EP2413302B1 - Procédé de réglage de la circulation d'un tramway - Google Patents

Procédé de réglage de la circulation d'un tramway Download PDF

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Publication number
EP2413302B1
EP2413302B1 EP11450096.0A EP11450096A EP2413302B1 EP 2413302 B1 EP2413302 B1 EP 2413302B1 EP 11450096 A EP11450096 A EP 11450096A EP 2413302 B1 EP2413302 B1 EP 2413302B1
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Prior art keywords
traffic
evaluation
parameters
model
evaluation criterion
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EP11450096.0A
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German (de)
English (en)
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EP2413302A1 (fr
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Andreas Kuhn
Birgit Kuhn
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KUHN, ANDREAS
KUHN, BIRGIT
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Individual
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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
    • G08G1/081—Plural intersections under common control
    • 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
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions

Definitions

  • the invention relates to a method for regulating the traffic of a road with several intersections, wherein at least two of the intersections signal systems are assigned, according to the preamble of claim 1.
  • Known signal systems of an intersection serve to regulate the traffic flow of the intersection, wherein the signal systems can preferably be designed to form signals, in particular for the formation of light signals.
  • the signal systems may comprise a signal device, which signaling device may display different signals as a function of manipulated variables.
  • Well-known examples of signal systems are traffic lights. It is known to switch the signal systems after predetermined fixed time intervals. In the course of a road are usually several intersections, which signaling systems are assigned. The traffic flow in the street can be improved by the coordination of the signal systems of the individual intersections. For example, it can be achieved that when driving at a predetermined speed all signal systems are reached when they are switched to transit. This is often called a green wave.
  • the DE 44 36 339 A1 describes a two-stage Ampei horrung.
  • 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.
  • the disadvantage here is further that vehicles and / or pedestrians, especially on side roads, often wait unnecessarily long for clearance for passing the road and / or entering the street.
  • 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 regulation of the road for different requirements can be reliably ensured 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. This can be a good performance with respect to a clearly defined evaluation criterion be ensured, which can be easily checked objectively. Furthermore, an assessment can be used to check the appropriateness of the evaluation criterion and, if necessary the evaluation criterion will be changed. Through the selection of the evaluation criterion different strategies for the regulation of the road can be specified, whereby the strategy can be changed easily and quickly and adapted to the respective situation, whereby a change of the evaluation criterion is sufficient for the change of strategy.
  • 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.
  • the regulation can essentially be carried out directly at the street, wherein in the event of a failure of the data transfer by means of external interfaces, the regulation can optionally be further regulated with the last transmitted data, so that despite the failure, a good regulation of the traffic flow 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 of pollutant emissions, in particular in the area of the road, 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 road with multiple intersections, wherein at least two of the intersections signal systems 1 are assigned, 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 evaluation criterion is given, the first traffic parameters 31 and the at least one evaluation criterion 4 are passed to a rating device 6, 6 are determined by the evaluation device manipulated variables 7 and the signal systems 1 are 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 road train is a traffic road train in which a vehicle can travel from one end of the road to the other end of the road. It can the Road section may be part of a road, but it may also be several parts of roads to a street group summarized.
  • the road train forms a substantially linear connection between its ends. In a Ring Nonyak the ends can also coincide.
  • the method essentially relates only to the regulation of the road, wherein the evaluation criterion 4 can be handed over, at least in part, by a hierarchically superordinated method.
  • the hierarchically superordinate method preferably relates to a street hierarchically superior element of a traffic network, for example, a district or a road system of several streets.
  • 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.
  • signal systems 1 may be arranged at crosswalks outside the area of an intersection of the street. Furthermore, signal systems 1 may be arranged during entrances and / or exits along the road, for example when entering and / or exiting parking spaces, parking garages or the like.
  • signal systems 1 may relate to information boards, sign boards and / or prohibition boards.
  • Road signs can alert road users to the particularities of the traffic situation, which can influence the behavior of road users.
  • the billboards may contain information about the parking lot situation, detours, traffic jams or other traffic related information.
  • Billboards and prohibition signs can directly and compulsorily influence the flow of traffic.
  • the signal systems 1, which are provided as information panels, bid panels and / or prohibition panels have a variable display, so that a change in the content of these panels can be effected by the method.
  • the traffic situation of the road 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 in the street measured by means of sensors.
  • other traffic data can be used, for example, from sensors at other traffic points that are related to the traffic situation in correlate to the street.
  • 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 in the street 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 traffic flows in the road, these variables being able to be provided as first traffic parameters 31.
  • the first traffic parameters 31 may also reflect other values, with the first traffic parameters 31 also being the same Traffic flows in the street can be determined. For example, the inflows and outflows at intersections, entrances and / or exits 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 in the street. 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 road 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 road to be imaged by means of the traffic model can instead of the time and day or in addition to the time and day at least one other or at least one other input parameter 10 is selected becomes.
  • the at least one input parameter 10 includes information about the current weather.
  • the weather data can be transmitted by data transfer to the traffic facility 2.
  • the weather data can be determined, for example, directly at the signal system 1 or taken over by prediction stations.
  • the number of vehicles in the street can form at least one of the at least one input parameter 10, whereby the current traffic volume can be determined directly.
  • the vehicles traveling along a traffic lane on the road can concern 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 by 60 minutes directed into the future, can be taken into account, so that the road 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 road.
  • 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.
  • the method can be easily integrated into the higher-level method of the hierarchically higher-level control system, wherein the control takes place locally in the street and only a part of the evaluation criterion 4 is specified by the higher-level control system.
