EP1298620B1 - Système de commande pour dispositif lumineux de signalisation d'un carrefour - Google Patents

Système de commande pour dispositif lumineux de signalisation d'un carrefour Download PDF

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Publication number
EP1298620B1
EP1298620B1 EP02020174A EP02020174A EP1298620B1 EP 1298620 B1 EP1298620 B1 EP 1298620B1 EP 02020174 A EP02020174 A EP 02020174A EP 02020174 A EP02020174 A EP 02020174A EP 1298620 B1 EP1298620 B1 EP 1298620B1
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Prior art keywords
traffic
characteristic
traffic situation
situations
signal
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EP02020174A
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German (de)
English (en)
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EP1298620A3 (fr
EP1298620A2 (fr
Inventor
Paul Dr. Mathias
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Siemens AG
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Siemens AG
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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

Definitions

  • the invention relates to a method for controlling light sensors at a node according to the preamble of claim 1 and a control device for carrying out the method according to the preamble of claim. 5
  • a traffic light system consists of a combination of light sensors for the various approaches to the junction and the required operating facilities to control the flow of traffic.
  • a light signal transmitter in this sense is a telecommunications device that transmits visible signals to the road users.
  • a local control unit of the intersection runs a signal program, in which the signal times of the traffic signal system with respect to duration and assignment are defined.
  • a distinction is made essentially fixed-time-controlled and traffic-dependent method for controlling the signal generator at a node.
  • the fixed-time signal control is a light signal control with fixed signal times without the possibility of influencing the road user.
  • This macroscopic signal control is based on a long-term consideration of the traffic condition at the node.
  • the method uses fixed time table signal programs with a fixed daily or weekly automatic. In fixed-time-controlled individual nodes, the switching times for changing signal programs are thus set, for example, for the respective day of the week.
  • the method is simple in itself, there are no detectors for the current detection of the traffic condition at the node necessary.
  • fixed-time-controlled methods are relatively inexpensive due to their average planning effort, they are neither In the short or long term flexible with regard to a change in traffic conditions at the intersection, so that re-planning is required time and again.
  • a method for the traffic-adaptive control of a traffic signal system which processes data supplied by sensors for traffic detection in the intersection area.
  • the method does not use pre-built models or algorithms other than traffic safety, but it learns, stores and uses the most favorable traffic flow control methods for all traffic situations typical for the intersection, thus adapting the green phases to the traffic flow in response to temporal variations in traffic ,
  • a so-called feed-forward network is selected, which is trained by means of Reinforcement Learning.
  • the signals obtained from the sensor measurement data are thereby applied to the network inputs so that they are available at the network outputs in processed form for the control of the signal groups during a decision cycle in which each neuron of the network determines its output value from its synaptic inputs stand.
  • the traffic flow resulting from the signal groups switched in this way is evaluated by calculating a real number, which is greater the more vehicles pass the intersection and the fewer vehicles wait at the stop line.
  • this real number is then converted into appropriate changes in the weights in the synapses, so that after many sequences of decision and learning cycles, the real number sets to a maximum value that corresponds to the most favorable traffic flow control.
  • the time required for pre-training of the neural network increases. To increase the speed of learning additional sensors are required at intervals before the stop lines except one sensor on the stop line for each lane.
  • US 5,257,194 discloses a method of controlling light emitters not only at a local node, but also for a blanket system.
  • the traffic intensities in the intersections and the saturation traffic intensities for each direction of travel are recorded;
  • pedestrian signal requirements are detected.
  • Linear programming is used to calculate the local signal timing parameters, ie, minimum, optimal, and maximum green times and round trip durations.
  • the light signal transmitters are switched according to the calculated signal time parameters.
  • an electronic neural system with a plurality of interconnected nodes, which are arranged along a road and coupled with sensors, is known.
  • the sensors Observed quantities such as positions, speeds, distances and the like of vehicles and processed into symbolic patterns representing traffic conditions on the road.
