EP1480183A1 - Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès - Google Patents

Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès Download PDF

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Publication number
EP1480183A1
EP1480183A1 EP03011372A EP03011372A EP1480183A1 EP 1480183 A1 EP1480183 A1 EP 1480183A1 EP 03011372 A EP03011372 A EP 03011372A EP 03011372 A EP03011372 A EP 03011372A EP 1480183 A1 EP1480183 A1 EP 1480183A1
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EP
European Patent Office
Prior art keywords
traffic
points
fundamental diagram
determining
detector
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP03011372A
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German (de)
English (en)
Inventor
Jürgen Mück
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TRANSVER GmbH
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TRANSVER GmbH
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Publication date
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Priority to EP03011372A priority Critical patent/EP1480183A1/fr
Priority to EP04001394A priority patent/EP1480184A3/fr
Publication of EP1480183A1 publication Critical patent/EP1480183A1/fr
Withdrawn legal-status Critical Current

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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
    • G08G1/075—Ramp control
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/07—Controlling traffic signals
    • 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 determining traffic parameters at operator stations for handling individually moving units with alternating ones Blocking and transmission phases and with a detector arranged in front of the operator station.
  • the operating stations mentioned such as traffic lights or locks, usually serve to transport the traffic of individually moving units, such as Motor vehicles to regulate.
  • the operator stations have handling phases that consist of a blocking phase and a pass phase.
  • LSA Light signal system
  • a fundamental diagram is a graphic representation of which the relationship between traffic volume (number of units per unit of time) and the traffic density (number of units per path length). Both sizes that Traffic strength and traffic density are usually predetermined for each Determine time intervals and then for each time interval as a point in the fundamental diagram shown. So every point of a fundamental diagram gives the relationship between traffic volume and traffic density during a Time interval. Both quantities can be appropriately standardized by: for example, divided by a time and / or length interval. In a fundamental diagram the traffic volume can be plotted against the traffic density become; alternatively, the axes can also be interchanged.
  • the Traffic density can be determined by explicitly observing and counting the units.
  • the traffic density can also be determined by the occupancy of a detector (Sum of the periods of occupancy) specified within a (measurement) interval become.
  • the occupancy period can also be divided by the duration of the measurement interval so that then the traffic density by the so-called occupancy rate is specified.
  • the fundamental diagram can show how already mentioned before, traffic volume over occupancy duration or occupancy rate or are shown with reversed axes.
  • At least one subset is shown in the fundamental diagram determined by points that correspond to a traffic condition.
  • a traffic condition becomes the state of the traffic flow especially at the operator station understood, for example, whether all incoming during an observation interval Units pass the operator station or a traffic jam occurs.
  • the subset in the fundamental diagram also depends on the arrangement of the detector with respect to the operator station. By the subset of points an area is defined in the fundamental diagram.
  • Traffic parameters From the at least one specific subset or from the corresponding one Traffic parameters can then be determined. In particular can from the arrangement and shape of the area and / or the number of points in the subset Statements about traffic parameters are made. Because a fundamental diagram can be determined without great effort, enables the invention Procedure a simple determination of traffic parameters.
  • step a) can include determining the traffic volume and the duration of occupancy of the detector. Both sizes can be determined in different simple ways.
  • the detector can simply count the number of passing units, for example, during an observation interval.
  • the occupancy period can be determined in an analogous manner by adding the individual occupancy periods of the detector by the units during an observation interval.
  • the quantities can also be determined from other measurement quantities.
  • B ZB Fz + ( r - dt )
  • B Fz is the mean individual occupancy time of a unit (in particular a vehicle)
  • r the duration of the blocking phase e.g. red phase in a traffic light system
  • dt filling time measured by the detector (duration from the beginning of the blocking phase to permanent occupancy of the detector).
  • each point of the fundamental diagram can be carried out in step a) can be determined for a handling phase.
  • the amount of handling phases can be a very precise fundamental diagram to be created.
  • the shown Sizes are appropriately standardized if the handling intervals are longer Seen observation period change, as is common for traffic lights the case is.
