yen ($3.27 billion) by 2030 into an
infrastructure and software platform using artificial
intelligence to reduce traffic accidents.
    The automaker and telecommunications firm said in a joint
statement on Thursday they want to develop a mobility AI
platform that uses large amounts of data to support driver
assist technology, aiming to have a system ready by 2028.
    The joint push comes at a time when Japanese automakers are
facing pressure to step up their efforts in the growing
autonomous driving market, which is increasingly dominated by
Tesla  TSLA.O  and Chinese firms.
        Toyota and NTT said they hope the platform will help
with things such as preventing accidents caused by poor
visibility in urban areas, supporting automated driving services
and making it easier to merge on expressways.
        Their goal is to make the system available not just for
themselves but for other industry players, the government and
academic partners who want to reduce traffic accidents to zero,
targeting widespread adoption from 2030 onwards.
    Toyota and NTT first partnered in 2017 to develop technology
for 5G-connected cars and formed a capital tie-up as part of a
smart city project in 2020.
    Last November, NTT said it planned to test driverless
vehicle technology with Toyota as early as 2025 and invest in a
U.S. startup developing self-driving systems.
    Toyota established an autonomous driving technology unit in
2021 to invest in and develop mobility with AI. 
    The unit, now known as Woven by Toyota, is also developing
an automotive software platform, Arene, and building a testing
site named Woven City for mobility-related systems and services
in Shizuoka prefecture, west of Tokyo.
($1 = 152.9400 yen)
    

 (Reporting by Daniel Leussink; Editing by Christian
Schmollinger and Sonali Paul)
 ((daniel.leussink@thomsonreuters.com; Twitter:
@danielleussink;))