  • the symbolic patterns are forwarded in the neural system and compared to their match quality using, for example, corellation techniques.
  • the degree of corelation ie, the goodness of fit, serves as a measure or metric of the traffic flow between the nodes of the compared symbolic patterns, with a high degree of corollation indicating unimpeded traffic flow, while a low degree of corollary indicates problems in traffic flow between the nodes.
  • the metric is 1, in normal traffic conditions with relatively moving vehicles, the metric value is less than 1. A sudden and rapid change in the corellation is to be taken as a warning, the value of the metric is significant between the patterns is less than 1. Coupled to the nodes is a plurality of traffic signals that are switched based on the symbolic patterns.
  • the US 3,818,429 discloses a traffic guidance system consisting of control method and apparatus for selecting a particular program for controlling light-emitting devices at one or more successive intersections of a plurality of programs stored in advance on punched tape.
  • the control device of the traffic control system is connected to intersection devices for controlling the light signal transmitter and with vehicle detectors for detecting the traffic conditions at the respective intersections.
  • the optimal program is selected by electronic calculation and analysis of the current traffic conditions. From the signals of the vehicle detectors are averaged values of various dynamic traffic parameters, such as density, speed and volume of traffic, calculated. different Traffic volumes are assigned to certain preselected areas of the traffic parameters and it is determined in which parameter area the current traffic volume lies.
  • a program can be done by specific programming of the control unit also by time of day and day of the week.
  • a program is understood to mean a data block of durations which determine the switching times for the light signal transmitters during a cycle. If the current parameter range is left in a running cycle, a new program, which is adapted to the current traffic conditions, is activated in the following cycle.
  • the known controls suffer from a considerable care and test effort on the part of the traffic planner or commissioning and require replanning due to often fundamental changes in traffic conditions over the course of months or years.
  • the invention is therefore based on the object to provide a system for local node control, which has greater flexibility in changes in traffic than pure fixed-time controls and at the same time shows high performance with minimal planning and coverage and moderate detector equipment.
  • each characteristic traffic condition a matched to this signal signal program is defined as a measure of the mutual position of two traffic conditions, a metric which is determined with respect to the defined metric the current traffic condition closest characteristic traffic condition, and the signal characteristic associated with the nearest characteristic traffic condition is issued for issuing switching commands for the light signal transmitter, the planning and supply effort is limited to the specification of basic data, such as the node topology, main directions, signal group definition, minimum green and transition times, split times and setup lengths, and some conditions, such as priorities and optimization criteria.
  • the procedure can adapt to changing traffic conditions on a short-term time scale.
  • the method according to the invention has a significantly greater flexibility than fixed-time-controlled methods and with relatively simple detection of the traffic conditions in the form of simple counts.
  • the traffic-related maintenance costs are reduced, since the method according to the invention adapts itself independently to changing framework conditions.
  • the diversity of traffic conditions occurring at a node becomes classified according to the frequency of their occurrence and their distribution in the space of all traffic conditions.
  • a characteristic traffic condition for example, as a heavy or accumulation point.
  • the distance between a newly determined characteristic traffic condition of a class of traffic conditions and the currently valid characteristic traffic condition of this class is determined, at a predeterminable threshold value for the distance exceeds the currently valid characteristic traffic condition by the newly determined characteristic traffic condition for replaces this class and calculates a signal program associated with the newly determined characteristic traffic condition.
  • a predeterminable threshold value for the distance exceeds the currently valid characteristic traffic condition by the newly determined characteristic traffic condition for replaces this class and calculates a signal program associated with the newly determined characteristic traffic condition.
  • a switching operation is determined by the previously executed signal program to the currently executable signal program.