  • each point of the fundamental diagram can be used for a time interval regardless of the length of the handling phase.
  • smoothing can be done in this way of the fundamental diagram can be achieved.
  • the whole The procedure is simplified because standardization is based on the same time intervals the sizes shown is not necessary; however, standardization can nevertheless be carried out, for example if a comparison with other data enables shall be.
  • Step b) determining at least two regions of points which are marked by a predetermined function, preferably linear function, are separated from one another include.
  • step b) of the previously described methods can be a division of the amount the points in the fundamental diagram into a predetermined number of subsets or into a number of subsets, the number between 1 and a predetermined Maximum number is included.
  • step b) can further approximate the Include points of each subset by a function, preferably a linear function.
  • the type of function can be used for the approximation, for example that it is a linear function acts, be predetermined; the parameters of the compensation function are then determined by the approximation. From the parameters of the compensation function (e.g. the slope and the ordinate section in a straight line) desired traffic parameters can be easily determined.
  • step b) can determine a quality value include for each approximation and the steps of range determination or splitting, approximating and determining the quality value are repeated, until the quality value is optimal.
  • the quadratic deviation can be used as a quality value.
  • step b) can do all of the previously described Methods include associating each subset with a traffic condition.
  • This Mapping can be done using fuzzy logic, for example. from that the quality of the traffic flow can then be determined in a simple manner, by checking which traffic conditions occur. If everyone also Point can also be indexed with the time at which its value was determined determine which traffic conditions occur at what times.
  • the methods described above can preferably determine traffic parameters for coordination with respect to an upstream Operating station include. In this way, the quality of successive operator stations determined and by a suitably modified setting or control one or both operator stations can be optimized.
  • a detector in front of the operator station there is a detector in front of the operator station arranged.
  • at least one further detector in one predetermined distance in front of the operator station is arranged.
  • This predetermined distance can also be 0, so that the detector directly at the Operating station is arranged.
  • a further detector can be used, in particular second fundamental diagram can be provided.
  • For certain traffic conditions e.g. with an ideal coordination of successive operator stations, see above
  • no vehicle or only a few stop in front of the operator station more precise information can be obtained if a detector is close to the Operating station is arranged.
  • it is, for example, with a disordered one Accumulation of units in front of the operator station is an advantage if a detector detects one further away from the operator station.
  • the invention provides a method for controlling an operator station for dispatch individually moving units with the steps ready:
  • Such control can be done offline or online.
  • the Data determined over a certain period of time and then using the method evaluated.
  • the invention also provides a computer program product which can be loaded directly into the working memory of a digital computer and instruction code sections comprising the steps of one of the previously described Procedures are performed when the computer program product is on a Computer is running.
  • a computer program product which is based on a computer-readable Medium is stored and includes computer-readable program resources, with which the steps of the previously described methods are carried out if the computer program product runs on a computer.
  • FIG. 1 illustrates an example of a geometry on which the method is based the case of traffic lights as an operator station on a street.
  • Street 1 has two operator stations, in this case light signal systems 2 and 2 '.
  • a stop line 3 or 3 ' is arranged on the road in each traffic light system.
  • the street shown is a one-way street on which Move vehicles 4 from left to right, as indicated by the arrow.
  • a detector 5 is arranged at a predetermined distance D in front of the stop line.
  • FIG. 2 An example of the possible areas of a fundamental diagram for light signal systems is shown in FIG. 2.
  • the duration of occupancy B is shown over the number of vehicles Z.
  • Z det also indicates the average number of vehicles that can be positioned between the detector and the stop line, Z max the capacity (maximum number of vehicles) per measuring interval and B max the maximum duration of occupancy with a permanent occupancy of the detector that corresponds to a measuring or Observation interval corresponds.
  • Examples of possible areas are also identified in the fundamental diagram. It should be emphasized again that the areas shown here are to be understood purely as examples and can vary in shape, arrangement and number from case to case.
  • a "coarser” or “finer” division into different areas can be selected.
