DE102019213818A1 - Detection of acoustic equipment at a level crossing - Google Patents

Abstract

A method for detecting acoustic equipment of a level crossing, comprising the following steps: detecting a noise which was emitted by an acoustic equipment of a level crossing; Determining a reaction to the detected noise by means of a computing unit which can be operated on a road vehicle.

Description

FIELD OF THE INVENTION

The present invention relates to a method for detecting noises from acoustic equipment of a level crossing.

TECHNICAL BACKGROUND

The patent application DE 10 2018 214 420 shows a method for detecting travel noises from rail vehicles.

SUMMARY OF THE INVENTION

Proceeding from this, the invention is based on the object of providing an improved method for detecting rail vehicles in the vicinity of a level crossing.

According to the invention, this object is achieved by a method for detecting acoustic equipment of a level crossing with the features of claim 1.

• - Ein Verfahren zum Detektieren von akustischen Betriebsmitteln eines Bahnübergangs mit den folgenden Schritten: Detektieren eines Geräuschs, welches von einem akustischen Betriebsmittel eines Bahnübergangs emittiert wurde; Ermitteln einer Reaktion auf das detektierte Geräusch mittels einer Recheneinheit, welche an einem Straßenfahrzeug betreibbar ist.

Accordingly, it is provided:

• A method for detecting acoustic equipment of a level crossing with the following steps: detecting a noise which was emitted by an acoustic equipment of a level crossing; Determining a reaction to the detected noise by means of a computing unit which can be operated on a road vehicle.

A road vehicle is a land vehicle that is primarily intended for use on roads. It is characteristic of all road vehicles that they can maintain or change their direction of travel on the surface they drive on with the help of static friction and do not need any tracks for this. For example, motor vehicles are road vehicles.

Rail vehicles are rail vehicles that travel or are guided on one or more rails. The vehicle and rail are a coordinated system, usually referred to as a wheel-rail system. For example, trains are rail vehicles.

A microphone is a sound transducer that converts airborne sound as alternating sound pressure vibrations into corresponding electrical voltage changes as a microphone signal.

A camera is a photographic apparatus that can record static or moving images on photographic film or electronically on magnetic video tape or digital storage medium or transmit them via an interface.

Warning signals are perceptible to the driver of a vehicle and increase or focus their attention. Warning signals can be optical, acoustic or haptic signals.

An intersection between a rail and a road is also known as a level crossing. A level crossing can be restricted or unrestricted. Barred level crossings can have multiple or single lane barriers. Light signal systems for emitting a warning signal are often provided at level crossings that are not barred.

In some countries, e.g. in Germany, level crossings have an acoustic warning device, e.g. a bell. A chime announces an imminent lowering of railway barriers with a number of chimes. The number of times the bell strikes can vary from region to region. Older electrical systems as well as mechanical systems supplemented by road signals are usually equipped with bells, also known as alarm clocks.

Components of a level crossing that emit noise are acoustic equipment. Visible characteristic features are optical features, for example railway barriers, traffic signs or St. Andrew's crosses.

A St. Andrew's cross is a cross with two diagonally crossing bars. It is also called the cross section after the holding device. If the cross consists of inclined bars, the term inclined cross is also used. This cross is often found at level crossings.

Position data are, for example, GPS data. They enable objects or systems to be located, here level crossings. Train passages are train passages through a level crossing. Data relating to train passages can include a time and / or data relating to the length of the train and / or the duration of the road block.

A data connection can be wired or wireless. Wireless data connections are, for example, radio connections or Lifi connections. Lifi is an optical technology that encodes signals into light. The Internet is a worldwide association of computer networks, the autonomous systems. It enables the use of Internet services such as WWW, e-mail, Telnet, SSH, XMPP, MQTT and FTP. Each computer can connect to any other computer. Of the Data exchange between the computers connected via the Internet takes place via the technically standardized Internet protocols.

