Ever-expanding cities require a public transport system that carries more people more efficiently. Increasing automation aims to increase the capacities of trains on existing tracks – and that includes driverless trains.
The global shift to city life shows no sign of slowing down. Experts estimate that today nearly half the world’s population lives in cities, and this number is expected to rise to 70 percent by 2050. By 2025 there will be at least 27 megacities in the world with populations of over ten million people. In order to keep pace and ensure the success of economic centres worldwide, public transportation systems will have to carry more people faster and more efficiently than ever.
More driverless transport capacity
Train manufacturers believe the answer lies in using fully automated metro trains. Properly equipped rapid-transit and underground trains can travel closer together, thereby carrying more passengers in the same time than a train with a human driver is able to do. Driverless trains have already been in service in numerous cities for some years: Algiers, Paris, Barcelona, Sao Paolo and also in Nuremberg.
In automatically controlled trains, the movement authority and control commands are not indicated by signals, but are issued via data communication between the rail vehicle and the trackside equipment. A computer tracks all trains in the assigned section of line and calculates an appropriate movement authority for each train. As a result, trains are routed continuously and can run at shorter headways than when driven manually on sight of a signal. In driverless operation, the trackside computers are constantly exchanging data by radio with the computers of the higher-level system in the control centre and the computers in the train. On board the train, the automatic train control system replaces the train driver and controls the train’s speed. The computer is monitored and, if necessary, corrected by the automatic train protection system.
Control signals and passenger information via LTE
Connecting trains with one another and with the control centre by radio requires a correspondingly powerful communication network. In the world’s first live pilot trial, Huawei has teamed up with Alstom to carry out tests on a Long Term Evolution (LTE) 4G multi-service broadband radio network for train control. Not only is the LTE network used to transfer the control data, it also enables passenger information systems and live streaming of CCTV images to the train.
Assistance systems protect against collisions
However, the technology is not restricted to autonomous trains – just as for cars, companies are also currently developing assistance systems for train drivers. Intelligence on Wheels, a company based in Gilching near Munich, offers a train collision avoidance system that is a complete departure from the traditional train safety systems. All of the components are installed inside the trains, which means the system does not require any expensive technology in the infrastructure, i.e. along the railway track. The system records all the parameters necessary for the train to avoid a collision, including the exact position, speed and also braking capacity. The key asset of the system is direct train-to-train communication based on the TETRA standard for trunked radio systems, which operates on a frequency band between 380 and 470 MHz. As soon as two trains come closer than five kilometres, they exchange information about their position on the track, speed, driving direction and so on. The localisation module consists of a multi-sensor set-up combining a GPS and a six degree-of-freedom inertial sensor. Among other functions, the system can determine the direction of travel by means of radial acceleration when driving round bends. If the system detects a critical situation, the train personnel are given an acoustic and visual warning in time to avoid a possible collision and bring the train to a stop.
Bombardier has also developed an anti-collision system. It gives tram drivers advanced warning of a potential impact with pedestrians, cyclists, other vehicles, or objects obstructing the tram tracks. The system uses a network of stereovision cameras to identify and track the movement of people or objects on or near a tram’s path. Should a potential collision be identified, the system issues an audio warning signal. The driver, or even the system itself, can then apply the brakes.
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