  • GA Green Arrival
  • MN Measurement Noise
  • FA Free Arrival Points in this area correspond to the cases where vehicles arrive at the traffic signal system "randomly" over the entire red period (blocking phase).
  • EA Electronic Arrival
  • LA Late Arrival
  • OS Oversaturation
  • the GA area can be used in the case of two successive light signals speak of good or even ideal coordination. Those arriving in a crowd Vehicles only hit during the release period (pass phase) at the stop line of the traffic light system.
  • a corresponding path / time diagram is shown in Figure 3. The x-axis corresponds to the path here, whereby for the better Overview lines 3 'and 3 are also drawn in this diagram are.
  • a group 7 that has passed during a green phase 6 hits the next one Light signal system also on a green phase (here designated 8) and is let through. The length of the green phase is g, the length of the red phase with r and the total length of a handling phase with c.
  • the size B Fz in [s / Fz] represents the average occupancy time of the detector when a vehicle is crossed.
  • the total occupancy time is proportional to the number of vehicles passing. This explains the position and the slope of the corresponding state range in the example shown in FIG. 2.
  • the occupancy duration B irrespective of the type of coordination, cannot have values higher than in equation (1).
  • FIG. 4 A simulation result for the measurement of good coordination is shown in FIG. 4.
  • the x-axis represents the traffic volume and the y-axis represents the period of occupancy. Each point corresponds to the observation in one Measurement interval.
  • LA area For poor coordination (LA area) there are generally two options be considered:
  • a bunch may arrive "too early" and the vehicles come to a stop before they leave can start again at the start of approval.
  • part of the bulk can be replaced by a too early end of the release to be forced to stop in front of the LSA.
  • the stopped vehicles then approximately during the entire period Wait lock time.
  • the release time can only be used to a limited extent.
  • the number of measured vehicles decreases, but at the same time the occupancy time increases due to stop-and-go traffic on the detector even during the approval period.
  • the occupancy period corresponds to the measurement interval (in the present case the circulation period or duration of the clearance phase c ).
  • a center of gravity ( Z congestion , B congestion ) of the corresponding point set in the fundamental diagram can be determined, which corresponds to the corresponding capacity
  • a linear approach for the location of the measuring points (points in the fundamental diagram) in the case of faults can take the form: where B congestion is equal to the maximum occupancy B max without disruption. From this, a (measurable) indicator of the severity of a disturbance can be derived:
  • traffic parameters such as capacity, the number of vehicles the come to a stop, waiting times, coordination quality levels according to HBS or others Specifications and / or information about an effective shift of the shaft position determine.
  • the corresponding parameters can also be used for certain time ranges are specified, for example the type that occurs during the morning peak an overload lasts from 8:30 to 9:15, in this time range for 15 Minutes of downstream disruption set up good coordination over 70% of the day, in case of stress less than approx. 450 vehicles per hour, the release time for loads above 450 vehicles / h ended too early, and that at maximum capacity the release end by 5 vehicles / 10s would have to be increased.
  • the average time that a detector is occupied during the passage of a vehicle can be estimated by:
  • the method illustrated in FIG. 7 can be used to determine areas.
  • a flow chart calculates the assignment to one of the areas for each measuring point ( B , Z ) by going through a sequence of inequalities (bounds).
  • inequalities bounds
  • additional criteria must be used.
  • B (Z) B Fz, u ⁇ Z + 5
  • B ( Z ) B Fz, u ⁇ Z + r - 5th
  • B ( Z ) B Fz, o ⁇ Z + r + 5
  • B Fz, u and B Fz , o denote a lower and an upper estimate for the average occupancy of the detector when a vehicle is crossed, which can be estimated, for example, at 0.4s and 0.6s.
  • a "tolerance range" is set for the deviation from an ideal profile with an occupancy of 5 s.
  • Another method of determining the areas in a fundamental diagram can have the following form, with this method the amount of points in the fundamental diagram into a number between 1 and a predetermined maximum number is divided by subsets. In the procedure described below the number of vehicles over the period of occupancy in the fundamental diagram applied; however, the method can also be used in an analogous manner for swapped Axes are performed. The set of points is relative to the x-axis divided into different areas, with the points in each area separated by a regression line should be described. The areas thus obtained correspond different status areas.
  • each block is divided into two blocks one after the other, starting from this then each block is divided one after the other and so on.
  • the branches the recursion ends in this example at 4 blocks, making a list of divisions with 1 to 4 blocks each. If traffic at an LSA as described above, is divided into 6 status areas AG, ..., OS, the division into up to 6 blocks. However, a smaller number of blocks is also possible simplifies the process. Conversely, if the traffic is in another, in particular larger number of traffic conditions is classified, including a corresponding one different number of maximum subsets can be selected.
