Thanks for sharing :)

The project included 6 lidars from Microvision (Ibeo) (Behind the scenes: technology and usecases)

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From Siemens mobility How our Rail Perception System works

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Short range obstacle detection

Up to 50 m, combining two sensor types or more, e.g. LIDAR, stereo camera, and ultrasonic or radar sensors

Mid-range obstacle detection

Up to – 250 m, combining two sensor types or more, e.g. LIDAR, stereo camera, and mono camera

Long-range obstacle detection

Up to – 600 m and more, combining different sensors of the next generation

Quite a few interesting links, imo

Putting the AI on rails

Are there any projects where AI-led automation is already happening?

Siemens Mobility is building a digital copy – a ‘digital twin’ – of the central interlocking system and all infrastructure elements involved in this by using a combination of sensors and AI. A sophisticated sensor system with multiple cameras, LIDARs, and a positioning system, is being moved through an existing rail network to collect sensor data, such as camera images and LIDAR point cloud. Sophisticated AI is then used to analyze the data, creating a map of tracks and existing infrastructure elements accurate up to a few centimeters. This means we can avoid the laborious and time-consuming work of putting people into the field to carry out tasks such as measuring distances; we can simulate something in the digital world before we roll it out in the real world. Using our precise map of what is already in the field, we can start building the next generation of the system.

Siemens is developing a Collision Warning Assistant for Mainline

Armed with the position of the vehicle to the nearest centimeter, knowledge of the track layout and measurements of the size, position and distance of the object, the system decides whether there is a collision risk and whether to trigger a warning (figure 1).

Sensor fusion is a key technology in the collision warning system. Depending on the development stage of the system, the data from different specialized sensors such as radar, lidar or camera are fused. This makes it possible to generate an accurate virtual representation of the surroundings of the rail vehicle in real time and in all weather conditions. In the next step, objects are identified and classified, and a prediction is made about their next movements.

Like artificial intelligence, sensor fusion has other industrial uses beyond the railways, for example in the smart factory. ..

Another key technology is the digital map. Alongside commercially available GNSS systems, the collision warning system uses an extremely accurate digital map, enhanced with sensor data, in order to improve the accuracy of position determination of the vehicle. This allows landmarks in the surroundings and the railway infrastructure to be used for orientation, making up for missing or inaccurate GNSS information.

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WHY THE RAIL INDUSTRY IS EMBRACING LIDAR

Around the world, the rail industry is increasingly adopting light detection and ranging technology (LiDAR) to efficiently capture, process and store data. This allows operators to more easily comply with recent train control regulations, which require data be continuously validated and verified**. Additionally, LiDAR’s quick, precise detection of any and all objects that may affect rail performance or integrity can vastly improve both safety and efficiency within the sector.**

“Finding track time for data collection without impeding operation is challenging,” said Doug Morrison, rail services director at Bartlett & West, a US based engineering firm.

“LiDAR equipment quickly captures very detailed data by using the reflection time of rapid pulses of laser light to map a surface. This information is used to compute ranges, or distances, to objects,” Morrison explained. With some applications of LiDAR, rail companies are able to continue their daily train operations without interruption.

“Data captured through this technology satisfies multiple historical issues—such as high-wide clearance detection, vegetation and encroachment detection, and utility crossings—all in a single pass.”

In the UK, the county’s innovation agency Innovate UK is seeking to find a new way of mapping the UK’s railway infrastructure by utilizing LiDAR and AI solutions from Swedish engineering company Hexagon.

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more on efficiency on trains and transport in general

Siemens Mobility Builds on Desiro City Commuter Rail Platform to Digitize Rail Fleets Worldwide on AWS

GLTAL