  • the data transfer can be kept low and local conditions in the street are easily taken into account.
  • the hierarchically higher-level control system preferably relates to a street hierarchically superior element of a transport network, for example, a district or a road system of several roads.
  • the evaluation criterion 4 can be a scalar or a vector variable.
  • a vectorial variable several conditions can simply be summarized in the evaluation criterion 4, whereby different weightings of the individual conditions can simply be specified. It is obvious to a person skilled in the art that a vectorial evaluation criterion 4 can also be provided as a scalar function or the like.
  • 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 by evaluating those manipulated variables 7, by means of which the mandatory criteria are not met, such 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 road is operated with a predeterminable 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 the street in a first standard sentence, the two streets are treated the same, which can be ensured on both roads low downtime due to the duration of the red phases.
  • the green phase of the road crossing the road can be extended and the red phase of the road can be shortened in a second standard set.
  • the red phase is lengthened and the green phase is shortened.
  • a predetermined second standard set at a higher flow level of the road train. This can be particularly favorable if the street is a main street and the street crossing the street is a side street.
  • the standard set can be easily provided that in the street 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 at least one evaluation criterion 4 relates to at least one condition that is to be fulfilled by the method as far as possible, the evaluation criterion 4 being, 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 road train reserve, an outflow in a predefined direction or a maximum backwater length may affect.
  • 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 road train reserve indicates which increase in the inflow can be handled without congestion from the road.
  • a degree of saturation of the road can be determined, which essentially corresponds to the value 100% less of the road train reserve.
  • the evaluation device 6 determines those manipulated variables 7 which fill the evaluation criterion 4, taking into account the first traffic parameters 31 and optionally the second traffic parameters 32.
  • an intersection reserve of the intersections of the road can be formed, which indicates which increase in the traffic flow can be handled by the respective intersection without congestion.
  • the intersection reserve of one or more of the intersections of the road can be provided as part of the first traffic parameters 31 and optionally 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 hierarchically superior element of a traffic network, for example a district or a road system of several streets.
  • control variables 7 can directly specify the signals, in particular the duration and / or the order of the individual signal phases, of the signal system 1.
  • the manipulated variables 7 can also be input parameters of a signaling system control 9 of the signal systems 1. It can be provided that the evaluation criterion of the signaling system control 9 is influenced by the manipulated variables 7.
  • 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 a pedestrian traffic is at least 40 seconds long, and further pretend that the saturation of the road is a maximum of 90%.
  • the design of the street and the current traffic situation further evaluation criteria 4 are specified in this sense, 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 ,
  • fuzzy logic models In addition to machine-learning models, fuzzy logic models have also proven useful for the control model and / or assessment model. Often it is it is possible to verbally describe ratings that can be easily translated into a fuzzy logic model.
  • the capacity of an intersection is exhausted, it may be provided, for example, that at the adjacent intersections the outflow towards this intersection should be reduced.
  • the conditions can be easily understood, so that empirical values can be easily implemented. For example, it may be provided that it can be specified as an evaluation criterion with regard to a crossing of the street: "if the intersection is full, then reduce the outflow of the neighboring intersection".
  • 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.
  • independent modules the individual models can be designed and trained in a particularly easy 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.
  • fuzzy logic models have also proved useful for the assessment model and / or the selection model. Often it is possible to verbally describe appropriate control strategies that can be easily translated into a fuzzy logic model. These control strategies can be achieved by the evaluation criterion 4 and / or the requirement 5.
  • 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 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 can be provided via the external input interface, as a result of which a manual control of the road train can be easily made possible by selecting the evaluation criterion 4.
  • the evaluation criterion the strategy for the regulation of the road can be simply specified.
  • the traffic flows in the road can be determined with the first traffic parameters 31, wherein the first traffic parameters 31 are in particular the traffic flows in the road and / or the crossing reserves of the intersections of the road characterizing parameters can.
  • the first traffic parameters 31 may directly indicate a numerical value for the traffic flows in the road and / or the intersection reserves of the intersections of the road.
  • the examples for training the traffic model can be determined separately in advance. It can be used over a predeterminable period, for example, at least two months, carried out at the intersection measurements.
  • 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 road can be easily adapted 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 continuous training of the models, whereby a steady adaptation of the models and a continuous improvement of the regulation of the road can be achieved.
  • the at least one input parameter 10 is determined at least partially by means of a sensor 11 in the region of the road.
  • the sensor 11 may be attached directly to one of the signal systems 1. In other embodiments of the sensor 11, it may be arranged below the roadway's lane and / or a feeder road.
  • the sensor 11 can be designed to determine the current weather, the inflows of the road, the backwater in the road and / or accidents in the street.
  • 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 traffic device 2, the evaluation device 6 and / or the assessment device 8 with an input device in the area of the road, a center, in particular a traffic control center, or with the higher-level control system, for example, a control system which performs a method for controlling a signaling system in a transport network be connected, for example, be radio or cable connected.
  • the evaluation criterion 4 can be changed from a distance, with which the traffic flow in the street can be controlled externally or at least partially synchronized with neighboring further streets, for example by a hierarchically superior method.
  • the advantage here is that only small amounts of data are to be transmitted, since the method can continue to operate autonomously, at least largely, or that pollutant emissions along main roads can be reduced by optimizing the flow of traffic beyond the road.
  • 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 that in this way the operation of the regulation of the road train can be easily controlled and / or the method for regulating a further road train and / or a traffic network 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.
  • the traffic model of the traffic facility 2 traffic situations for given input parameters 10 can be stored on individual worksheets and the first traffic parameters 31 can be interpolated on the basis of the current input parameters 10.

