EP1032928A1

EP1032928A1 - Method and device for signalling local traffic delays

Info

Publication number: EP1032928A1
Application number: EP98963454A
Authority: EP
Inventors: Gerd Binnig
Original assignee: Delphi 2 Creative Technologies GmbH; Definiens AG
Current assignee: Definiens AG
Priority date: 1997-11-17
Filing date: 1998-11-13
Publication date: 2000-09-06
Anticipated expiration: 2018-11-13
Also published as: JP2001523871A; US20020082768A1; WO1999026212A1; DE19750942A1; EP1032928B1; JP4132662B2; DE59803467D1; US6397141B1

Abstract

The invention relates to a method and device for signalling local traffic delays. Decentralised communication occurs between vehicles by exchanging respective vehicle data. Repeated evaluation of individual vehicle data enables each reference vehicle to determine a relevant vehicle group within a maximum vehicle group and to compare the behaviour of said relevant group to its own behaviour. The result of the comparison is displayed in the reference vehicle. A regular traffic flow can thus be produced and the number of accidents can be reduced.

Description

description

Method and device for signaling local traffic disruptions

The invention relates to a method and a device for signaling local traffic disturbances and in particular to a method and a device for recognizing and displaying accidents and increased traffic and the congestion caused thereby.

In order to avoid traffic jams and accidents with increased traffic volume, conventional traffic control systems have already been permanently installed along particularly heavily used traffic sections, such as, for example, heavily used motorways, etc. Conventional traffic control systems of this type have a large number of detection devices which detect, for example, the traffic density, the speed of the motor vehicle current, the ambient conditions (temperature, fog) etc. and use the respective detection signals to control the motor vehicle traffic along the predetermined section in such a manner that congestion or accidents are prevented as far as possible.

A disadvantage of such conventional traffic control systems is the fixed installation along a predetermined route section, which results in extremely high acquisition costs. In addition, such a permanently installed traffic control system has little flexibility, since it only regulates or directs traffic in relatively short sections.

To increase flexibility, US Pat. No. 4,706,086 proposes a communication system between a large number of motor vehicles, in which signals and information are transmitted in accordance with the respective driving conditions of the motor vehicle a transmitting / receiving unit is transmitted by means of electromagnetic radio waves.

Furthermore, from the document US-A-5, 428, 544 a device and a method for signaling local traffic disturbances is known, in which the vehicle data or states of the motor vehicle, such as the speed, route and direction, are mutually transmitted via communication devices . The respective data are transmitted to another motor vehicle in an indirect manner via an oncoming motor vehicle. In addition, this conventional traffic information system requires a navigation module, a map module and an intrinsic position determination device for identifying one's own position. However, such conventional communication systems have the disadvantage that they absolutely require a large number of extremely expensive elements, such as, for example, a map memory, a navigation module and a positioning module for recognizing one's own position.

The invention is therefore based on the object of providing a method and a device for signaling local traffic disruptions which is relatively inexpensive to manufacture, has a high degree of flexibility and is independent of permanently installed detection devices.

According to the invention, this object is achieved by the measures and features of claims 1 and 9.

In this case, a maximum group of vehicles to be considered is determined as a function of a predetermined minimum signal level of an electromagnetic radio signal that is emitted by a large number of vehicles. The individual vehicle data transmitted with the radio signal, which the respective movement states of the Play vehicles lying within the reception range, are repeatedly evaluated and saved. Based on the stored vehicle data, a relevant group of vehicles within the maximum group of vehicles is determined for each reference vehicle to be examined by evaluating the individual vehicle data. The group behavior is then determined on the basis of the individual vehicle data of the vehicles within the relevant group. This group behavior is signaled in the reference vehicle so that a driver is informed in good time of any changes or dangers within his relevant vehicle group. Accidents and traffic jams can thus be recognized or avoided in good time.

The relevant group of vehicles is preferably determined by means of a method for fractally Darwinian object generation, an order or sequence within a group of vehicles being continuously generated by considering the respective vehicle data and then weighting a possible position probability. In this case, a precise positioning or sequence of the respective vehicles within a group can be determined even with a minimal number of vehicle data, without using expensive positioning systems.

A group to be considered in each case can result in particular from a maximum reception range of a reception device. However, it can also be determined by a maximum storage capacity.

An identification code for identifying a respective vehicle, a speed value for specifying an instantaneous speed of the vehicle and a distance parameter are preferably used as vehicle data. The one distance between the reference vehicle and The distance parameters representing the respective vehicles from the maximum group can be derived, for example, from the reception field strength of the radio signal transmitted in each case.

