EP2418632B1 - Procédé de réglage d'un dispositif de signal - Google Patents

Procédé de réglage d'un dispositif de signal Download PDF

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Publication number
EP2418632B1
EP2418632B1 EP11450097.8A EP11450097A EP2418632B1 EP 2418632 B1 EP2418632 B1 EP 2418632B1 EP 11450097 A EP11450097 A EP 11450097A EP 2418632 B1 EP2418632 B1 EP 2418632B1
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EP
European Patent Office
Prior art keywords
traffic
evaluation
parameters
evaluation criterion
intersection
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EP11450097.8A
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German (de)
English (en)
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EP2418632A1 (fr
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Andreas Kuhn
Birgit Kuhn
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/07—Controlling traffic signals
    • G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/095—Traffic lights
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled

Definitions

  • the invention relates to a method for controlling a signaling system of an intersection.
  • Known signal systems of an intersection serve to regulate the traffic flow of the intersection, wherein the signal system can preferably be designed for the formation of signals, in particular for the formation of light signals.
  • the signal system may comprise a signaling device, which signal device may display different signals as a function of manipulated variables.
  • Well-known examples of signal systems are traffic lights. There is known a scheme in which the signal system switches after predetermined fixed time increments. In the case of the traffic light, the green phases, the yellow phases and the red phases each have predetermined constant periods of time.
  • the DE 44 36 339 A1 describes a two-level traffic light control.
  • signals are first acquired from measured data by sensors using an analytically operating preprocessor, which are then evaluated in a downstream neural network.
  • the disadvantage here is that it can often lead to congestion in the known method, because not always best deals with any traffic situation and thus only sub-optimal solutions are achieved.
  • Another disadvantage is that vehicles and / or pedestrians, especially on side roads, often wait unnecessarily long for clearance to pass the intersection.
  • the object of the invention is to provide a method of the type mentioned, in which the known disadvantages are avoided, which can be easily integrated into the traffic control of an existing transport network, with a good control of the intersection can be reliably ensured for different requirements in which the required computing power and the required data transfer can be kept low, and which can ensure a reduction of pollutant emissions at the intersection.
  • the advantage here is that with the method varying specifications and control strategies can be considered according to the predetermined evaluation criterion. In this case, a good performance with respect to a clearly defined evaluation criterion can be ensured, which can be easily objectively checked. Furthermore, through An assessment of the appropriateness of the evaluation criterion is reviewed and if necessary, the evaluation criterion is changed. By selecting the evaluation criterion different strategies for the regulation of the intersection can be specified, whereby the strategy can be easily and quickly changed and adapted to the respective situation, whereby a change of the evaluation criterion is sufficient for the change of strategy. Furthermore, it is advantageous that the current traffic situation can be determined and evaluated with the method with little expenditure of computing power and data transfer, whereby a simple, local traffic model is sufficient.
  • control can be carried out substantially directly in the signal system, wherein in case of failure of the data transfer by means of external interfaces, the control can optionally be further regulated with the last transmitted data, so that despite the failure of a good flow control can be provided.
  • An advantage of the method is further that it can be easily integrated into the traffic control of an existing transport network, in particular by a gradual conversion or extension of existing traffic regulations can be realized in a simple manner that in the process, the required computing power can be kept low and only a small amount of data transfer is required.
  • the method has a low susceptibility to interference. Furthermore, by incorporating the evaluation criterion, for example, a reduction in pollutant emissions, in particular in the area of the intersection, can be ensured.
  • the invention further relates to a computer program product which can be loaded directly into the internal memory of a computer and comprises software code sections with which the steps of the method according to the claim or the subclaims are executed when the computer program product runs on a computer.
  • the Fig. 1 to 3 show embodiments of a method for controlling a signal system 1 an intersection, wherein at least one input parameter 10 is passed to a traffic device 2, the traffic device 2 first traffic parameters 31 of the current traffic situation are determined, at least one assessment criterion 4 is given, the first traffic parameters 31 and at least an evaluation criterion 4 of a rating device 6 are passed, are determined by the evaluation device 6 manipulated variables 7 and the signal system 1 is operated with the manipulated variables 7.