  • the following table shows the result of these subdivisions for an example with 721 measured values, whereby only a section of the list of subdivisions is shown in the table shown. For each block, the table shows the first value (lower limit on the occupancy axis) and the number of points in the subset.
  • Each block is then divided into a status area (AG, FA, MN, EA, LA, OS) assigned. This is done by comparing different parameters the regression line or the regression line of the mirrored point set according to predetermined criteria. The slope, the ordinate section and the standard estimation error of both the regression line the set of points as well as the mirrored set of points.
  • the Belonging a block to a status area is done via fuzzy logic queries checked. The corresponding fuzzy logic functions check for agreement or less than or equal correspondence of parameters with predetermined ones Values. According to these queries, a status area is assigned to each block, for which the query gives the best match.
  • a quality value is calculated for each division using a quality function. In the following example, this is done by adding the standard estimation errors of the blocks i weighted by the number of elements n i, the standard estimation errors s B, Z, i being used for the regression line of the mirrored point set in all state areas except MN.
  • the method according to the invention only requires aggregated detector data without synchronization with LSA signals.
  • the process can be done in many different ways be used. For example, use in a central monitoring or monitoring system for permanent monitoring, a temporary one Use through an offline use of aggregated values in LSA control units are temporarily stored or can be used as a mobile, infrastructure-independent Procedure when temporary detectors are used. Also Online use in control units or network controls is possible, wherever in time finely resolved data are available.
  • the method can also be used for online traffic quality monitoring become. Many traffic control centers are already receiving traffic lights aggregated detector values for occupancy and traffic volume. With the invention Procedures can be permanently monitored online traffic flow be performed. In particular, an automated evaluation of the status area can OS by means of suitable threshold values in order to generate corresponding alarm messages trigger. In addition, the workload can be recorded to automatically or manually switch to a cheaper signal program. The procedure can also be used to calibrate bulk models. Pulkmodelle have the goal of detecting the arrival of vehicles at a traffic light system Characteristic data (e.g. traffic load, turn rates, signal position, distance) to calculate an LSA in the inflow. Bulk models are used e.g. in Network controls to optimize green waves online.
  • Characteristic data e.g. traffic load, turn rates, signal position, distance
  • FIG. 10 A schematic representation of the optimization of a bulk model is shown in FIG. 10.
  • An optimization algorithm tries to switch green phases optimally to adapt to the arrival distributions.
  • the calibration can be done step by step after each new measurement of the fundamental diagram or based on saved Data of a period (e.g. a day) for a large amount of measurements be done at once. This can be based on a target function be the measure of the deviation between a generated fundamental diagram and a measured fundamental diagram.
  • Calibration based on a large number of saved measuring points can be done both online and offline. You can also during a Commissioning phase are carried out, optimizing coordination after calibration is complete.
  • a simple variant of the calibration procedure would be to limit it to a few Characteristics of the fundamental diagram, for example the number of vehicles, from which the full batch can no longer drain during the release.
  • the method according to the invention can be used to adapt the offset time LSA with respect to an upstream LSA, so that the Flow time or generally the offset is minimized.
  • This can be based on a quality index (for example, the estimated total loss times for all vehicles) or on Based on certain parameters of the fundamental diagram (e.g. the number of the vehicles from which the full group no longer flows off during the release can happen).
  • the offset time to an upstream LSA can also depending on the number of vehicles per unit time to be carried out to compete Coordination requirements in various LSA driveways to meet.
  • FIG. 11 An example of such an offset time optimization is shown in FIG. 11.
  • exemplary a ring road is shown in this figure, which is designed as a one-way street.
  • Traffic signals are arranged where relevant streets cross the ring road.
  • the route to be coordinated is designed as a one-way street can be done with the help of the method the entire ring can be optimally coordinated using this procedure.
  • Only a signal system 9 the beginning and end cross section of the ring at the same time must be excluded from the optimization as a resting point.
  • criteria For the selection of this LSA the incoming section of the route can be the traffic one has the least importance.