Further vehicle data include, for example, a deceleration / acceleration value for specifying an instantaneous deceleration / acceleration of the respective vehicle, a steering angle for specifying an instantaneous steering angle of the respective vehicle, a direction value for specifying an instantaneous absolute direction, a position value for specifying one instantaneous absolute position of the respective vehicle, and a brake signal value for specifying an instantaneous use of a braking device of the respective vehicle are conceivable. Furthermore, a group behavior value can also be forwarded as a vehicle date, which reflects the current group behavior of a relevant group belonging to the reference vehicle.

The information signaled in the reference vehicle can be made both visible and audible via a display device. However, it can also lead directly to a control of the braking behavior of the reference vehicle or else influence the engine control, as a result of which, for example, automatic full braking can be implemented.

In particular when there is a predetermined combination of individual vehicle data, that is to say movement states, of a respective vehicle, an emergency signal can be generated which has higher priority than the individual vehicle data signals. In this way, for example, if an acute danger occurs, this state can be passed on to groups of vehicles further back as quickly as possible, which results in a particularly rapid spread of information. In order to To avoid storing a large number of emergency signals, such an emergency signal is only passed on to a greater extent (repeater function) if its reception field strength falls below a predetermined threshold value.

The invention is described below using exemplary embodiments with reference to the drawing.

Show it:

1 shows a schematic illustration of a traffic situation on a country road,

2 shows a schematic illustration of a traffic situation on a multi-lane motorway, FIG. 3 shows a block diagram of the device for signaling local traffic disturbances according to a preferred exemplary embodiment, and

4 shows a table which represents an example of a storage of respective vehicle data in a storage device.

Figure 1 shows a schematic representation of a traffic situation as it can occur, for example, on a country road. In FIG. 1, reference symbol 0 denotes a reference vehicle, while reference symbols 1 to 4 represent vehicles in a preceding column. The vehicles 0 to 4 each have transmission / reception devices with which they transmit their individual movement states or vehicle data or receive the vehicle data transmitted by the other vehicles. In the exemplary embodiment according to FIG. 1, only the transceiver of the reference vehicle 0 is now taken into account, with particular reference being made to the data received. It is assumed that the reference vehicle 0 travels a certain distance behind the vehicle column consisting of vehicles 1 to 4, but because of a route through a forest, for example, has no visual contact with the column.

It is assumed that at least one of the vehicles 1 to 4 of the column has a corresponding transmission / reception system as the reference vehicle 0 and thus transmits its individual vehicle data in the form of electromagnetic radio waves. The transmitted vehicle data signals have as minimum vehicle data an identification code IC, which identifies a respective vehicle, and a speed value v, which indicates the current speed of the respective vehicle.

It is further assumed that a group classification (described later) or

Order has taken place and the truck 4 has identified itself as the vehicle in front, which the vehicles 3, 2 and 1 follow in this order. The group behavior of this column can be described, for example, by an almost identical speed of, for example, 50 km / h. If the following faster reference vehicle 0 now reaches the reception area of the radio signal of vehicle 1, then its vehicle data, that is to say at least the identification code IC of vehicle 1 and its speed value v (50 km / h) are received at reference vehicle 0 with a predetermined reception field strength and saved. This process is carried out until, based on decision criteria described later, a relevance check is deemed to have been met and vehicle 1 is recognized as a vehicle relevant to reference vehicle 0. In the same way, vehicles 2 to 4 are recognized as relevant vehicles, as a result of which a group of vehicles relevant for reference vehicle 0 is formed. The training or relevance criteria for training the relevant group of vehicles will be described later. In this way, the reference vehicle 0 receives a large number of vehicle data of the column or relevant group of vehicles traveling in front of it. The vehicle data of the relevant vehicles are evaluated via an evaluation device and compared with the vehicle data of the reference vehicle 0 or related to one another. Depending on this comparison, a signal is now generated in the reference vehicle 0, which can consist, for example, of a visible or audible display to reduce the speed. In this way, an early warning can be given long before visual contact with a relevant group of vehicles, which safely prevents accidents.

However, the generated signal value can not only cause an audible or visible display in the reference vehicle 0, but can also cause automatic braking or acceleration.

In this way, a method and a device for signaling local traffic disruptions are obtained which are extremely flexible and do not require any permanently installed sensors or display devices. The cost of such a system for signaling local traffic disruptions is therefore extremely low.

To increase the accuracy of the system, further vehicle data can be recorded and transmitted. Such vehicle data are, for example, a deceleration value or acceleration value v, which indicates an instantaneous deceleration or acceleration of a respective vehicle

Steering angle θ, which indicates an instantaneous steering angle of the respective vehicle, a direction value DIR, which for example uses a compass to reflect the instantaneous absolute direction of the respective vehicle. dergenden, a position value POS, which indicates the current absolute position of the respective vehicle, for example via a GPS system, or a brake signal value BREMS, which indicates an instantaneous use of a braking device of the respective vehicle. In addition, a recognized group behavior value, for example the average speed of the entire group, can be transmitted as a vehicle date, which can result in groups being linked to one another to superordinate groups.