  • An advantage of the method is that it can be easily integrated into the traffic control of an existing transport network, in particular by also a gradual conversion or extension of existing traffic regulations is easily feasible. In this case, controlled variables of the existing traffic regulation can be integrated into the process by means of the evaluation criterion 4. Furthermore, it is advantageous that in the method, the required computing power can be kept low and only a small data transfer is required that it has a low susceptibility, and that the inclusion of the evaluation criterion 4, a reduction of pollutant emissions, such as CO2 emissions, in particular along main roads.
  • intersection is a traffic intersection where at least two roads meet. At the intersection, more than two roads can meet. Another embodiment of the intersection relates to a roundabout.
  • the method essentially relates only to the regulation of the intersection, wherein the evaluation criterion 4 can be handed over, at least partially, from a hierarchically superordinated method.
  • the hierarchically superordinated method preferably relates to a cross-hierarchically superior element of a traffic network, for example, a street.
  • a data transfer can take place with a hierarchically higher-order method.
  • the signal system 1 may be provided for traffic control of pedestrian and / or vehicle traffic at the intersection, the traffic is controlled by the signal system 1.
  • the intersection is a controlled intersection and the signal system 1 indicates by means of signals whether passing in a predetermined manner, for example a crossing or a turn is currently permitted or not.
  • the signal system 1 may comprise a traffic signal system, wherein the signals are at least partially light signals.
  • the traffic signal system can be designed in particular as a traffic light.
  • the traffic light may include at least one green, at least one yellow and at least one red light signal to indicate whether or not the passage is permitted in the predetermined manner.
  • signaling system 1 comprises optical displays, for example information boards, and / or sounders, such as loudspeakers or sirens.
  • the signaling system 1 comprises a transmitting unit.
  • signals can be transmitted to the road users and / or vehicles, wherein the transmission can be carried out by means of radio, WLAN, TMC or other types of information transmission.
  • the duration can be transmitted to the next green.
  • Pedestrians can receive these signals by means of suitable receivers, for example mobile telephones or the like. In vehicles immediately suitable receiving devices can be integrated.
  • the traffic situation at the intersection is determined by means of a traffic model, wherein the traffic facility 2 determines the first traffic parameters 31 as a function of the at least one input parameter 10.
  • an analytical representation of the traffic model of the traffic facility 2 can be provided. Often, however, such a representation is not appropriate.
  • Machine learning models may be, for example, artificial neural networks, regression or classification trees, support vector machines and / or look-up tables and / or committees of machine-learning models.
  • the input parameters 10 may be different sizes and may be, for example, traffic flows measured at the intersection by means of sensors.
  • other traffic data can be used, for example, sensors at other traffic points, which correlate with the traffic situation at the intersection.
  • the traffic situation can also be determined indirectly, for example by measuring pollutant emissions.
  • the input parameters 10 may include traffic parameter dependent values which depend directly on the traffic, for example a traffic density. Furthermore, the input parameters 10 may include traffic parameter independent values that are not traffic dependent. However, this does not exclude that the traffic parameters 31 depend on these values. Traffic parameter independent values are, for example, the day of the week.
  • the input parameters 10 may include weather data and / or calendar data.
  • weather data for example, the commuter traffic, the tourist traffic at the beginning of the holiday and / or in bad weather can be easily taken into account.
  • the input parameters 10 may include data about events, such as sporting events, trade fairs or concerts, which may also take into account typical traffic at major events.
  • the traffic parameters 31 are determined from input parameters 10 which do not directly relate to the traffic parameters 31 or comprise only a part of the traffic parameters 31.
  • the above-mentioned examples of the input parameters 10 show that it has not proved necessary to provide input parameters 10 from which the traffic parameters 31 can be determined analytically. In this way, the measurement effort at the intersection can be kept low and still get a good picture of the traffic situation.
  • the input parameters 10 preferably comprise at least one currently measured variable, this variable being different from the traffic parameters 31.