An artificial neural network (ANN) is, in particular, a network of networked artificial neurons which is simulated in a computer program. The artificial neurons are typically arranged on different layers. The artificial neural network usually comprises an input layer and an output layer, the neuron output of which is the only one of the artificial neural network that is visible. Layers located between the input layer and the output layer are typically referred to as hidden layers. Typically, an architecture or topology of an artificial neural network is first initiated and then trained in a training phase for a special task or for several tasks in a training phase.

The term “topology of an ANN” encompasses all aspects relating to the structure of an ANN. This includes, for example, the number of neurons of the ANN, the division of the neurons into the individual layers of the ANN, the number of layers of an ANN, the networking of the neurons and the weighting of the networking.

The training of the artificial neural network typically includes a change in the weight of a connection between two artificial neurons of the artificial neural network. The weight contains information on the strength of the consideration of an input of a neuron. The training of the artificial neural network can also include developing new connections between artificial neurons, deleting existing connections between artificial neurons, adapting threshold values of the artificial neurons and / or adding or deleting artificial neurons.

An interface is a device between at least two functional units at which an exchange of logical quantities, e.g. data, or physical quantities, e.g. electrical signals, takes place, either unidirectionally or bidirectionally. The exchange can be analog or digital. The exchange can also be wired or wireless.

A controller is an electronic module for controlling or regulating. Controls are used in all imaginable electronic areas in the automotive sector, as well as for controlling machines, systems and other technical processes.

A reaction to a noise from acoustic equipment at a level crossing is, for example, a warning signal to a driver or a braking signal for braking the vehicle. Devices for carrying out the signals are reaction units.

A computing unit is a device that processes incoming information and outputs a result resulting from this processing. Electronic circuits such as central processing units or graphics processors are computing units.

An audio signal (also sound signal) is an electrical signal that transports acoustic information or acoustic noise.

Computer program products generally comprise a sequence of instructions which, when the program is loaded, cause the hardware to carry out a specific method that leads to a specific result.

The basic idea of the invention is to record vehicle environment-related noises of a road vehicle and, if necessary, to detect a noise in the recorded audio data which was emitted by an acoustic device of a level crossing. If a noise that was emitted by acoustic equipment at a level crossing was detected, the invention provides for a reaction to the detected noise to be determined by means of a computing unit which can be operated on a road vehicle.

In this way, the software-supported control of a vehicle can be improved and the safety of the road vehicle compared to rail vehicles can be optimized.

It goes without saying that a driver assistance system for a road vehicle is also advantageous for carrying out the method according to the invention. In this context, the invention provides for vehicle-environment-related noises to be recorded by means of a plurality of microphones, the recorded vehicle-environment-related noises to be evaluated by means of a computing unit and to react by means of a reaction unit on the basis of a detected noise.

It is also understood that a training system that uses a driver assistance system to detect noises from acoustic equipment at a level crossing or to the Determining a reaction to the detected sound trained, is advantageous.

Advantageous refinements and developments emerge from the further subclaims and from the description with reference to the figures of the drawing.

According to a preferred development of the invention, the noise is emitted by a railway barrier and / or by a bell. Both railway barriers and bells emit particularly characteristic noises of a level crossing, which typically do not change over a long period of time and are at least similar or identical over large stretches of land.

It is also useful to determine and evaluate the number of strikes of a bell.

It is thus possible to evaluate information which is coded in the number of strikes of a bell.

According to a preferred development of the invention, optical features of a level crossing, in particular a railway barrier, a St. Andrew's cross, a flashing light and / or rails, are detected by means of a camera.

The acoustic process can thus be improved with optical means.

According to a preferred development of the invention, position data of a level crossing and / or data relating to train passages are retrieved via a data connection, in particular via the Internet. The acoustic method for detecting acoustic equipment at a level crossing can thus be checked for plausibility.

Alternatively or additionally, existing data, for example an HD card, can be checked for plausibility.