For determining the relevant group of vehicles 1 to 4, a method for fractally Darwinistic object generation is preferably carried out, as is known, for example, from German patent application DE 197 47 161 (filed on October 24, 1997). Here, the fractal, hierarchical object library is particularly adapted to the requirements of traffic situations, the property rules, for example, defining a specific driving situation of the respective vehicle, the context rules defining the sequence within the group of vehicles, and the modification rules, the continuous regrouping of vehicles, for example, when overtaking establish. The fractal, hierarchical object library has typical traffic situations as basic objects, for example for driving on country roads, on motorways or in heavy city traffic. Typically, a large number of vehicle data are examined at time intervals for each vehicle in a specific group, which, for example, iteratively increases the classification probability for a specific membership in a group or a specific position within a group.

Since the use of the method for fractal Darwinian object creation is a preferred method for determining the relevant vehicles or vehicle groups below, the basic considerations of fractal Darwinian object creation are given in a general manner.

In the following, only two-dimensional images are considered here, which are viewed as a complex structure to be examined or as objects with a complex relationship. Such structures to be examined can, however, also be the traffic situations described above, in which the individual vehicles combine to form subordinate and superordinate objects or groups.

In the method described below, the detection and generation of a traffic situation, for example, is understood as an honor-scale or fractal and evolutionary or Darwinian process. The individual objects of a traffic situation are treated here as a kind of independent "living being", which are very vague, formal and unrealistic at the beginning of the procedure, but which change repeatedly when the procedure is carried out and become more concrete so that they are better adapted to one Adapt the library of known objects that form the wealth of experience of the computer, so to speak.

The objects are structured hierarchically. Large or higher-level objects are thus broken down or broken down into sub-objects or subordinate objects, while small or subordinate objects are combined to form large or higher-level objects. The procedure for adapting the objects to the object library thus takes place on several levels (scales). When making a comparison with the object library, property rules for the objects and context rules between the objects as well as hierarchical structures are important for this adjustment. For the optimal adaptation of all objects and structures to create the most sensible solution, evolutionary ones

Algorithms used. Among other things, the general Darwinian mechanisms are used, which are briefly described below:

Isolation, attraction

According to the present invention, isolation is to be understood as the delimitation of partial areas, for example of an image to be examined, from objects. This can be done by disassembling or smashing or segmenting according to certain algorithms. A method is preferably used for the segmentation, in which the similarity or affiliation between picture elements and picture segments is determined taking into account homogeneity criteria. Conversely, the small objects or subordinate objects can also be combined into large or superordinate objects. In this case, limiting this grouping to a certain number of group members corresponds to isolation. For example, a hierarchical object structure can be created largely without knowledge and thus lead to a hierarchical abstraction of any given data set by combining smaller objects into larger objects if the application of a homogeneity criterion leads to a value that is below a threshold value. As a homogeneity criterion, for example, the difference between the size-weighted heterogeneity h of an object newly created by fusion or foundation and the sum of the heterogeneities of the original objects hi or h weighted with the respective size n or n can be used. The difference .DELTA.h _weight of the weighted heterogeneity after and before, that is, at the menlegen together of two objects registered heterogeneity arises from the equation Δ gew = (ni + n ₂ ) h _new - (nihi + n ₂ h ₂ ),

this difference should be as small as possible.

In particular, of all object pairs that are potentially eligible for a merger or foundation, those are those that are the first to be combined in which the difference in weighted heterogeneity entered by the merger or foundation is the smallest. Falls below the differ- ence of the weighted heterogeneity divided by the total size (.DELTA.h _wt ./. (Nι + n ₂₎₎ a certain predetermined threshold value, objects are fused at the merger. On the other hand, a new parent object is created, that is, stored in the object library, of the smaller objects, that is, a new parent object is created if this difference in weighted heterogeneity divided by the total size is above a predetermined threshold value. A subordinate object potentially interchangeable between two objects is always actually rearranged if this exchange or rearrangement results in the weighted heterogeneity of both objects according to the equation

l'ücu n.iehlier ^ "LI W v oiii r - * π |, _la chhcιh | afterwards + π..π, ι _l ; hh _L h2n.n.lιlι _l .'i <Il orhch urhcr + 1-2 .

is reduced.

Thus a hierarchical object structure from basic objects is created by foundations, smashing, fusion, dissolution, subordination, grouping and regrouping of objects. Here, a foundation in which superordinate objects are created is opposed to smashing to create subordinate objects. The fusion to create larger objects from a variety of small objects contrasts with the resolution to create smaller objects from a large object. In the Objects are captured and subordinate to a parent object. In contrast, a subordinate object is ejected from a superordinate object during the grouping. Subordinate objects are exchanged during the regrouping.

