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Rail Vision’s Long-Term Pilot Program with Rio Tinto Completed and Extended to Evaluate Additional Use Cases

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Rail Vision Ltd. (Nasdaq: RVSN) announced the expansion of its pilot program with Rio Tinto for the AutoHaul® project, the world’s first fully automated heavy haul rail network. This initiative leverages Rail Vision’s AI-based Main Line System to enhance railway safety and operational efficiency. The project, which began in May 2022, has seen autonomous trains operate successfully over 4.5 million kilometers. The next phase aims to improve obstacle detection capabilities, furthering the goal of safer autonomous train operations.

Positive
  • Completion of a pilot program with Rio Tinto expands testing capabilities for AutoHaul®.
  • Demonstrated operational success with trains traveling over 4.5 million kilometers autonomously.
  • AI-based Main Line System enhances safety by detecting obstacles on tracks.
  • Potential for accelerated adoption of technology in the rail industry.
Negative
  • None.

Ra’anana, Israel, Sept. 14, 2022 (GLOBE NEWSWIRE) -- Rail Vision Ltd. (Nasdaq: RVSN) (“Rail Vision” or the “Company”), a development stage technology company seeking to revolutionize railway safety and the data-related market, today announced the completion of a pilot with Rio Tinto Iron Ore (“Rio Tinto”) for the AutoHaul® project, the world’s first automated, long distance, heavy haul rail network.  Rail Vision’s Main Line System test in Pilbara, Australia began in May 2022 as part of the Company’s contract with Hitachi Rails STS (“Hitachi”), the lead project technology partner and integrator.

“We are excited to expand our long-term pilot program with Rio Tinto and evaluate additional use cases for the AutoHaul® project, which is at the forefront of the future of autonomous train operations,” commented Shahar Hania, CEO and co-founder of Rail Vision. “Early successes with the initial long-term pilot program announced in May was a key factor in moving forward with additional testing programs through the now-expanded pilot program. We look forward to continuing operational testing with Rio Tinto.”

As part of the AutoHaul® project, 2.4-kilometer-long trains, monitored remotely from an operations center in Perth, Australia, travelled across a vast network of 1,700 kilometers of track, delivering iron ore from 16 mines to ports in Dampier and Cape Lambert. These trains have now safely travelled more than a collective 4.5 million kilometers autonomously since the trains were first deployed in 2018.

Under the AutoHaul® program, Rio Tinto is seeking to add a forward-looking capability to its autonomous trains to detect obstacles on and along the tracks. During the next testing phase of the Rail Vision Main Line System pilot program, Rio Tinto and Hitachi will test different types of obstacles the system can detect at various ranges.

The Rail Vision Main Line System is an artificial intelligence (AI)-based solution that enables railway operators to improve the safety of train operations, prevent collisions and reduce maintenance downtime. The system detects and classifies obstacles on or near the tracks within a predefined area of interest, and generates real-time visual and acoustic alerts for both the driver’s and the operator’s command-and-control center. Combining sensitive imaging sensors with AI and deep learning technologies, the tailormade system provides an extended visual range of up to two kilometers, under almost any weather and light conditions.

“Through advanced, long-range artificial intelligence detection systems, our technology provides unparalleled obstacle identification on and near tracks, making it a key enabling technology for autonomous trains and an ideal solution for the world’s first AutoHaul® project,” added Hania. “The success of this pilot project has the potential to rapidly accelerate the rollout and adoption of our technology across the rail industry.”

About Rail Vision Ltd.

Rail Vision is a development stage technology company that is seeking to revolutionize railway safety and the data-related market. The company has developed cutting edge, artificial intelligence based, industry-leading technology specifically designed for railways. The company has developed its railway detection and systems to save lives, increase efficiency, and dramatically reduce expenses for the railway operators. Rail Vision believes that its technology will significantly increase railway safety around the world, while creating significant benefits and adding value to everyone who relies on the train ecosystem: from passengers using trains for transportation to companies that use railways to deliver goods and services. In addition, the company believes that its technology has the potential to advance the revolutionary concept of autonomous trains into a practical reality. For more information please visit https://www.railvision.io/

Forward-Looking Statements

This press release contains “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act and other securities laws. Words such as “expects,” “anticipates,” “intends,” “plans,” “believes,” “seeks,” “estimates” and similar expressions or variations of such words are intended to identify forward-looking statements. For example, the Company is using forward-looking statements when it discusses the design and duration of the pilot program, the potential of the Company’s products, and that the success of this pilot project has the potential to rapidly accelerate the rollout and adoption of the Company’s technology across the rail industry. Forward-looking statements are not historical facts, and are based upon management’s current expectations, beliefs and projections, many of which, by their nature, are inherently uncertain. Such expectations, beliefs and projections are expressed in good faith. However, there can be no assurance that management’s expectations, beliefs and projections will be achieved, and actual results may differ materially from what is expressed in or indicated by the forward-looking statements. Forward-looking statements are subject to risks and uncertainties that could cause actual performance or results to differ materially from those expressed in the forward-looking statements. For a more detailed description of the risks and uncertainties affecting the Company, reference is made to the Company’s reports filed from time to time with the Securities and Exchange Commission (“SEC”), including, but not limited to, the risks detailed in the Company’s final prospectus (Registration No. 333- 262854), filed pursuant to Rule 424(b)(4) with the SEC on April 1, 2022. Forward-looking statements speak only as of the date the statements are made. The Company assumes no obligation to update forward-looking statements to reflect actual results, subsequent events or circumstances, changes in assumptions or changes in other factors affecting forward-looking information except to the extent required by applicable securities laws. If the Company does update one or more forward-looking statements, no inference should be drawn that the Company will make additional updates with respect thereto or with respect to other forward-looking statements. References and links to websites have been provided as a convenience, and the information contained on such websites is not incorporated by reference into this press release. Rail Vision is not responsible for the contents of third-party websites.

Contacts
Shahar Hania
Chief Executive Officer
Rail Vision Ltd.
15 Ha'Tidhar St
Ra'anana, 4366517 Israel
Telephone: +972- 9-957-7706


FAQ

What is the significance of the pilot program between Rail Vision and Rio Tinto?

The pilot program is critical for advancing the AutoHaul® project, aiming to enhance autonomous train operations and safety.

When did Rail Vision begin its test with Rio Tinto?

The testing with Rio Tinto commenced in May 2022.

What distance have the autonomous trains covered in the Rail Vision pilot?

The autonomous trains have traveled over 4.5 million kilometers since their deployment.

What technology does Rail Vision's Main Line System utilize?

The Main Line System uses AI and deep learning to detect and classify obstacles on tracks.

How does the AutoHaul® project improve railway safety?

The AutoHaul® project utilizes advanced technology to enhance obstacle detection, thereby improving safety in autonomous train operations.

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