  • the characteristic traffic state does not change or only slightly changes during its cyclic detection, the characteristic traffic state is maintained and thus the signal program assigned to it remains active. If, however, due to a shift in the statistical distribution, a new characteristic traffic condition or, due to a current change in the traffic condition, the characteristic traffic condition of another class is more obvious, a new signal program must be carried out after the cycle change.
  • traffic data of the node are continuously detected by detectors in the form of raw measured values, cyclically retrieving the acquired raw measured values and processing them by averaging or smoothing, using substitute values in the case of missing measured values, and the current traffic condition from the processed and possibly replaced measured values derived.
  • sensibly usable measured values are obtained from the continuously recorded raw measured values of the detectors, which cyclically provides the process with a current traffic state at the node to be controlled, even in the event of a possible failure of detectors.
  • the control module consists essentially of a main processor, which controls up to 48 signal groups, for example, from memory modules and various interfaces.
  • a control unit 10 comprises a core module 20 and a control module 30.
  • the switching of signal groups comprising light signal transmitters 40 and the continuous acquisition of traffic data by detectors 50 takes place.
  • About the basic supply 24 of the core module 20 intermediate times, minimum release times, offset times and transition times can be specified.
  • the control module 30 is encapsulated, the only interfaces go to the traffic-dependent core module 20 of the control unit 10.
  • the control component 30 does not use the signal program memory of the core module 20, but manages its own signal programs and only sets the corresponding switching commands.
  • the control module 30 comprises means 31 for processing the currently detected raw measured values of the detectors 50.
  • the means 23 for storing the raw measured values in the core module 20 shown in FIG. 2 are polled cyclically.
  • the pipe readings may then be condensed by special smoothing or averaging. If different types of measurements are available, such as counting and time gap, derived quantities such as LOS values are calculated by combining the original values. In the case of missing or failed detectors 50 substitute values are used instead of the original measured values.
  • the replacement measurements may optionally be defined at the supply 60 of the control module 30. It is also possible to specify substitute values specifically for different day types and hour ranges.
  • the measured values processed in this way represent the traffic state detected at the junction, which is stored in the means 32 for storing prepared measured values shown in FIG.
  • the control module 30 further comprises means 33 for deriving traffic conditions characteristic of the node.
  • traffic conditions characteristic of the node statistics about the current traffic data are continuously created, taking into account special calendar days, such as weekdays, weekends and public holidays. By using correspondingly smoothed or averaged values, the statistics only cover medium to long-term trends.
  • calendar data is important to adequately respond to infrequent but important traffic conditions.
  • the maximum number of classes can be specified via the supply 60 of the control module 30. For each class a representative representative is calculated, the so-called characteristic traffic condition.
  • the determination of the classes and their representatives is based on metrics, that is, certain distance functions which are expressions for specific performance criteria such as waiting times or set-up lengths.
  • the type of criteria can be selected in the supply 60 of the control module 30.
  • the characteristic traffic conditions are stored in means 34.
  • control module 30 comprises means 35 for monitoring changes in the characteristic traffic conditions.
  • the currently valid characteristic traffic conditions are compared with the newly calculated characteristic traffic conditions and it is determined whether the new, possibly drifted, have departed from the currently valid characteristic traffic conditions beyond a certain, predeterminable extent. If a threshold is exceeded, a new drifted characteristic traffic condition replaces the currently valid representative for that class. To determine the distance between two characteristic traffic conditions, the same metrics are used as in the clustering of traffic conditions.
  • the control module 30 also comprises means 36 for calculating signal programs which are each tuned to and associated with a stored characteristic traffic condition. For each new drifted characteristic traffic condition, an optimal signal program is calculated using a "genetic algorithm" based on attributes of a characteristic traffic condition, such as counts or traffic densities, from the nodal topology and other ancillary information such as directional priorities, pitch and offset times.
  • the optimization criterion ie the objective function, is freely definable.
