Method and device for signalling local traffic delays
First Claim
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1. A method for signalling local traffic disturbances, comprising the steps of:
- determining a maximum group of vehicles to be examined associated with a reference vehicle through reception of at least one individual vehicle data signal;
repeatedly evaluating the at least one individual vehicle data signal and storing as individual vehicle data of at least one vehicle from among the maximum group of vehicles to be examined;
determining at least one group of vehicles having relevance for the reference vehicle within the maximum group of vehicles to be examined by evaluating the individual vehicle data by fractal-darwinian object generation;
determining a group behavior of the at least one relevant group of vehicles by evaluating the respective individual vehicle data of vehicles within the relevant group of vehicles; and
signalling information corresponding to the group behavior of the at least one relevant group of vehicles;
wherein relevant information is passed on to other vehicles or groups of vehicles.
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Abstract
A method and an apparatus for signalling local traffic disturbances wherein a decentralised communication between vehicles is performed by exchanging their respective vehicle data. Through repeated evaluation of these individual vehicle data, each reference vehicle may determine a group of vehicles having relevance for itself from within a maximum group of vehicles and compare the group behavior of the relevant group with its own behavior. The results of this comparison are indicated in the reference vehicle, whereby a homogeneous flow of traffic may be generated, and the occurrence of accidents is reduced.
42 Citations
18 Claims
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1. A method for signalling local traffic disturbances, comprising the steps of:
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determining a maximum group of vehicles to be examined associated with a reference vehicle through reception of at least one individual vehicle data signal;
repeatedly evaluating the at least one individual vehicle data signal and storing as individual vehicle data of at least one vehicle from among the maximum group of vehicles to be examined;
determining at least one group of vehicles having relevance for the reference vehicle within the maximum group of vehicles to be examined by evaluating the individual vehicle data by fractal-darwinian object generation;
determining a group behavior of the at least one relevant group of vehicles by evaluating the respective individual vehicle data of vehicles within the relevant group of vehicles; and
signalling information corresponding to the group behavior of the at least one relevant group of vehicles;
wherein relevant information is passed on to other vehicles or groups of vehicles. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
preparing a fractal, hierarchical object library with predetermined objects and related property, context and modification rules;
forming basic objects in a hierarchical object structure including subordinate and superordinate objects;
comparing the basic objects with the objects of the fractal, hierarchical object library, wherein a respectively formed basic object is evaluated to be unknown if no corresponding object having the corresponding property rules exists in the fractal, hierarchical object library, a local classification likelihood is allocated to the respective formed basic object having the property rule if a corresponding object exists in the fractal, hierarchical object library, or several local classification likelihoods are allocated to the basic object having said property rule if several corresponding objects exist in said fractal, hierarchical object library;
applying said context rules to the respective objects in order to form and calculate respective fractal classification likelihoods;
applying said modification rules to the respective objects in order to optimize the fractal classification likelihoods; and
iteratively executing the steps of applying the context rules and the modification rules for stepwise improvement of the fractal classification likelihoods.
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3. The method according to claim 1, wherein the maximum group of vehicles to be examined and associated with the reference vehicle is determined through a maximum reception range of its receiver.
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4. The method according to claim 3, wherein the maximum reception range is a variable range of the receiver which is set in dependence on at least one of a determined traffic density and a reception disturbance resulting from overlap of the received vehicle data signals.
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5. The method according to claim 1, wherein the individual vehicle data include:
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an identification code for identifying a respective vehicle;
a velocity value for indicating the current speed of the respective vehicle; and
a distance parameter for indicating a distance between the reference vehicle and the respective vehicles from among the maximum group of vehicles.
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6. The method according to claim 5, wherein the individual vehicle data include at least one of:
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a deceleration/acceleration value for indicating a current deceleration/acceleration of the respective vehicle;
a steering angle for indicating a current steering angle of the respective vehicle;
a direction value for indicating a current absolute direction of the respective vehicle;
a position value for indicating a current absolute position of the respective vehicle;
a brake signal value for indicating a current use of a brake device of the respective vehicle;
group behavior values for indicating the current group behavior of a group of vehicles to be examined and associated with the respective vehicle;
an emergency signal value for indicating a current emergency situation of the respective vehicle.
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7. The method according to claim 6, wherein in accordance with a combination of predetermined individual vehicle data of a respective vehicle, the emergency signal having priority over the individual vehicle data value is generated.
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8. The method according to claim 1, wherein depending on the signalled information, vehicle control is performed in the reference vehicle by a control device.
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9. The method according to claim 8, wherein the control is at least one of an engine control and a brake control.
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10. Apparatus for signalling local traffic disturbances, including:
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detection means for detecting local vehicle data to be transmitted;
a transmitting/receiving device for transmitting/receiving radio signals containing respective vehicle data to be transmitted/received;
a field strength detection means for detecting a respective field strength of the respective received radio signals;
first memory means for storing the respective received vehicle data as a maximum data group to be examined in accordance with an identity code allocating each radio signal to its respective transmitting vehicle, a time value, and the reception field strength of the respective radio signal;
second memory means for storing a fractal, hierarchical object library;
an evaluation device for evaluating the data of a maximum data group to be examined, using a fractal darwinian object library to perform fractal-darwinian object evaluation wherein at least one relevant data group is determined;
a determining device for determining a signal value in accordance with the data of the at least one relevant data group and the local vehicle data; and
signalling means for signalling the determined signal value, a field strength detection means for detecting a respective field strength of the respective received radio signals;
memory means for storing the respective received vehicle data as the maximum data group to be examined in accordance with an identity code allocating each radio signal to its respective transmitting vehicle, a time value, and the reception field strength of the respective radio signal, wherein relevant information is passed on to other vehicles or groups of vehicles. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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Specification