  • This currently measured variable can include, in particular, weather data, time information and / or pollutant emissions.
  • the current traffic situation can be described, for example, by the inflows and the turning rates of the feeder roads of the intersection, wherein these variables can be provided as first traffic parameters 31.
  • the first traffic parameters 31 can also reflect other values, whereby the inflows and the turning rates of the feeder roads of the intersection can also be determined with these first traffic parameters 31.
  • the drains can be selected.
  • a particularly simple traffic model of the traffic facility 2 describes, depending on a time and a day, the average traffic flows at the intersection. At least the time and the day are then transmitted to the traffic facility 2 as the input parameter 10, the traffic facility 2 determining the corresponding first traffic parameters 31 and transmitting them to the evaluation facility 6.
  • rush hour traffic, morning and evening peaks in traffic volume, in particular one-way peaks in traffic volume can be taken into account.
  • history values of the intersection can be used for the traffic model.
  • the accuracy of this particularly simple traffic model of the traffic facility 2 can be increased and better adapted to the intersection to be imaged by means of the traffic model.
  • at least one other or at least one further input parameter 10 can be selected becomes.
  • the at least one input parameter 10 includes information about the current weather. In this way, rain, snow, sun and the like can be taken into account in the traffic model, whereby the average driving speed, the accident frequency and / or the braking distance of the road users can be taken into account.
  • the weather data can be transmitted by data transfer to the traffic facility 2. In this case, the weather data can be determined, for example, directly at the signal system 1 or taken over by prediction stations.
  • the crossing vehicles and / or pedestrians For example, at least one of the at least one input parameter 10 can be formed, with which the actual traffic volume can be determined directly.
  • the vehicles driving along the traffic lane to the intersection can relate to at least one of the at least one input parameter 10, with which the actual traffic volume can likewise be determined directly.
  • a plurality of input parameters 10 of the traffic device 2 can be transferred, with which a good determination of the current traffic situation can be provided by the traffic device 2.
  • the at least one input parameter 10 can comprise a large number of different variables and can be represented as a multi-dimensional vector.
  • traffic parameters 32 of the future traffic situation are predicted by the traffic facility 2 and the second traffic parameters 32 are transferred to the assessment facility 6, as in FIGS Fig. 2 and 3 is shown.
  • the advantage here is that thereby the expected future traffic situation, for example by 15 minutes, by 30 minutes and / or directed by 60 minutes into the future, can be taken into account, whereby the signal system 1 can also be regulated in view of the expected future traffic situation. In this case, expected changes in the traffic situation can be handled better by the intersection.
  • the second traffic parameters 32, together with the first traffic parameters 31, can form a multi-dimensional traffic parameter vector.
  • traffic-parameter-dependent values and / or traffic-parameter-independent values of the input parameters 10 can be used. It has been found that the accuracy of the second traffic parameters 32 can be improved considerably, in particular by including values which are independent of traffic parameters. In particular, events or weather-dependent peculiarities can be easily taken into account.
  • At least one evaluation criterion 4 is specified in the method.
  • the evaluation criterion 4 can be predetermined, at least in part, by a hierarchically higher-ranking control system. As a result, the method can be easily integrated into the higher-level method of the hierarchically higher-level control system, wherein the control takes place locally at the intersection and only from the higher-level control system a part of the evaluation criterion 4 is given. As a result, the data transfer can be kept low and local conditions at the intersection are easily taken into account.
  • the hierarchically higher-level control system preferably relates to a cross-hierarchically superior element of a traffic network, such as a street.
  • the evaluation criterion 4 can be a scalar or a vector variable.
  • a vectorial evaluation criterion 4 can also be provided as a scalar function or the like. In other embodiments, other embodiments of the evaluation criterion 4 may be provided, for example in the form of a matrix and / or several evaluation criteria. 4
  • evaluation criterion 4 can be provided that a first part is assigned a significantly higher weight compared to a second part, whereby this first part in this sense can represent a mandatory criterion to be met.
  • a mandatory criterion may be provided in particular for the fulfillment of legal requirements.