  • the maximum number of signal groups is limited to sixteen in this embodiment.
  • the newly calculated signal program is stored in means 37 for storing signal programs, being assigned to the characteristic traffic state to which it is tailored.
  • the control module 30 comprises means 38 for determining the closest to the current traffic condition characteristic traffic condition with associated signal program. Depending on the traffic conditions recorded online, the selection of the respectively appropriate signal program is made by determining the closest characteristic traffic state. Distance estimation uses the same metrics as analyzing and clustering traffic conditions. In order to be able to react quickly to particularly extreme, unusual situations, a free emergency signal program is available, which can be temporarily overwritten and switched depending on the situation and in particular is not subject to the drift of the characteristic traffic conditions. In the case of a signal program change, corresponding phase transitions are determined which take into account the usual framework conditions, such as intermediate and offset times. Existing routines of the core module 20 are used for the calculation of the phase transitions.
  • control module 30 comprises means 39 for executing a signal program.
  • switching commands for the light signal transmitters 40 are forwarded to the core module 20 of the control device 10 every second.
  • control module 30 has its own fixed-time control with self-managed signal programs.
  • the method for controlling optical signal transmitters 40 at a node consists of the three cyclic subprocesses "data processing and clustering of traffic conditions" 70, "monitoring the characteristic traffic conditions and signal program calculation” 80 and "signal program selection and signal group circuit” 90, which are the partially common local Means 23 for storing raw measured values of the detectors 50, means 32 for storing prepared measured values or traffic conditions, means 34 for storing characteristic traffic conditions and means 37 for storing signal programs associated with the characteristic traffic conditions. Otherwise, the sub-processes work largely independently of each other.
  • the sub-process 70 begins in step 71 with the cyclic readout of the raw measured values from the memory 23.
  • these raw measured values are aggregated, ie smoothed and optionally averaged over time, and linked. For failed or missing detectors 50, substitute values may be used.
  • the measured values prepared in this way form the traffic states with which the method works; they are stored in the memory 32.
  • the space of the traffic conditions is divided into a predetermined number of classes according to a statistical distribution of the traffic conditions. For each class, a representative, a so-called characteristic traffic condition, is calculated.
  • the most recent characteristic traffic conditions are stored in memory 34 and optionally cyclically overwritten there.
  • the memory 34 also contains the currently valid characteristic traffic conditions, on which the automatic signal program selection currently operates.
  • the sub-process 80 begins in step 81 with the retrieval of the currently valid and the newly calculated characteristic traffic conditions from the memory 34. Cyclically, in step 82 it is checked whether a newly calculated characteristic traffic state moves beyond a threshold beyond the currently valid characteristic traffic condition. In determining the mutual location of characteristic traffic conditions, a given metric is used as a measure of the distance. When the threshold value is exceeded, in step 83 the previously valid characteristic traffic condition is replaced by the newly calculated drifted characteristic traffic condition and stored in the memory 34. Furthermore, in step 84, a signal program tailored to the new characteristic traffic condition is calculated and stored in memory 37 while being assigned to it.
  • Sub-process 90 starts cyclically in step 91 with retrieving the current traffic condition from memory 32. Further in step 92, the current traffic characteristic conditions are retrieved from memory 34 to determine in step 93 which of the valid characteristic traffic conditions corresponds to the current traffic condition predetermined metric is closest. In step 94, a decision is made as to whether there is a change in the characteristic traffic condition due to drift within the same class or due to class change due to the current traffic condition. If so, in step 95 the associated signal program is loaded from memory 37 and in step 96 a suitable phase transition is determined for switching from the previously active to the newly loaded signal program. Finally, in step 97, switching commands for the light signal generator 40 having signal groups corresponding to the current signal plan or after the specific phase transition issued. The collection of the stored signal programs constantly adapts to the current statistical distribution of the traffic values, whereby the control device 10 according to the invention organizes itself.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)