The respective objects can have special relationships with other group members. These relationships or context rules are also referred to as attractions. In static images, the attraction or the relationship can express itself in certain patterns with characteristic relative distances, proportions or angles. In addition, predetermined properties are assigned to each object, which reflect, for example, their geometrical shape in n-dimensional space in a condensed manner, the color distribution, etc.

Variations

As already mentioned, it is often not possible to clearly define which areas of a complex structure should be referred to as objects in a first run of the method. That is why the disassembly or assembly into objects from these areas is done iteratively. Objects are therefore initially created provisionally and later iteratively modified more and more specifically. Objects are changed by excluding areas from them, for example subordinate objects, or by incorporating surrounding areas, for example neighboring objects. Another type of modification is changing the attractions or context rules.

A local modification of an object could be seen as a mutation. However, since there are different possibilities of modifications from the local modification, the general term modification is used. Selection, fitness

When the respective objects are modified, their "fitness" or "classification probability" should be optimized with regard to the object library. As a measure of their fitness or classification probability, the similarity of their bundled properties to the properties of objects in the prepared object library applies. A large number of possible objects with their possible properties or property rules are stored in the object library, i.e. significantly more objects than in the object to be examined (e.g. picture).

In addition, possible relationships or context rules of the objects to one another, that is to say their attraction, can be described in the object library. The objects or structures found in the image then also have a greater or lesser degree of similarity, that is, the classification probability to the possible attractions or context rules of the corresponding objects in the object library.

Diversity, mating

A variety of objects and object structures can also be used as long-term memory. This means that not only the absolute best (highest classification probability) of these objects or structures is survived or used, but also less good objects (lower classification probability). As a result, once found, but currently second-class options are not immediately lost. This diversity represents a memory for second or third class. This makes sense because what is second-rate at the moment can be superior in a later development phase. The variety of possible solutions also makes another type of modification possible in addition to the mutation. This white Another type of modification is referred to as "mating" or mixing and combining different solution structures.

reproduction

In nature, the reproduction of a "successful" living being increases the number of this type of living being. This increases the importance of the special genetic code because it can now act in parallel at two locations. At first glance, something similar does not make sense for objects when creating objects with a sequentially operating computer. In the case of a dynamic system, however, this can be useful at second glance, even if it is the same solution or the same object. The environment of the objects changes in a dynamic system. For this reason, the importance of an object is increased in object recognition or generation by treating the object more often and thus virtually increasing the number. If the reproduced objects are also modified, it often makes sense to save only one object plus the various modifications.

Clear

Some of the possible solutions must be deleted so that the number of possible solutions does not increase too much due to reproduction and thus unnecessarily slows down the optimization process.

Since some of the Darwinian algorithms are very specific, it is not desirable to use all possible types of algorithms simultaneously for the entire image to be examined. Rather, it makes sense to start with very general formal algorithms at the beginning of the process or "evolution". By comparison with the The object library achieves a first level of knowledge that can be used to use more targeted algorithms or modification rules. This may increase the likelihood of classification or fitness. Targeted algorithms can preferably also be used, which results in ever more sophisticated objects with individual significance and with ever increasing fitness or classification probability.

The particularity of the multiscale nature of the method according to the invention is discussed below, which plays an important role in the analysis of complex structures.

The similarity of an object of the object to be examined or of the image to that of an object of the object library corresponds to a local fitness or local classification probability. However, this local classification probability is not sufficient on its own, since ambiguity may continue to exist even for objects with a very high fitness or classification probability, ie there is a similarly high local fitness or classification probability for several objects in the object library. Often, its meaning can only be clearly recognized through the context rules or the structure of the subordinate objects of the respective object.

Multi-scale, ie fractal, approaches are therefore indispensable. The fractal treatment of a structure to be examined, for example an image or a traffic situation, therefore requires a fractal hierarchical object library, a fractal fitness or classification probability, a fractal modification and possibly a fractal reproduction and a fractal deletion. The fractal object library is a library in which not only the properties or properties rules of objects but also their possible internal and external relationships (internal and external context rules) as well as the modification rules are stored. This means that the fractal object library also stores what possible subordinate objects the object can consist of, including the possible relationships of these subordinate objects, and the relationships or contexts the object can be to superordinate objects. This is also hierarchical information, since the object is usually embedded in larger contexts and is made up of subordinate objects with their special relationships. A hierarchical or fractal fitness or classification probability can be determined from this hierarchical structure by comparison with the hierarchical structures in the library.

Based on the local fitness or classification probability, which results from the direct comparison of the object with the objects of the object library, a fractal fitness or classification probability is calculated based on this local fitness, which is derived from the local and the hierarchical fit - ness composed. These fractal classification probabilities are optimized via the modification.

FIG. 2 shows a further schematic illustration of a traffic situation as it exists, for example, on an autobahn.

