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Siemens at UITP International Mass Transit Trade Show

Stockholm, 09 June to 12 June 2019

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On the way to an Autonomous Tram

Since its world premiere at the InnoTrans 2018, the research project "Autonomous Tram" has made considerable progress. The collision warning system "Siemens Tram Assistant" is ready for series production and marks an important milestone on the way to autonomous operation.

Press Pictures

Siemens Mobility presents world's first autonomous tram

This experimental vehicle is equipped with multiple lidar, radar and camera sensors that serve as "digital eyes" by capturing the tram and its traffic environment.

Siemens Mobility presents world's first autonomous tram

Siemens Mobility, together with ViP Verkehrsbetrieb Potsdam GmbH, will be presenting their research project on the world's first autonomous tram at InnoTrans 2018. On a six-kilometer section of the tram network in Potsdam, Germany, Siemens Mobility will be demonstrating a test tram driving autonomously in real traffic on September 18 through 21.

Siemens Mobility presents world's first autonomous tram

ViP has provided a Siemens Combino tram for the project. This experimental vehicle is equipped with multiple lidar, radar and camera sensors that serve as "digital eyes" by capturing the tram and its traffic environment. At the same time, complex algorithms function as a "brain" by interpreting and evaluating data from the momentary operating situation, providing a prognosis for further development of the situation, then triggering an appropriate response by the tram. Thanks to its artificial intelligence capability, the tram responds to trackside tram signals, stops at tram stops, and reacts autonomously to hazards such as crossing pedestrians and other vehicles. Siemens Mobility is the first company to launch an autonomous tram for research and development purposes.

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Mobility Made Easy: Digital Solutions for Seamless Transportation

Mobility Made Easy: Digital Solutions for Seamless Transportation
Based on a flexible and secure "Mobility as a Service" MaaS platform, a wide variety of data and interfaces can be efficiently combined to provide a holistic travel information service – whether for public transport, demand-responsive transport, road traffic information, private transport, car-sharing providers, taxis, bicycles or pedestrian navigation. At the end of an intermodal journey, the system automatically provides a ticket with the cheapest price across all transport modes and tariff zones the traveler will use.

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Seamless Digital Chain in Material Supply – the Easy Spares App

Seamless Digital Chain in Material Supply – the Easy Spares App
A key element for ensuring the high availability of rolling stock and railway infrastructure is to have a holistic logistics system for spare parts. By using artificial intelligence, virtual reality and machine-learning technologies, we can easily master this challenge.

Infographics

Easy Spares Next GenerationTM

Seamless digital material supply

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The test field for an autonomous electronic bus system in Vienna's Seestadt Aspern

The test field for an autonomous electronic bus system in Vienna's Seestadt Aspern
Self-Driving vehicles have the potential to make roadways both safer and less congested. As such, cities around the world are preparing for a future where autonomous vehicles are commonplace. In Seestadt Aspern, Siemens Mobility is working with consortium partners to provide the car-to-X (C2X) technology to ensure the autonomous electric bus effectively communicates with the infrastructure and roadways around it. This project is the first time that Austria successfully implemented C2X technology with an autonomous vehicle. The vehicle communicates with traffic lights, detects pedestrians and cyclists in the roadway and alerts the self-driving vehicles of real-time roadway dangers.

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Contact

Ellen Schramke

Siemens Mobility GmbH

+49 (30) 386-22370

Eva Haupenthal

Siemens Mobility GmbH

+49 (89) 636-24421

Kara Evanko

Siemens Mobility GmbH

+1 (202) 285-3072

Link to this page
www.siemens.com/press/uitp2019