Eye-Net Mobile Successfully Completes Controlled-Environment Trial for the Connected Car Division of a Leading Global Vehicle Manufacturer

Foresight Autonomous Holdings Ltd. (NASDAQ and TASE: FRSX), an innovator in automotive vision, announced today that its wholly owned subsidiary, Eye-Net Mobile Ltd., successfully completed a controlled-environment trial of its Eye-Net cellular-based accident prevention solution for a leading vehicle manufacturer. The trial, conducted in a designated test track, was designed to demonstrate Eye-Net’s advanced capabilities of protecting vehicles and vulnerable road users from oncoming collisions, to test the system’s performance and robustness, and to discuss possible suitability of the Eye-Net solution for the connected car platforms of the leading vehicle manufacturer.

Eye-Net Mobile’s market penetration strategy is directed at potential partners, such as this leading vehicle manufacturer and location-based service providers. Integrating Eye-Net as a feature in the partners’ applications at a very early stage in order to optimize the solution to their needs will help facilitate Eye-Net’s rapid market penetration, thus reaching millions of users. A controlled trial demonstrating the system’s capabilities will help to engage potential partners and present the potential of the solution and its advantages in the commercialization phase. The Company believes that such cooperation will add substantial value to potential strategic partners by enhancing their users’ safety.

The controlled-environment trial took place at the conclusion of Eye-Net Mobile’s large-scale trial (as reported by the Company on August 12, 2019). Prior to the controlled trial, Eye-Net Mobile presented a detailed analysis of the large-scale trial’s results to the leading vehicle manufacturer.

Eye-Net Mobile tested several predefined extreme accident-simulated scenarios at various speeds up to 80 kilometers per hour. The scenarios included multiple participants—vehicles, pedestrians, and cyclists—that had no direct line of sight. In all cases, the participants in the trial used the Eye-Net application installed on their smartphones. The Eye-Net system was able to filter out non-critical events and send real-time alerts only to the participants who were in potentially unsafe situations, in order to prevent an oncoming collision. In all scenarios tested, Eye-Net met all predefined objectives of the controlled-environment trial.