  • the manipulated variables 7 are determined by the evaluation device 6 by means of a control model and / or a rating model.
  • the input parameters 10 and manipulated variables 7 are assigned a rating, taking into account the evaluation criterion 4.
  • other parameters in particular by feedback, can be provided in other embodiments.
  • the rule model is the inverse evaluation model that assigns a manipulated variable 7 to the input parameters 10, taking account of the evaluation criterion 4, so that the evaluation satisfies predefined conditions.
  • the evaluation device 6 can assign a higher priority to the fulfillment of the mandatory criteria.
  • statutory requirements for example a minimum duration of the individual signal phases of the signals displayed by the signal system 1, for example, in each case the green, the yellow and the red phase, can be taken into account very simply. This can be achieved, for example, by excluding those manipulated variables 7, by means of which the mandatory criteria is not met, from the evaluation device 6 and thus can not be output by the evaluation device 6. This can also be achieved be evaluated by those manipulated variables 7, by means of which the mandatory criteria are not met, so that these manipulated variables 7 are not determined by the evaluation device 6 as those manipulated variables 7, which have the highest degree of fulfillment.
  • the best possible fulfillment can be provided.
  • an optimization problem can be solved by the evaluation device 6.
  • a first part of the evaluation criterion 4 specified as a must criterion can essentially be regarded as a secondary condition for the optimization problem, which is mandatory.
  • the signal system is operated with a predefinable standard set of manipulated variables 7, as long as the evaluation criterion 4 is met with the standard set of manipulated variables and only then a change in the manipulated variables 7 occurs when the evaluation criterion 4 is no longer satisfied, or Non-compliance threatens.
  • a plurality of standard sets of manipulated variables 7 are predetermined and is changed in a first step from a standard sentence to another standard sentence. For example, it can be provided that in a crossing of a main road and a side street in a first standard sentence, the two streets are treated the same, which can be ensured even in the side street low downtime due to the duration of the red phases.
  • the green phase of the main road can be extended and the red phase of the main road can be shortened.
  • the red phase and shortens the green phase As a result, it is also possible to work with a predetermined second standard rate at a higher flow level of the main road.
  • the standard set can be easily provided that on a road a green wave is ensured. If, in the case of regulation with a standard sentence, the evaluation criterion 4 is no longer met, for example because of a traffic jam, it is usually no longer expedient to follow the concept of the green wave, since vehicles will no longer reach the next intersection within the scheduled time.
  • the manipulated variables 7 are determined independently of the standard sentences.
  • the at least one evaluation criterion 4 relates to at least one condition which is to be fulfilled by the method as much as possible.
  • the evaluation criterion 4 is, for example, a signal duration of an enable signal, in particular the green phase, a signal duration of the stop signal, in particular the red phase, a minimum crossing reserve for one or more predetermined permissible types of passing the intersection, a drain in a predetermined direction, a maximum tailback length along a given feeder road, may relate.
  • the evaluation criterion 4 may include, in particular, a predefinable setpoint, an extemal condition, or compliance with a threshold.
  • the evaluation criterion 4 makes it possible to compare different manipulated variables 7 with regard to the suitability for achieving the strategy prescribed by the evaluation criterion 4 of a traffic situation predefined by the first traffic parameters 31 and possibly the second traffic parameters 32.
  • the crossing reserve indicates which increase of the inflow can be handled without congestion from the intersection.
  • a degree of saturation of the intersection may be determined that is substantially equal to 100% less of the intersection reserve.
  • the evaluation device 6 determines those manipulated variables 7 which satisfy the evaluation criterion 4, taking into account the first traffic parameters 31 and possibly the second traffic parameters 32.
  • evaluation criteria 4 can be transferred as a multi-dimensional evaluation criteria vector. With the evaluation criterion 4 different goals can be given in this way at the same time, which can be partly contradictory.
  • a weighting of the individual evaluation criteria 4 may be provided, which may be part of the evaluation criteria 4. It can also be provided that at least part of the weighting is implemented in the evaluation device 6, for example by the order of the evaluation criteria 4.