According to a preferred development of the invention, a microphone and / or a camera is activated on the basis of a detection of a noise from acoustic equipment of a level crossing and / or on the basis of an optical feature of a level crossing and / or on the basis of a data retrieval of position data or a data retrieval of data regarding train passages aligned.

The method can thus be set more precisely, or it is possible to determine reactions more precisely.

According to a preferred development of the invention, the reaction is determined by means of an artificial neural network. This ensures that the method learns during its operation without the need for further software updates.

According to a preferred development of the invention, the reaction is a control signal which is aimed at bringing the road vehicle to a stop at a stop line of the level crossing. The method thus contributes to further improving the safety of a road vehicle or to ensuring fully autonomous control of a road vehicle.

According to a preferred development of the invention, the reaction includes warning a driver of the road vehicle. The method thus improves safety even for road vehicles that are not fully autonomously controlled.

According to a preferred development of the invention, the reaction includes warning other road users. For example, provision can be made to warn careless pedestrians or cyclists by means of acoustic signals emitted by the road vehicle or to draw their attention to the level crossing. Pedestrians and cyclists are often distracted from road traffic by technical devices, for example smartphones, and thus overlook crossing traffic. Accordingly, the present invention makes it possible to defuse such traffic situations.

Alternatively, it can also be provided to warn other road users, in particular other vehicles, by flashing or other light signals.

The computer program product according to one embodiment of the invention carries out the steps of a method according to the preceding description when the computer program product runs on a computer, in particular a computer internal to the vehicle. When the program in question is used on a computer, the computer program product produces an effect, namely the improvement of the safety of road vehicles at level crossings.

Figure list

• 1 ein schematisches Blockdiagramm gemäß einer Ausführungsform der Erfindung;
• 2 ein Blockschaltbild eines Trainingssystems gemäß einer Ausführungsform der Erfindung.

The present invention is explained in more detail below with reference to the exemplary embodiments specified in the schematic figures of the drawings. It shows:

• 1 a schematic block diagram according to an embodiment of the invention;
• 2 a block diagram of a training system according to an embodiment of the invention.

The accompanying drawings are intended to provide a further understanding of the embodiments of the invention. They illustrate embodiments and, in conjunction with the description, serve to explain principles and concepts of the invention. Other embodiments and many of the advantages mentioned emerge with a view to the drawings. The elements of the drawings are not necessarily shown to scale with one another.

In the figures of the drawings, identical, functionally identical and identically acting elements, features and components - unless stated otherwise - are each provided with the same reference symbols.

DESCRIPTION OF EXEMPLARY EMBODIMENTS

1 shows a schematic block diagram of a method for detecting acoustic operating resources of a level crossing. In step S1, a noise is detected which was emitted by acoustic equipment of a level crossing. In step S2, a reaction to the detected noise is determined by means of a computing unit which can be operated on a road vehicle.

2 shows a block diagram of a training system 10 according to one embodiment of the invention. The training system 10 includes an interface 12th as well as an evaluation unit 20th with an KNN 22nd . The KNN 22nd includes several neurons that are in 2 simplified with 108a-f are shown. In doing so, the neurons form 108a , b an entry layer 102 who have favourited Neurons 108c , d , e form a hidden layer 104 and the neuron 108f forms an output layer 106 .

The neurons 108a , b the entrance layer 102 are through the interface 12th with an audio signal 16 fed forward. The audio signal 16 is in the neurons 108a , b the input layer weighted with initial weights. It can be provided that the audio signal 16 is broken down into several signal components and the signal components are weighted. It can be provided that one or more functions are applied to the weighted input data. The evaluation of the function forms the output value of a neuron 108a , b that goes to the neurons 108c , d , e the next lower layer, i.e. the hidden layer 104 , are transferred as input values. It can be provided that the hidden layer 104 has multiple layers.

