ARSOFT winner of the challenge "Virtual Reality Training" organized by the Renfe startup accelerator

ARSOFT has won the challenge "Virtual Reality Training" organized by Renfe's startup accelerator, whose objective is to develop a tool for train drivers in driving.

In its commitment to Virtual Reality to make a quality leap in its training programs, Renfe has recognized ARSOFT as the winner of the Virtual Reality Training challenge of the V TrenLab Call, with 50,000 euros to develop the pilot of its project in Renfe's startup acceleration program.

Real infrastructure environments and specific vehicles will be digitized to train situations and skills necessary to complement safety training for driving personnel.

A virtual technology with a genuine impact

The investment figures clearly reflect the growth and deployment of Virtual Reality and augmented reality in education. The estimated volume of the educational market in these two technologies is 300 billion dollars by 2032, according to a study by Sheer Analytics and Insights. And, in particular, the market linked to Virtual Reality applied to training is $142 billion by 2031, according to Transparency Market Research.

But the impact is not only economic. For example, until now the training of operators depended on the system or methodology with which the training was delivered. All this has changed thanks to virtual reality, a technology through which ARSOFT has developed the EyeFlow authoring platform, which allows companies and professionals to work with augmented reality, virtual reality and mixed reality content in a simple, fast and sustainable way.

In the context of the railway sector, virtual reality simulators can recreate routes, driving cabs or places such as train stations so that, in this way, train drivers can train in a safe environment their skills and abilities, as well as reproduce as many times as desired possible incidents such as accidents, fires, adverse weather conditions or breakdowns. In this sense, ARSOFT offers substantial advantages by improving the learning curve of the machinists, avoiding the use of real machinery and saving travel, which also means an improvement in the sustainability of the project. This proposal offers a self-evaluation capacity for a more autonomous training, in which the operators can have access to the training contents at any time from all types of devices.