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  • General Physics & Mathematics (AREA)
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EP03011372A 2003-05-19 2003-05-19 Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès Withdrawn EP1480183A1 (fr)

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EP03011372A EP1480183A1 (fr) 2003-05-19 2003-05-19 Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès
EP04001394A EP1480184A3 (fr) 2003-05-19 2004-01-22 Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès

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EP03011372A EP1480183A1 (fr) 2003-05-19 2003-05-19 Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2280383A1 (fr) 2009-07-31 2011-02-02 Siemens Aktiengesellschaft Procédé d'établissement d'informations de circulation pour un traject routier d'un réseau routier et calculateur de circulation destiné à l'exécution du procédé
DE102012220094B3 (de) * 2012-11-05 2014-02-20 Deutsches Zentrum für Luft- und Raumfahrt e.V. Verfahren zur Bestimmung einer Verlustzeit, Verfahren zur dynamischen Steuerung einer Signalanlage und Vorrichtung zur Bestimmung einer Verlustzeit
CN113593267A (zh) * 2021-06-25 2021-11-02 青岛海尔科技有限公司 红绿灯控制方法及红绿灯控制装置

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US4390951A (en) * 1979-09-07 1983-06-28 Thomson-Csf Apparatus for monitoring road traffic to control an associated signaling system
US5444442A (en) * 1992-11-05 1995-08-22 Matsushita Electric Industrial Co., Ltd. Method for predicting traffic space mean speed and traffic flow rate, and method and apparatus for controlling isolated traffic light signaling system through predicted traffic flow rate
FR2761502A1 (fr) * 1997-03-26 1998-10-02 Michel Glinel Procede et installation de commande de moyens de signalisation routiere pour l'optimisation des flux de vehicules
EP1276085A1 (fr) * 2001-07-11 2003-01-15 TransVer GmbH Procédé pour déterminer un index d'embouteillage et pour déterminer des longeurs de refoulement
EP1298620A2 (fr) * 2001-09-20 2003-04-02 Siemens Aktiengesellschaft Système de commande pour dispositif lumineux de signalisation d'un carrefour

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US4390951A (en) * 1979-09-07 1983-06-28 Thomson-Csf Apparatus for monitoring road traffic to control an associated signaling system
US5444442A (en) * 1992-11-05 1995-08-22 Matsushita Electric Industrial Co., Ltd. Method for predicting traffic space mean speed and traffic flow rate, and method and apparatus for controlling isolated traffic light signaling system through predicted traffic flow rate
FR2761502A1 (fr) * 1997-03-26 1998-10-02 Michel Glinel Procede et installation de commande de moyens de signalisation routiere pour l'optimisation des flux de vehicules
EP1276085A1 (fr) * 2001-07-11 2003-01-15 TransVer GmbH Procédé pour déterminer un index d'embouteillage et pour déterminer des longeurs de refoulement
EP1298620A2 (fr) * 2001-09-20 2003-04-02 Siemens Aktiengesellschaft Système de commande pour dispositif lumineux de signalisation d'un carrefour

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PAPAGEORGIOU M ET AL: "ALINEA: A LOCAL FEEDBACK CONTROL LAW FOR ON-RAMP METERING", TRANSPORTATION RESEARCH RECORD, TRANSPORTATION RESEARCH BOARD, WASHINGTON, DC, US, 1989, pages 58 - 64, XP009015472, ISSN: 0361-1981 *
PAPAGEORGIOU M: "MEHRSCHICHTENREGELUNG DES VERKEHRSABLAUFS AUF SCHNELLSTRASSEN. MULTI-LEVEL CONTROL OF HIGHWAY TRAFFIC FLOW", REGELUNGSTECHNIK, OLDENBOURG VERLAG. MUNCHEN, DE, vol. 30, no. 5, 1 May 1982 (1982-05-01), pages 166 - 174, XP000649324 *
XU YANG ET AL: "GA-based Parameter Optimization For The ALINEA Ramp Metering Control", PROCCEDINGS OF THE 5TH IEEE CONFERENCE ON ITS, 3 September 2002 (2002-09-03), pages 627 - 632, XP010608364 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2280383A1 (fr) 2009-07-31 2011-02-02 Siemens Aktiengesellschaft Procédé d'établissement d'informations de circulation pour un traject routier d'un réseau routier et calculateur de circulation destiné à l'exécution du procédé
DE102012220094B3 (de) * 2012-11-05 2014-02-20 Deutsches Zentrum für Luft- und Raumfahrt e.V. Verfahren zur Bestimmung einer Verlustzeit, Verfahren zur dynamischen Steuerung einer Signalanlage und Vorrichtung zur Bestimmung einer Verlustzeit
CN113593267A (zh) * 2021-06-25 2021-11-02 青岛海尔科技有限公司 红绿灯控制方法及红绿灯控制装置

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