Here, the reference symbol 0 again designates a reference vehicle, while the reference symbols 1 to 4 represent the vehicles relevant for the reference vehicle 0 or a relevant group of vehicles, since they are driving in front of the reference vehicle 0 in the direction of travel. The reference vehicle 0 has, for example, a maximum reception range, as indicated by the oval border. In addition to the relevant group of vehicles, there are a large number of other vehicles within this maximum reception range. On the one hand, the reference numerals 5, 6, 10 and 12 denote the vehicles which are moving in the opposite direction on the motorway, but which are also in the reception area of the reference vehicle 0. Furthermore, the reference numerals 7, 8, 9 and 11 denote vehicles which drive in the same direction of travel as the reference vehicle 0, but are located behind it and are therefore primarily or not to be taken into account for the reference vehicle 0. All vehicles send and receive vehicle data signals containing the respective vehicle data at more or less uniform intervals or continuously. Thus, for example, a large number of vehicle data are received at the reference vehicle 0, which are shown in tabular form in FIG. 4, for example.

FIG. 4 shows a simplified representation of a tabular storage of the minimum vehicle data for the respective vehicles 0 to 12. In the left column, for example, the respective identification code of a received vehicle data signal is stored in binary form (0000 to 1100). The vehicle data received at the times tn- _{3 /} t _n _ ₂ , t _n _χ and t _n are stored in the further columns in the form of a speed value v and a respective reception field strength E.

The first line of the table according to FIG. 4 shows the vehicle data of the reference vehicle 0, which serve as a comparison or as reference values for the further vehicle data. The reception field strength E is therefore not entered.

The table according to FIG. 4 will now be described in detail. It is assumed that the reference vehicle has a speed v of 120 km / h. The vehicles 1 and 3 traveling in the right-hand lane of the motorway have the same speeds vl and v3 of 100 km / h, which is why they have increasing values for the reception field strength for different times t _n _ ₃ to t _n . The reception field strength increases because the distance to vehicles 1 and 3 is reduced due to the overtaking process by reference vehicle 0. In contrast, vehicles 2 and 4 have the same speed v2 and v4 of 120 km / h, which is why their reception intensity remains constant in proportion to the distance to the reference vehicle 0.

The other values for the speed and the reception field strength of the other vehicles 5 to 12 are obtained in the same way. However, it should be noted that in particular the oncoming vehicles 5, 6, 10 and 12 due to the very high relative speed (for example vO - vl2 = 240 km / h) in the time grid of the selected exemplary embodiment, when passing through the maximum reception area of the reference vehicle 0, only leave a data value in the memory, which is preferably designed as a ring memory. This fact can be used, for example, as a criterion for object recognition or object generation in order to exclude vehicles 5, 6, 10 and 12 as an irrelevant group or to classify them as an oncoming group. In the same way, a group of following vehicles 7, 8, 9 and 11 can be determined by appropriate classification criteria if, for example, the respective deceleration times with regard to the braking process or acceleration process are checked within the fixed group.

The group of vehicles 1 to 4 relevant for the reference vehicle 0 is determined in a similar manner. A more precise classification can take place here, for example, for the vehicles 2 and 4 driving directly in front and the vehicles 1 and 3 driving in the adjacent lane. The arrangement in such a large number of subordinate and superordinate groups or objects takes place in the customary fractal Darwinian manner described above. If a group of vehicles, for example vehicles 2 and 4, is classified as a particularly relevant group, their respective group behavior can be determined, for example, by arithmetic averaging of their average speed, their deceleration behavior, etc. and compared with the vehicle data of the reference vehicle 0. On the basis of this comparison, signaling is now carried out, which is displayed, for example, in the form of known traffic symbols, that is to say speed limits, or is otherwise displayed visually or acoustically. However, there is also the possibility of evaluating the group behavior of the relevant group in such a way that, for example, the reference vehicle 0 is braked automatically if the limit value is exceeded. In this regard, a variety of other control measures are conceivable, such as control of the steering or acceleration.

In the exemplary embodiment described above, the parameter of the distance which is important for the determination of the objects or groups was determined on the basis of the received field strength of the received radio signal. In addition to the reception field strength, other signals or measured values can also be used as values proportional to the distance between the respective vehicles and the reference vehicle.

FIG. 3 shows a block diagram of the device for signaling local traffic disturbances according to a preferred exemplary embodiment.

