French Startups Pitching Autonomous Tech to Detroit, Silicon Valley

France's UbiMobility selects companies offering tech related to ADAS, facial and vocal recognition, driver behavior and interaction, vehicle connectivity and software validation.

May 9, 2017

4 Min Read
Thanks to UbiMobility electric autonomous shuttle Navya was selected to be part of Mcity program
Thanks to UbiMobility, electric autonomous shuttle Navya was selected to be part of Mcity program.

The race to develop self-driving and mobility technologies is heating up and two of the hottest spots are San Francisco’s Silicon Valley and Detroit.

Countless hopeful tech startups are converging on these cities from around the world to pitch their ideas. So much so, it is becoming difficult for automakers and Tier 1 suppliers to separate the wheat from the chaff.

In an effort to help France’s best and brightest get their shot, two French economic development organizations, Business France and Bpifrance, have developed UbiMobility, a10-month development program combined with a 2-week immersion into the automotive ecosystems of Detroit and San Francisco.

Business France is a government agency supporting the international development of the French economy and Bpifrance is a public investment bank that helps finance entrepreneurs.

Now in its third year, UbiMobility selects 20 top French startups that offer advanced technologies in areas related to connected and autonomous vehicles, including advanced driving and safety, facial and vocal recognition, driver behavior and interaction, vehicle connectivity and software validation.

A jury composed of industry executives and a WardsAuto editor selected eight companies from the group that they believe have the most compelling business cases.

Beginning June 3, the eight French companies will visit the Detroit/Ann Arbor area and Silicon Valley as part of the 2-week immersion program, present their technologies and try to develop partnerships with major U.S. players.

The UbiMobility delegation also will meet with the jury members and their autonomous- and connected-vehicle teams, including Ford Silicon Valley, Delphi, FCA, Valeo North America, Magna International, The University of California – Berkeley, the Boston Consulting Group and The University of Michigan.

U of M has developed Mcity, a special test facility in Ann Arbor for testing autonomous vehicles in real-life conditions. Thanks to UbiMobility, the Navya electric autonomous shuttle was selected to be a part of the Mcity program. 

Meetings in previous years have included companies such as Uber, Tesla, Faraday Future, Google and NVIDIA.

The eight startups selected for UbiMobility 2017 are:

Acapela Transport

Acapela invents speech solutions to vocalize contents with authentic and “ultra-natural” voices in the transportation market. Over 100 synthetic voices in 34 languages are ready to give a voice to any content, the company says. By mixing two technologies (unit selections and concept-to-speech) the company says it now can generate voices close to a human being in cars but also in other parts of multimodal transport. And the voices are available on all main platforms (Cloud, Windows Server, Windows Desktop and mobile, Linux servers and embedded, OSX and iOS, Android and others.


This company is a Paris-based developer of biologically-inspired computer vision sensors and systems for autonomous navigation and IoT applications. The company says its technology introduces a new computer vision paradigm based on how the human eye and brain work, and significantly improves the performance and power efficiency of how computer vision can be implemented in a wide range of products and applications.

CS Communications & Systèmes 

CS has developed a technology that improves the efficiency of the verification and validation process for complex critical systems such as advanced automotive systems.  Its solution permits the generation of scripts for tests of hundreds of lines of code in several seconds, significantly reducing costs.

LiDAR sensors allow self-driving vehicles to have a precise 3-D perception of their surroundings. However, they are too expensive for mass-market adoption and are not giving keen resolution and detailed data compared with cameras. Dibotics real-time software permits the vehicle to know its precise location and to know its environment (obstacles, route, road markings).


This company offers high-quality facial-analysis middleware which can be applied to a wide range of domains including the automotive industry. The company showcased a car at CES 2017 in partnership with Visteon that has the abilities to authenticate the driver, track his gaze and do simple expression analysis. This kind of technology is key to the development of advanced driver-assist systems.

Neavia Technologies

Neavia Technologies has more than 10 years’ experience in devices for Intelligent Transport Systems: smart cameras, wireless detection of transportation duration and communication vehicle to infrastructure (V2I). All these products for road infrastructure are contributing to better road management, more efficient traffic and to saving more lives.

Pertech Solutions

This company designs solutions for eye tracking, which include measuring the gaze direction of a subject in order to understand the interaction between the subject and his environment. The innovation is centered on the development of high-performance algorithms and software. It is based solely on image-processing techniques, without corneal reflection. This enables accurate, robust, fast pupillary tracking which is non-intrusive, simple to implement, and not influenced by conditions of brightness and without any constraint related to the acquisition equipment (camera).

Smart Me Up

Smart Me Up says, “We bring vision intelligence into cars to create the autonomous car of tomorrow.” Computer vision deals with how computers can gain high-level understanding from digital images or videos. It can detect and identify any object in a scene. Vision intelligence goes beyond that definition by understanding the context of the scene and reporting the information (drowsiness detection, car-accident detection, pedestrians crossing the road). The company says it has a light and affordable solution that can be embedded in any type of camera or OS.

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