Claims (10)

  1. Procédé pour la régulation de la circulation sur une voie de circulation à plusieurs croisements, dans lequel des installations de signalisation (1) sont associées à au moins deux des croisements, 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
    - les installations de signalisation (1) sont pilotées 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 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).
  4. Procédé selon la revendication 3, 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.
  5. Procédé selon l'une des revendications précédentes, caractérisé en ce que l'installation d'interprétation (8) comprend un modèle d'apprentissage automatique et/ou un modèle de reconnaissance des formes.
  6. Procédé selon l'une des revendications précédentes, caractérisé en ce que l'installation d'évaluation (6) et/ou l'installation d'interprétation (8) comprennent un modèle de logique floue.
  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 de la voie de circulation.
  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.
EP11450096.0A 2010-07-29 2011-07-29 Procédé de réglage de la circulation d'un tramway Active EP2413302B1 (fr)

Applications Claiming Priority (1)

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ATA1278/2010A AT510248B1 (de) 2010-07-29 2010-07-29 Verfahren zur verkehrsregelung eines strassenzuges

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EP2413302A1 EP2413302A1 (fr) 2012-02-01
EP2413302B1 true EP2413302B1 (fr) 2016-07-20

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CN103440774B (zh) * 2013-08-27 2015-09-23 上海市城市建设设计研究总院 单个信号周期内变换车道转向功能的交叉口信号配时方法
EP3751539A1 (fr) * 2019-06-13 2020-12-16 Siemens Aktiengesellschaft Procédé de régulation de circulation et système de régulation de circulation
CN115733839B (zh) * 2022-11-14 2023-09-12 中国电子科技集团公司第五十四研究所 一种带宽自适应的数据链智能分发策略优化方法

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US5357436A (en) * 1992-10-21 1994-10-18 Rockwell International Corporation Fuzzy logic traffic signal control system
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
US6587778B2 (en) * 1999-12-17 2003-07-01 Itt Manufacturing Enterprises, Inc. Generalized adaptive signal control method and system
DE10021929A1 (de) * 2000-05-05 2001-11-15 Siemens Ag Verfahren und Fuzzy-Steuervorrichtung zum rechnergestützten Ermitteln einer Steuerungsstrategie für ein technisches System, Computerlesbares Speichermedium und Computerprogramm-Element
US6617981B2 (en) * 2001-06-06 2003-09-09 John Basinger Traffic control method for multiple intersections
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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AT510248B1 (de) 2023-01-15
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EP2413302A1 (fr) 2012-02-01

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