Similar to the entry layer 102 are sent to the neurons 108c , d , e The input values transferred to the hidden layer are weighted and one or more functions are applied to the weighted input values. The evaluation of the functions that is applied to the weighted input values form the output values of the neurons 108c , d , e . These output values are sent to the neurons of the output layer 106 transferred as input values. In 2 are the neurons of the output layer 106 exemplified as a neuron 108f shown. The neuron 108f calculated from the input values received from the neurons 108c , d , e the hidden layer 104 were passed, weighting the input values and applying one or more functions to the weighted input values, an output value. An actual response signal can be derived from this initial value 24 derive. This process is also referred to as feeding an ANN forward.

The next step is the actual response signal 24 with the target response signal 18th which of the evaluation unit 20th through the interface 12th was passed, compared.

The next step is the topology of the individual layers 102 , 104 , 106 of the KNN 22nd adapted so that the KNN 22nd for the transferred audio signal 16 the target response signal 18th calculated. The adaptation of the topology 26th can include changing the weights, adding connections between neurons, removing connections between neurons and / or changing functions that are applied to weighted input values. This process is also referred to as reverse feeding of an ANN.

List of reference symbols

S1-S2

Procedural steps

10

Training system

12th

interface

14th

Training data

16

Audio signal

18th

Target response signal

20th

Evaluation unit

22nd

artificial neural network

24

Actual response signal

26th

topology

102

Entry layer

104

hidden layer

106

Output layer

108a-f

Neurons

QUOTES INCLUDED IN THE DESCRIPTION

This list of the documents listed by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent literature cited

• DE 102018214420 [0002]

Claims (13)

Method for detecting acoustic equipment of a level crossing with the following steps: - Detecting (S1) a noise which was emitted by an acoustic operating means of a level crossing; - Determination (S2) of a reaction to the detected noise by means of a computing unit which can be operated on a road vehicle. Procedure according to Claim 1 , the noise being emitted by a railway barrier and / or by a bell. Procedure according to Claim 2 , whereby a number of strikes of a bell is evaluated. Method according to one of the preceding claims, wherein optical features of a level crossing, in particular a level crossing, a St. Andrew's cross, a flashing light and / or rails are detected by means of a camera. Method according to one of the preceding claims, wherein position data of a level crossing and / or data relating to train passages are called up via a data connection, in particular via the Internet. Method according to one of the preceding claims, wherein a microphone and / or a camera are aligned on the basis of a detection of a noise and / or on the basis of a detection of an optical feature of a level crossing and / or on the basis of a data retrieval of position data or data with regard to train passages. Method according to one of the preceding claims, wherein the reaction is determined by means of an artificial neural network. Method according to one of the preceding claims, wherein the reaction is a control signal which is aimed at bringing the road vehicle to a stop at a stop line of the level crossing. A method according to any preceding claim, wherein the response comprises warning a driver of the road vehicle. Method according to one of the preceding claims, wherein the reaction comprises warning other road users. Driver assistance system for a road vehicle for performing a method according to one of the preceding claims a plurality of microphones for capturing audio signals from the environment of the road vehicle; a computing unit for evaluating the recorded audio signals with regard to the detection of noises of an acoustic operating means of a level crossing and for determining a reaction to a detected noise and with a reaction unit for carrying out a determined reaction on the basis of the detected noise. Computer program product with program code means in order to implement a method according to one of the Claims 1 to 10 perform. Training system (10) for a vehicle control for detecting noises of acoustic equipment of a level crossing with - at least one interface (12) in order to receive training data (14) which each have an audio signal (16) and a target reaction signal (18) - An evaluation unit (20) which forms an artificial neural network (22) and is set up to feed the artificial neural network (22) forward with training data (14) in order to determine actual reaction signals (24), and a changed topology ( 26) of the artificial neural network (22), in particular weights, by feeding back the setpoint reaction signals (18) in the artificial neural network (22), the topology (26) being set up in the driver assistance system Claim 12 to be saved.

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