  • the at least one evaluation criterion 4 can be specified directly by a higher-level entity or can also be predetermined in the long term. It can also be provided a long-term specification, which can be changed immediately.
  • the higher-level entity preferably relates to a cross-hierarchically superior element of a traffic network, for example a street.
  • the variables which are input variables for the evaluation device 6 are evaluated in order to determine those manipulated variables 7 by means of this evaluation, by means of which manipulated variables 7 the signal system 1 is operated by the manipulated variables 7 the signals , Specify in particular the duration and / or the order of the individual signal phases, the signal system 1.
  • the evaluation criterion 4 can be a mandatory criterion, for example, the signal minimum duration of the enable signal to meet regulated, in particular legally regulated, specifications.
  • a regulated specification can, for example, be the green phase of a pedestrian traffic light that is sufficiently long in accordance with the road width.
  • the evaluation criterion 4 on the one hand pretend that the green phase of the pedestrian traffic is at least 40 seconds long, and further pretend that the saturation of the intersection is maximum, that is below, 90%.
  • further evaluation criteria 4 can be specified in this sense, whereby these specifications can be variable in time.
  • the evaluation criterion 4 and the first traffic parameters 31 form input variables for the evaluation device 6. If the traffic device 2 supplies second traffic parameters 32, the second traffic parameters 32 can also be other input variables of the evaluation device 6. In the case of particularly simple control models and / or evaluation models of the evaluation device 6, an analytical representation can be provided, which however often does not prove to be expedient.
  • Machine learning models and / or pattern recognition models in which the models can be trained on the basis of examples, and in this way, even in the case of complex systems, have proven to be favorable for a fast and good determination of the control model and / or evaluation model the manipulated variables 7 can be achieved.
  • the machine learning models can be in particular artificial neural networks, regression or classification trees, support vector machines and / or look-up tables and / or committees of machine-learning models ,
  • the traffic model, the control model and / or the evaluation model are preferably designed as independent modules, which are coupled to one another by means of interfaces.
  • the interfaces can also form feedback.
  • the individual models can be designed and trained in a particularly simple way. In particular, each module can be easily optimized for its specific task.
  • the first traffic parameters 31 and / or the second traffic parameters 32 are transmitted by the traffic device 2 to a judging device 8 and at least partially the at least one assessment criterion 4 is determined by the judging device 8.
  • the traffic situation can be assessed by means of a rating model and the evaluation criterion 4 can be adapted to the traffic situation.
  • the assessment device 8 further comprises, in addition to the assessment model, a selection model for specifying the evaluation criterion 4. In other embodiments, it may be provided that the assessment model and the selection model are combined in the assessment model.
  • the method is coupled with a hierarchically higher-order method, it can be provided that instructions are transferred from the hierarchically superordinated method to the assessment device 8 and are taken into account by the latter when determining the evaluation criterion 4.
  • the instructions can directly represent part of the evaluation criterion 4.
  • first traffic parameters 31 and / or second traffic parameters 32 can be taken into account.
  • an analytical representation of the assessment model and / or the selection model of the traffic facility 2 can be provided. Often, however, such a representation is not appropriate.
  • Machine learning models and / or pattern recognition models have proven to be favorable, in which the models can be trained on the basis of examples and in this way a fast and good determination of the evaluation criterion 4 can be achieved even with complex systems.
  • Machine learning models can be, for example, artificial neural networks, regression or classification trees, support vector machines and / or look-up tables.
  • the assessment model and / or the selection model are preferably designed as separate modules with respect to the traffic model, the control model and / or the evaluation model, which are coupled to one another by means of interfaces.
  • the interfaces can also form feedback.
  • the individual models can be particularly easily designed and trained. In particular, each module can be easily optimized for its specific task.
  • the morning commuter traffic can be city-centered, with a second out-of-town commuter traffic outbound, with a third strategy of tourist traffic, with a fourth strategy the particulate matter pollution or the concentration of other pollutants and with a fifth strategy the traffic to or from an event be specially taken into account.