In Figure 3, reference numeral 10 denotes a transmission or Receiving antenna, the reference numeral 20 a transmitting / Reception switch for separating the reception channel from the transmission channel, the reference symbol 30 a filter device with which the respective radio signals of the respective vehicles are filtered out according to their identification code, the reference symbol 40 a receiver and the reference symbol 50 a transmitter. The filter device 30 can also have a detector for detecting the reception field strength of the respective radio signal. The receiver 40 and the transmitter 50 are connected to a microprocessor 60, which takes over the control of the transmission / reception system. Reference numerals 90 to 140 show a multiplicity of detection devices which detect the respective vehicle data of the vehicle. Reference numeral 90 designates a detection device for detecting the use of a brake pedal. Reference numeral 100 designates a detection device that indicates a value Θ corresponding to an instantaneous steering angle. Numeral 110 denotes a detection device that represents the current speed value v of the vehicle. Reference numeral 120 designates a detection device which specifies an instantaneous acceleration or deceleration value v of the respective vehicle. In addition, the device according to FIG. 3 can have a compass 130, which indicates a direction signal DIR, which represents the current direction of travel of the respective vehicle. Furthermore, a GPS system (global positioning system) can be used which has an absolute position value POS for specifying an instantaneous absolute position. The detection devices 90 to 140 are connected, for example, to an input port of the microprocessor 60 and are either transmitted as vehicle data to the other vehicles via the transmitter 50 and the antenna 1 or used to compare the received vehicle data with the local vehicle data. Reference numeral 70 denotes a first storage device in which, for example, the table shown in FIG. 4 can be stored. The first memory device 70 preferably consists of a ring memory, the memory locations of which are repeatedly written at predetermined time intervals. This can ensure, for example, that the vehicle data last received in each case are stored in the first storage device 70.

In the event that fractal Darwinian object generation is used as a method for determining the relevant group of vehicles, the device for signaling local traffic disruptions also has a second storage device 80. The fractal hierarchical object library is then located in this second storage device 80.

The first storage device 70 and the second storage device 80 are connected to the microprocessor 60 via a bus system 170, which ensures data exchange. If, when evaluating the vehicle data, the microprocessor determines that the group behavior of its associated relevant group contradicts its own vehicle data, for example the speed of the relevant group is significantly lower than the speed of its associated vehicle, then signaling takes place either via the display device 150 or via a control device 160. The respective signal is displayed and / or audibly displayed in the display device 150, wherein the known symbols can preferably be used for a speed limit. In addition, there is the possibility that, for example, automatic emergency braking is initiated via the control device 160 if the evaluation of the received vehicle data with the local vehicle data results in an acute dangerous situation. Such an acute danger situation can also be transmitted to the other vehicles by an additional emergency signal which has a higher priority, as a result of which, for example, a mass collapse of vehicles can be prevented in a particularly effective manner. In order to ensure maximum spreading of the emergency signal, the receiver 40 has a threshold detector which only evaluates emergency signals below a certain reception field strength and emits them again via the microprocessor 60 and the transmitter 50, which results in a repeater function. In this case, the emergency signal, which is emitted again and intensified, has the same identity code as the vehicle which originally sent the emergency signal.

Since the repeater function enables an extremely long range to be achieved beyond the respective groups, each vehicle can carry out a relevance test for the received emergency signal. It is checked whether the vehicle that originally sent the emergency signal belongs to a group that cannot be relevant in any way for the respective vehicle. A repeater function would not take place in this case.

The ignition key preferably activates the transmitter and receiver of the respective vehicles. This means that the parked vehicles do not automatically belong to the relevant groups of vehicles.

Due to the limited transmission or reception range, a maximum group of vehicles has already been generated for each vehicle. However, this group can be expanded or restricted as required or according to the situation, for example by: ■ targeted expansion or limitation of the transmission and / or reception range;

Forwarding received information, i.e. Vehicle data (Since the information can be passed on again and again, an enormous range is conceivable.)

■ targeting a vehicle or group with a specific characteristic. This can be done by sending the identification codes of the vehicles to be addressed, in that a sending vehicle addresses the receivers with a certain property, such as all of its maximum group, which drive behind the respective vehicle (transmitter determines group directly), or by sending indirect information such as "To all vehicles that drive in the same direction as the reference vehicle" (recipient decides whether he is addressed).

■ Formation of sub-groups and / or super-groups, which each vehicle individually and again and again determines. Here, the super-group is formed by interpreting forwarded information: groups in the vicinity of the reference vehicle or close groups in the same direction of travel, one group representing all vehicles in the set reception area, and a sub-group, for example, all vehicles approaching the reference vehicle and its group, all Show vehicles of the group of the reference vehicle with the same direction of travel, all with similar driving behavior (eg speed), all vehicles that are behind or in front of the reference vehicle, etc. Subordinate subgroups are e.g. formed by all vehicles that are behind the reference vehicle and accelerate, etc.

■ Formation of sub-groups and / or super-groups, which develop dynamically according to predetermined rules (partly in consultation between the vehicles globally. The global segmentation (fractal hierarchical grouping) has the advantage that group speakers can be determined who exchange relevant information between the groups.

The following parameters can be determined in order to determine the information necessary for forming a group:

■ Determination of the relative distance (reference vehicle - other vehicle): by measuring the field strength; by analyzing the driving pattern over time (eg the vehicle in question always brakes one second in front of the reference vehicle. At a speed of ... this does ...; using a distance meter. ^β Determining the relative direction of travel of the vehicle from which the information was received: by measuring the increase or decrease in field strength; by measuring the Doppler effect (if relative position is determined); by analyzing the driving pattern over time; by receiving absolute directional data (e.g. compass) and comparing it with your own directional data (of the reference vehicle).