Claims (7)

  1. Procédé de commande de dispositifs (40) lumineux de signalisation en un point nodal, dans lequel
    - on détecte cycliquement un état du trafic au point nodal,
    - on sélectionne un programme de signal adapté à l'état du trafic déterminé,
    - et les dispositifs (40) lumineux de signalisation reçoivent des instructions de commutation du programme de signal sélectionné,
    caractérisé en ce que
    - on déduit des états de trafic détectés, des états de trafic caractéristiques du point nodal,
    - on associe à chacun des états de trafic caractéristiques, un programme de signal qui lui est adapté,
    - on définit une métrique comme mesure de la position mutuelle de deux états de trafic,
    - on détermine, par rapport à la métrique définie, l'état du trafic caractéristique le plus proche de l'état du trafic instantané,
    - et l'on effectue le programme de signal associé à l'état de trafic caractéristique le plus proche pour émettre des instructions de commutation des dispositifs (40) lumineux de signalisation,
    dans lequel
    - après chaque détection de l'état de trafic actuel, on forme une répartition statistique de tous les états de trafic détectés,
    - en fonction de la répartition statistique, on rassemble en classes les états de trafic,
    - et on détermine pour chaque classe d'état de trafic, un état de trafic caractéristique comme étant son représentant.
  2. Procédé suivant la revendication 1,
    caractérisé en ce que
    - on détermine l'intervalle entre un état de trafic caractéristique nouvellement déterminé d'une classe d'état caractéristique et l'état de trafic caractéristique en vigueur actuellement de cette classe,
    - si une valeur de seuil pouvant être prescrite pour l'intervalle est dépassée, on remplace l'état de trafic caractéristique en vigueur actuellement par l'état de trafic caractéristique nouvellement déterminé pour cette classe,
    - et on calcule un programme de signal associé à l'état de trafic caractéristique nouvellement déterminé.
  3. Procédé suivant la revendication 1 ou 2,
    caractérisé en ce que lors d'un changement de l'état de trafic caractéristique, on détermine une opération de passage du programme de signal exécuté jusqu'ici au programme de signal s'exécutant actuellement.
  4. Procédé suivant l'une des revendications 1 à 3,
    caractérisé en ce que
    - on détecte en continu des données de trafic du point nodal par des détecteurs (50) sous la forme de valeurs de mesures brutes,
    - on demande cycliquement les valeurs de mesures brutes détectées et on les traite en faisant une moyenne ou un lissage,
    - dans le cas où des valeurs de mesures sont manquantes, on utilise des valeurs de remplacement,
    - et l'on déduit des valeurs de mesures traitées et le cas échéant remplacées l'état de trafic actuel.
  5. Appareil (10) de commande pour la mise en oeuvre d'un procédé suivant l'une des revendications 1 à 5, comprenant
    - des moyens (32) de mémorisation d'états de trafic détectés sur un point nodal,
    - et des moyens (39) d'exécution d'un programme de signal qui est formé pour émettre des instructions de commutation aux dispositifs (40) lumineux de signalisation,
    caractérisé par
    - des moyens (33) pour déduire des états de trafic caractéristiques pour le point nodal à partir des états de trafic mémorisés,
    - des moyens (34) de mémorisation des états de trafic caractéristiques déduits,
    - des moyens (36) de calcul de programmes de signal, qui sont adaptés respectivement à un état de trafic caractéristique mémorisé et qui lui sont associés,
    - des moyens (37) de mémorisation des programmes de signal associés aux états de trafic caractéristiques,
    - des moyens (38) de détermination de l'état de trafic caractéristique le plus proche de l'état de trafic actuel ayant un programme de signal associé,
    les moyens (33) pour déduire des états de trafic caractéristiques pour le point nodal, comportant
    - des moyens de formation d'une répartition statistique des états de trafic détectés,
    - des moyens de rassemblement des états de trafic en des classes correspondant à la répartition statistique,
    - et des moyens de détermination d'un état de trafic caractéristique comme représentant d'une classe d'état de trafic.
  6. Appareil de commande suivant la revendication 5,
    caractérisé en ce qu'il a en outre des moyens (35) de contrôle de la position mutuelle de deux états de trafic caractéristiques, l'intervalle entre les deux états de trafic caractéristiques étant comparé à une valeur de seuil prescrite.
  7. Appareil suivant la revendication 5,
    caractérisé en ce qu'il comporte en outre des moyens (31) de traitement des valeurs de mesures brutes de détecteur détectées actuellement, les valeurs de mesures traitées représentant l'état de trafic détecté au point nodal.
EP02020174A 2001-09-20 2002-09-09 Système de commande pour dispositif lumineux de signalisation d'un carrefour Expired - Lifetime EP1298620B1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE10146398 2001-09-20
DE10146398A DE10146398A1 (de) 2001-09-20 2001-09-20 System zum Steuern von Lichtsignalgebern an Kreuzungen

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EP1298620A2 EP1298620A2 (fr) 2003-04-02
EP1298620A3 EP1298620A3 (fr) 2003-06-18
EP1298620B1 true EP1298620B1 (fr) 2007-07-18

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Publication number Publication date
US20030063016A1 (en) 2003-04-03
DE50210488D1 (de) 2007-08-30
EP1298620A3 (fr) 2003-06-18
US6850171B2 (en) 2005-02-01
DE10146398A1 (de) 2003-04-17
EP1298620A2 (fr) 2003-04-02

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