  • the strategy can be easily and quickly adapted to the current situation.
  • a quick strategy change for short-term events is possible. For example, by detecting the position of a given vehicle, a fast progress of this vehicle can be ensured, whereby a route change of the vehicle can be easily taken into account.
  • the progress of emergency vehicles and / or public transport vehicles can be substantially improved.
  • the evaluation criterion 4 can also be provided to specify the evaluation criterion 4 via an external input interface, wherein only a part of the evaluation criterion 4 can be specified. It can be provided that the external input interface is connected to an input of the assessment device 8 and the assessment device 8, taking into account the specifications of the external input interface determines the evaluation criterion 4 and passes it to the evaluation device 6. It can also be provided that the external input interface is directly connected to an input of the evaluation device 6, whereby, if appropriate, the selection of an arbitrary strategy for controlling the intersection is simply made possible.
  • a manual input from a police officer at the intersection can be input via the external input interface, whereby manual control of the intersection can be easily made possible by selecting the evaluation criterion 4.
  • the strategy for the regulation of the intersection can simply be specified.
  • the inflows and turning rates of the feeder roads of the intersection can be determined with the first traffic parameters 31, wherein the inflows and the turning rates of the feeder roads of the intersection can be parameters which characterize the first traffic parameters 31.
  • the first traffic parameters 31 can directly indicate a numerical value for the inflows and bends of the feeder roads of the intersection.
  • the examples for training the traffic model can be determined separately in advance. In this case, over a predeterminable period, for example at least two months, measurements carried out at the intersection can be used.
  • the examples for training the control model and / or the evaluation model can be determined by preliminary simulations, for example by Monte Carlo simulations, wherein the best control variables 7 are determined for selected evaluation criteria 4, first traffic parameters 31 and possibly second traffic parameters 32.
  • the examples for training the assessment model and / or the selection model can also be determined by preliminary simulations, for example by Monte Carlo simulations.
  • the evaluation device 6 and, if appropriate, the assessment device 8, these can be designed differently.
  • the examples used for training can be obtained in different ways, whereby the traffic model of the traffic device 2 and / or the control model and / or the evaluation model of the evaluation device 6 and / or the assessment model and / or the selection model of the assessment device can be kept simple.
  • a further advantage is that the evaluation criterion 4 can be targeted to the traffic situation and the data of the traffic situation, the first traffic parameters 31 and / or the second traffic parameters need not be present as measured input parameters but are provided by the traffic facility 2 by means of the traffic model.
  • the required measurement effort during operation can be kept low and, for example, empirically determined empirical values can be used which, if necessary, can be confirmed or adapted by only a small amount of measurement.
  • the current traffic situation can be determined easily and with little need for computing power and data transfer. In this way, the regulation of the signal system 1 of the intersection can be ensured in a simple and resource-saving manner adaptable to a wide variety of local and regional traffic situations.
  • the traffic model and / or the control model and / or the evaluation model and / or the assessment model and / or the selection model may be designed to be adaptive.
  • the advantage here is that the accuracy of the models can be improved during operation.
  • the respective model is improved starting from an initial configuration offline in training phases and / or online during operation, in particular by means of known methods, for example an evolution method.
  • offline training phases can be provided before operation and / or during operation during breaks or parallel to the operation.
  • the outputs of the devices (2, 6, 8) are fed back to the inputs of other of the devices (2, 6, 8), whereby the accuracy of the corresponding models can be increased.
  • the manipulated variables 7 have an immediate effect on the second traffic parameters 32.
  • the influence of the evaluation criterion 4 on the second traffic parameters 32 increases, in particular for longer forecasts.
  • the input parameter 10 of the traffic facility can comprise at least one of the manipulated variables 7, wherein it can also be provided that the input parameter 10 comprises all manipulated variables 7.
  • the fulfillment of the strategy specifications can be determined prematurely and a particularly early adaptation of the strategy can take place by changing the evaluation criterion 4.
  • the feedback can easily provide a constant training of the models, whereby a steady adaptation of the models and a continuous improvement of the control of the intersection can be achieved.