■ Determination of the relative position (in front of reference vehicle - behind reference vehicle): by measuring speed differences (reference vehicle - respective vehicle) and comparison with changes in distance. If the respective vehicle is faster than the reference vehicle and the respective vehicle is behind the reference vehicle, the distance between the respective vehicle and the reference vehicle must be smaller; by temporal analysis of the driving patterns (e.g. the respective vehicle usually brakes in front of the reference vehicle, i.e. it drives in front of the reference vehicle); by direction finder or receiver.

■ Determination of the lane (fast lane or wrong side of the motorway): by transmitter on the side of the road and comparison of the field strengths: wrong, right - left, right; through temporal analysis of driving patterns.

Furthermore, by limiting the reception or transmission range, in particular when using “burst” transmitters, the probability of simultaneous reception of different transmitters can be kept small. However, this procedure has the disadvantage that the number of information received could be too small.

Therefore, matching the transmitters can be more advantageous. This can be done by synchronizing or "group tuning" the transmitters. The synchronization can be done centrally, for example, using the radio clock signal.

According to a preferred exemplary embodiment, transmission takes place in defined transmission blocks. After each block there is a pause before the next vehicle can send. If there is a group, the transmitters can define the order of their transmission blocks among themselves. This can e.g. the order in which the broadcasters joined the group.

Groups that come too close to each other and interfere with each other can be "merged" with each other with regard to the transmission clock if they match (eg same direction of travel) and the group does not become too large. When merging, for example, the order can be kept within the original groups and the group, of which one of the members first proposed the fusion, be the first to be sent and then the second group. If the group would become too large as a result of a merger or if the two groups do not fit well together (eg oncoming traffic), you must still ensure that they do not transmit at the same time. This can be done using a "Zipper procedure" happen. This means that depending on how many groups meet, each of the groups increases the transmission pauses between the individual programs in such a way that the members of the other groups fit in between.

However, there is often a rather continuous flow of traffic that can be networked. Since not all vehicles in a large network can be synchronized with each other, groups have to be created artificially. This can be done using a fractal hierarchical method. Here, vehicles can be grouped, vehicles can be taken up by a group, groups can merge, group spokespersons can be determined, groups can be broken up and / or super-groups can be formed. When a broadcaster approaches a group, it can be integrated with its group (if there is one) by radioing its request to be included in the pauses in the transmission of the others.

Transmission pauses are not only necessary to enable group dynamics, but also to send a signal (emergency signal) with high priority (accident, full braking).

Another way of creating synchronization groups would result from a special pair synchronization:

Suppose there is a group that someone wants to join. Each newcomer first receives until he can assess the situation and then registers in a transmission pause. The order of all participants then shifts.

If the vehicle that entered the group in front of the reference vehicle has the transmission number n, the reference vehicle has the transmission number n plus 1. If n plus 1 is above a threshold value, the reference vehicle has number one, but with a phase shift of 180 degrees. The reference vehicle thus represents the first member of the second group. The reference vehicle then transmits into the enlarged transmission pauses of the vehicles traveling ahead. The transmitter behind the reference vehicle is then number 2 with a 180 degree phase. If the maximum number in the group of the reference vehicle has now been reached, it continues with number 1 and 0 degree phase of a third group. Third and first group now send synchronously. If they are far enough apart, they don't bother each other '.

Whenever groups should disturb each other, the "zipper procedure" takes effect.

In order to prevent neighboring groups from interfering too much, the transmission frequencies could also be shifted slightly instead of the phase shift of the transmission clocks described above, so that neighboring groups can no longer receive each other. So that information can still get from one group to another, speakers of the groups could be determined (e.g. the last vehicles entered), who then work on several frequencies at the same time.

Claims

Expectations

1. Method for signaling local traffic disturbances with the steps:

a) determining a maximum group of vehicles (1-12) belonging to a reference vehicle (0) by receiving at least one individual vehicle data signal, b) repeatedly evaluating the at least one individual vehicle data signal and storing them as individual vehicle data of the at least one vehicle (1 - 12) from the maximum group of vehicles (1-12); c) determining at least one group of vehicles (1-4) relevant to the reference vehicle (0) within the maximum group of vehicles (1-12) by evaluating the individual vehicle data; d) determining the group behavior of the at least one relevant group of vehicles (1-4) by evaluating the respective individual vehicle data; and e) signaling information corresponding to the group behavior of the at least one relevant group of vehicles (1-4).

2. The method according to claim 1, wherein the determination of the at least one relevant group of vehicles (1-4) is carried out by means of a method for fractally Darwinian object generation.

