Skip to main content

SenseTime and Honda partner to accelerate R&D of smart AI Cars

Chinese artificial intelligence (AI) company SenseTime (ST) has signed a long-term agreement that will combine its AI algorithms with Honda’s vehicle control system to build autonomous smart AI cars. The partnership is expected to accelerate the research and development of these vehicles. The autonomous driving solution is said to provide advantages to a variety of passenger vehicle scenarios and lower transducer manufacturing costs. In addition, ST has also developed chips and embedded systems for the car
December 7, 2017 Read time: 2 mins

Chinese artificial intelligence (AI) company SenseTime (ST) has signed a long-term agreement that will combine its AI algorithms with Honda’s vehicle control system to build autonomous smart AI cars. The partnership is expected to accelerate the research and development of these vehicles.

The autonomous driving solution is said to provide advantages to a variety of passenger vehicle scenarios and lower transducer manufacturing costs. In addition, ST has also developed chips and embedded systems for the cars with a set of core technologies and patents for autonomous driving.

Lao Shihong, chief executive officer of ST, said: “Safety is the utmost priority when it comes to driving, and it also constitutes the core of our autonomous driving solution. By combining SenseTime's strengths in computer vision technologies with Honda's superior vehicle control technologies, we will together enable a safe and pleasant autonomous driving experience. Moreover, the fact that SenseTime provides core technology to a global enterprise like Honda marks a milestone."

Related Content

  • August 29, 2019
    Cohda trial proves C-ITS can work in tunnels
    Connected cars require uninterrupted signals to ensure driving safety. Going underground creates problems – but a trial in Norway suggests that there might be light at the end of the tunnel… As connectivity becomes increasingly important for transportation – in particular for connected and autonomous vehicles (C/AVs) - the problem of ‘blackspots’ and dead zones where signals fail or drop out is a pressing one. But developments early this year suggest that advances in technology might be on the brink of d
  • August 29, 2013
    Honda experiments with pedestrian and motorcycle safety
    Honda has demonstrated its experimental vehicle-to-pedestrian (V2P) and vehicle-to-motorcycle (V2M) technologies, aimed at reducing the potential for collisions between automobiles and pedestrians and between automobiles and motorcycles. The vehicle-to-pedestrian (V2P) technology uses a car equipped with dedicated short range communications (DSRC) technology to detect a pedestrian with a DSRC-enabled Smartphone and provides auditory and visual warnings to both the pedestrian and drivers. According to Ho
  • November 23, 2018
    Cubic: predictive analytics is putting fortune tellers out of business
    The rise of machine learning and artificial intelligence means that fortune tellers will soon be out of business. Ed Chavis takes a behind the scenes look at the world of predictive analytics ver since organisations started taking advantage of insights derived from Big Data, data scientists concentrated their efforts on the ability to make correct assumptions about the future. A few years later, with the help of automation, developments in machine learning (ML) and advancements in the application of a
  • June 11, 2015
    Machine vision’s image of road management’s future
    Q-Free’s Marco Sinnema looks at how the commoditisation of high-quality vision-based solutions is widening their application. Machine vision technology’s entry into the ITS/traffic management sector has followed a classic top-down path. This is unsurprising given the extremely demanding performance criteria which are the standard in its market of origin, manufacturing processing. Very high image qualities combined with frame rates often in the hundreds per second range resulted in vision systems with capabi