  • the at least one input parameter 10 is at least partially determined by means of a sensor 11 in the region of the intersection.
  • the sensor 11 can be attached directly to a signaling device of the signal system 1, as shown schematically in FIG Fig. 4 is shown, and / or may be arranged spaced from the signaling device of the signal system 1, for example, be arranged below the roadway of one or more feeder roads, as also shown schematically in FIG Fig. 4 is shown.
  • the signaling device is designed to reproduce the signals dependent on the manipulated variables.
  • the signal device can be designed in particular as a light signal device 12 for the reproduction of light signals, with which the signal system 1 can be designed as a traffic light.
  • the sensor 11 may be configured to determine the current weather, the tributary tributary tributaries of the intersection, the backwater on the feeder roads of the intersection, and / or accidents at the intersection and in the vicinity around the intersection.
  • the sensor 11 may comprise induction loops, temperature sensors, light barriers, magnetic sensors, image sensors, for example video sensors, laser scanners, and / or radar sensors.
  • the at least one evaluation criterion 4 is predetermined at least partially by means of an external input interface, preferably by a manual input device or by a hierarchically higher-order control system.
  • the advantage here is that the evaluation criterion 4 can be changed from a distance so that the traffic flow at the intersection can be controlled externally or at least partially synchronized with neighboring further signaling systems, for example by a hierarchically superior method.
  • the advantage here is that only small amounts of data have to be transmitted, since the method can continue to operate autonomously, at least as far as possible, or that pollutant emissions along main traffic routes can be reduced by optimizing the flow of traffic beyond the intersection.
  • feedback from the evaluation device 6 is transmitted to an external output interface, preferably to a display device or the hierarchically higher-order control system. It is advantageous in this case that the mode of operation of the signal system 1 can be easily controlled and / or the method for controlling a further signal system 1 of another intersection can be influenced by the feedback.
  • a further advantage is that only small amounts of data are to be transmitted, since the feedback usually causes small amounts of data.
  • the traffic device 2, the evaluation device 6 and optionally the assessment device 8 can be arranged in a common housing, whereby a particularly compact design can be provided. It can also be provided that a computer comprises several or even all of the devices 2, 6, 8.
  • the invention further relates to a computer program product which can be loaded directly into the internal memory of a computer and comprises software code sections with which the steps of the above method are executed when the computer program product runs on a computer.
  • the computer program product can be stored on a data medium.
  • the associated output parameters can be stored on individual worksheets and the current output parameters can be interpolated based on the current input parameters 10.
  • traffic situations for given input parameters 10 can be stored on individual tables and the first traffic parameters 31 can be interpolated on the basis of the current input parameters 10.

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Claims (10)

  1. Procédé pour la régulation d'une installation de signalisation (1) à un croisement, dans lequel
    - au moins un paramètre d'entrée (10) est transmis à une installation de circulation (2) déterminant des premiers paramètres de circulation (31) ;
    - l'installation de circulation (2) détermine, à l'aide d'un modèle d'apprentissage automatique et/ou d'un modèle de reconnaissance des formes, des premiers paramètres de circulation (31) de la situation de circulation actuelle en fonction de l'au moins un paramètre d'entrée (10) ;
    - au moins un critère d'évaluation (4) est prédéterminé ;
    - les premiers paramètres de circulation (31) et l'au moins un critère d'évaluation (4) sont transmis à une installation d'évaluation (6) ;
    - l'installation d'évaluation (6) détermine des grandeurs de réglage (7) à l'aide d'un modèle d'apprentissage automatique et/ou d'un modèle de reconnaissance des formes, en fonction des premiers paramètres de circulation (31) et de l'au moins un critère d'évaluation (4) et
    - l'installation de signalisation (1) est pilotée avec les grandeurs de réglage (7).
  2. Procédé selon la revendication 1, caractérisé en ce que l'installation de circulation (2) pronostique des deuxièmes paramètres de circulation (32) de la situation de circulation future et transmet les deuxièmes paramètres de circulation à l'installation d'évaluation.