3. The method according to claim 2, wherein the method for fractal Darwinian object creation from the steps

a) preparing a fractal, hierarchical object library with predetermined objects and associated property, context and modification rules; b) formation of basic objects in a hierarchical object structure with subordinate and superordinate objects; c) Comparison of the basic objects with the objects of the fractal object library, the basic object formed in each case being classified as unknown if there is no corresponding object with the corresponding property rules in the object library, and the basic object with the property rule one or several local classification probability (s) are assigned if one or more corresponding object (s) is (are) present in the fractal object library; d) applying the context rules to the respective objects in order to form and calculate respective fractal classification probabilities; e) applying the modification rules to the respective objects to optimize the fractal classification probabilities; f) iteratively performing steps d) and e) to gradually improve the classification probabilities.

4. The method according to claim 1, wherein the maximum group of vehicles (1-12) associated with the reference vehicle (0) is determined by a maximum reception range of its receiver (40).

5. The method according to claim 4, wherein the maximum reception range is a variable range of the receiver, which is set as a function of a determined traffic density and / or a reception interference resulting from overlaps of the received vehicle data signals.

6. The method according to any one of claims 1 to 5, wherein the individual vehicle data an identification code (IC) for identifying a respective vehicle, a speed value (v) for specifying the current speed of the respective vehicle, and a distance parameter for specifying a distance between the reference vehicle (0) and the respective vehicles from the maximum group of vehicles (1-12).

7. The method according to claim 6, wherein the individual vehicle data furthermore a deceleration / acceleration value (v) for specifying an instantaneous deceleration / acceleration of the respective vehicle, and / or a steering angle (θ) for specifying an instantaneous steering angle of the respective vehicle, and / or a direction value (DIR) for indicating an instantaneous absolute direction of the respective vehicle, and / or a position value (POS) for indicating an instantaneous absolute position of the respective vehicle, and / or a brake signal value (BRAKE) for indicating an instantaneous use of one Braking device of the respective vehicle, and / or

Group behavior values for specifying the current group behavior of a group of vehicles to be considered belonging to the respective vehicle, and / or an emergency signal value for specifying an instantaneous emergency situation of the respective vehicle.

8. The method according to claim 7, wherein depending on a combination of predetermined individual vehicle data of a respective vehicle, the emergency signal value is generated, which is compared to the individual driving tool data has priority.

9. The method according to any one of claims 1 to 8, wherein depending on the signaled information in the reference vehicle (0) via a control device (160), a control of the vehicle is carried out.

10. The method according to claim 9, wherein the control is a motor control and / or a brake control.

11. Device for signaling local traffic disturbances with a detection device (90-140) for detecting the local vehicle data to be transmitted; a transceiver (10-50) for transmitting / receiving radio signals containing respective vehicle data to be transmitted / received; a field strength detection device (30-40) for detecting a respective field strength of the respectively received radio signals; a storage device (70) for storing the respectively received vehicle data as a maximum data group in dependence on an identity code (IC) which assigns each radio signal to its respective transmitting vehicle, a time value and the reception field strength of the respective radio signal; an evaluation device (60) for evaluating the data of the maximum data group, whereby at least one relevant data group is determined; a determining device (60) for determining a signal value depending on the data of the at least one relevant data group and the local vehicle data; and a signal device (150, 160) for signaling the determined signal value.

12. The device according to claim 11, with another Storage device (80) for storing a fractal hierarchical object library by means of which the at least one relevant data group is determined.

13. The device according to claim 11 or 12, wherein the detection device comprises a brake signal sensor (90), a steering lock sensor (100), a speed sensor (110), an acceleration / deceleration sensor (120), a direction sensor (130), a position sensor ( 140) and / or an emergency signal sensor.

14. Device according to one of the claims 11 to 13, wherein the detection device (90-140) has a group behavior value determination device which indicates the current group behavior of a relevant group of vehicles belonging to the respective vehicle.

15. Device according to one of the claims 10 to 13, wherein the signal device is a display device

(150), which represents the determined signal value audibly and / or visibly.

16. Device according to one of the claims 10 to 13, wherein the signal device is a control device

(160) that performs engine control and / or brake control.

17. Device according to one of the claims 10 to 16, wherein the transmitting / receiving device comprises a detector device which detects a received emergency signal and forwards a corresponding amplified emergency signal when the reception strength falls below a certain level.

18. The apparatus according to claim 17, wherein the received emergency signal is an emergency signal value and / or group has holding values of the vehicle emitting the emergency signal.

19. Device according to claim 18, with an emergency signal evaluation device which evaluates the group behavior values associated with the emergency signal and adds it to the emergency signal to be passed on.

20. Device according to claim 19, wherein the group behavior value associated with the emergency signal is a distance between the vehicle transmitting the emergency signal and the vehicle receiving the emergency signal, and the evaluation device adds up the respective distances to a total distance when the emergency signal is passed on.