  3. Procédé selon la revendication 1 ou 2, caractérisé en ce que les entrées et les taux de changement de direction des voies entrant dans le croisement sont déterminées avec les premiers paramètres de circulation (31).
  4. Procédé selon la revendication 2 ou 3, caractérisé en ce que l'installation de circulation (2) transmet les premiers paramètres de circulation (31) et/ou les deuxièmes paramètres de circulation (32) à une installation d'interprétation (8) et l'installation d'interprétation (8) détermine au moins en partie l'au moins un critère d'évaluation (4).
  5. Procédé selon la revendication 4, caractérisé en ce que l'installation de circulation (2) et/ou l'installation d'évaluation (6) et/ou l'installation d'interprétation (8) sont adaptatives.
  6. Procédé selon la revendication 4 ou 5, caractérisé en ce que l'installation d'interprétation (8) comprend un modèle d'apprentissage automatique et/ou un modèle de reconnaissance des formes.
  7. Procédé selon l'une des revendications 1 à 6, caractérisé en ce que l'au moins un paramètre d'entrée (10) est déterminé au moins en partie au moyen d'un capteur (11) situé dans la zone du croisement.
  8. Procédé selon l'une des revendications 1 à 7, caractérisé en ce que l'au moins un critère d'évaluation (4) est au moins en partie prédéterminé au moyen d'une interface d'entrée externe, de préférence d'un appareil de saisie manuel ou d'un système de régulation d'un niveau hiérarchique supérieur.
  9. Procédé selon l'une des revendications 1 à 8, caractérisé en ce que l'installation d'évaluation (6) transmet une rétrosignalisation à une interface de sortie externe, de préférence à une installation d'affichage ou au système de régulation d'un niveau hiérarchique supérieur.
  10. Programme pour ordinateur qui peut être chargé directement dans la mémoire interne d'un ordinateur et qui comprend des segments de code de logiciel avec lesquels les étapes du procédé selon l'une des revendications 1 à 9 peuvent être réalisées quand le programme pour ordinateur est exécuté sur un ordinateur.
EP11450097.8A 2010-07-29 2011-07-29 Procédé de réglage d'un dispositif de signal Active EP2418632B1 (fr)

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EP3176768A1 (fr) * 2015-12-02 2017-06-07 Siemens Aktiengesellschaft Procédé de transformation d'une commande de commutation en une position de signal d'un groupe de signaux
DE102020204979A1 (de) 2020-04-20 2021-10-21 Siemens Aktiengesellschaft Verfahren und Vorrichtung zur Verkehrssteuerung
DE102020211698A1 (de) 2020-09-18 2022-03-24 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren zum Steuern eines Verkehrsflusses

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WO2001018767A1 (fr) * 1999-09-02 2001-03-15 Siemens Aktiengesellschaft Dispositif de commande pour carrefour echantillon de circulation

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DE4436339A1 (de) * 1994-10-11 1996-04-18 Ifu Gmbh Verfahren zur verkehrsadaptiven Steuerung einer Verkehrsampelanlage
DE19521927C2 (de) * 1995-06-09 1998-08-06 Inst Automation Und Kommunikat Verfahren und Vorrichtung zur verkehrsabhängigen Grünzeitanpassung in einer Verkehrssignalanlage
JP3399421B2 (ja) * 1999-11-05 2003-04-21 住友電気工業株式会社 交通信号制御装置
US6587778B2 (en) * 1999-12-17 2003-07-01 Itt Manufacturing Enterprises, Inc. Generalized adaptive signal control method and system
DE10241706B4 (de) * 2002-09-09 2006-03-23 Siemens Ag Verfahren zum Steuern des Verkehrs an einem Knotenpunkt eines Straßennetzes
DE102008050822A1 (de) * 2008-10-08 2010-04-15 Gevas Software Systementwicklung Und Verkehrsinformatik Gmbh Verkehrsadaptive Netzsteuerung und Verfahren zur Optimierung der Steuerungsparameter

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