EP0902404B1 - Procédé de détermination d'information sur le trafic - Google Patents

Procédé de détermination d'information sur le trafic Download PDF

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Publication number
EP0902404B1
EP0902404B1 EP98117163A EP98117163A EP0902404B1 EP 0902404 B1 EP0902404 B1 EP 0902404B1 EP 98117163 A EP98117163 A EP 98117163A EP 98117163 A EP98117163 A EP 98117163A EP 0902404 B1 EP0902404 B1 EP 0902404B1
Authority
EP
European Patent Office
Prior art keywords
data
traffic
cross sections
measured values
data processing
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.)
Expired - Lifetime
Application number
EP98117163A
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German (de)
English (en)
Other versions
EP0902404A3 (fr
EP0902404A2 (fr
Inventor
Thomas Sachse
Fritz Dr. Busch
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siemens AG
Original Assignee
Siemens AG
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Filing date
Publication date
Application filed by Siemens AG filed Critical Siemens AG
Priority to DK98117163T priority Critical patent/DK0902404T3/da
Publication of EP0902404A2 publication Critical patent/EP0902404A2/fr
Publication of EP0902404A3 publication Critical patent/EP0902404A3/fr
Application granted granted Critical
Publication of EP0902404B1 publication Critical patent/EP0902404B1/fr
Anticipated expiration legal-status Critical
Expired - Lifetime legal-status Critical Current

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Classifications

    • 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 determining Road routes, especially related to highways. Traffic information.
  • DE-P 44 08 547 describes a method for traffic detection and traffic situation detection on highways, preferably Motorways, known.
  • Measuring cross-sections are set up for track-related measuring points, with traffic sensors, such as induction loops, for vehicle detection and with a traffic data processing device are provided.
  • traffic data such as vehicle speed, traffic volume and traffic density determined and from this determined traffic parameters in one Traffic data processing formed.
  • Each form two neighboring measuring points a measuring section with a certain Length. From the traffic data of two such measuring points traffic parameters are formed.
  • These are one Speed density difference, calculated from local traffic data medium speed and traffic density, a trend factor, determined over a certain period of time from the ratio of the traffic volumes of both measuring points as well a traffic intensity trend. From this data is used a fuzzy logic the probability of a critical one Traffic situation derived. When a probability threshold is reached can then be a control signal for a Variable message signs are generated.
  • European patent application EP 0 740 280 A2 discloses one Procedures for fault detection in road traffic within of a sector to be monitored.
  • One measurement cross-section each At the beginning and end of the sector, the number is the measured data and the speed of those passing through the measurement cross sections Vehicles continuously captured during finite, consecutively numbered measuring intervals collected and cyclically to average values of traffic volume and speed condensed and after transfer of data from route stations assigned to the measurement cross sections to a central evaluation point evaluated.
  • detectors are also known, which Presence and the speed of a moving object can capture.
  • detectors work According to a passive infrared process, which can also be used with other methods can be combined.
  • No method is known to date, traffic information covering the entire area to record and evaluate. In particular no methods are known to determine the traffic information route section variable, event-oriented if necessary and enable with little data transfer effort.
  • the present invention is based on the object of providing area-wide traffic data acquisition which, with simple sensors and low data transmission effort, provides reliable and sufficiently meaningful data bases for different traffic information services.
  • this object is achieved by a method solved according to claim 1.
  • the invention enables the implementation of a step organized acquisition and processing system. Thereby can different traffic models to different Levels are applied, some of which are local, some of which are central. The advantages are that short term results can be achieved by expanding into the individual Levels are consolidated and refined. Through the dissolution there is a high level in individual subtasks or stages Degree of flexibility and reliability through the Formation of fallback levels. Through the local pre-analysis of the Traffic gives rise to extremely energy-saving, event-oriented data transmission to the parent Data processing systems or centers.
  • the invention proposes that fixed detectors positioned at junctions, nodes and the like become. It is also proposed that the Arrangement density of the fixed detectors depending is determined by traffic expectation estimates. So leave through the arrangement of many local detection systems Build comprehensive networks. It is also with the invention possible to organize an overall network structure. On traffic local detectors and critical positions Preprocessing computer arranged, preferably in radio digital technology the data to higher-level data processing systems forward or control centers. There you can then other traffic models are applied to the data.
  • Adjacent local detection cross sections can be a so-called route-related level of service in a higher-level Data processing system or one of the entire network assigned headquarters can be determined.
  • Measured data After a detector, for example a passive infrared detector, Measured data are delivered, they will preprocessed, for example by calculating mean values, Plausibility checks and trend factor determinations carried out become. From the changes in the data or the data state codes themselves are then determined, for example in the form of a numerical value for conditions such as free traffic flow, Traffic jam, stop and go, traffic jam or standstill etc. Evaluation cycles can, for example, every 1 to 5 minutes to get voted. However, the evaluation cycle can be variable be determined, for example depending on the status codes or the traffic conditions. For example there is a transmission every 30 minutes with free flow of traffic with averaging every 5 minutes. Depending on the fault condition the transmission density can be increased. In doing so the data transmission rates of neighboring acquisition cross sections matched to each other.
  • a detector for example a passive infrared detector
  • the measured values can be recorded in relation to lanes, but what is not absolutely necessary, other acquisition cross sections can also be used To be defined. It is also fundamental possible, vehicle type differentiation values, for example Detect trucks, cars and the like.
  • the invention proposes that superordinate data processing systems at least for those grouped together neighboring detection cross sections can be assigned.
  • a control center can act as a higher-level data processing system for all acquisition cross sections of a network or for several higher-level data processing systems can be assigned.
  • the network organization can be done in whatever stages flexibility and data security are affected. Here economic parameters can be used as a boundary condition become.
  • source-to-target relationships by analyzing the data of all acquisition cross sections of a network determines that the data for route search, evaluated for the output of traffic management information, subjected to statistical analysis for clarification and that the data for making traffic development forecasts be evaluated.
  • the invention provides methods for different Types and qualities of traffic information data to provide.
  • the main task is to provide such data prepare for the motor vehicle driver and this provide appropriate information. It can be for example, travel time displays, route displays, traffic forecast, Act traffic jams and the like.
  • Information displays are used in the individual vehicles, for example arranged on which the motor vehicle driver their planned routes and travel time information are displayed to get. You can then, for example, under different Alternatives choose the fastest route. Additionally or alternatively, indications of traffic jam developments, Probabilities related to further development on the upcoming route section and the like are displayed. The range of applications is extensive.
  • the invention provides an extremely flexible method, with which with the connection of different traffic models an almost network-wide, nationwide Traffic information system is buildable, which data for provides a wide variety of information purposes. It can be conventional and already known models and processes are used and be combined. Forecasts can be curve-based Forecasts at measuring points, model-based forecasts for Sections and meshes and additions of immeasurable effects using artificial intelligence. For the calculation Standard formulas of average values are used. Trend factors can, for example, use the extrapolation method based on the quadratic extrapolation of Lewandowski (1974).
  • the traffic volume is determined over time. It results the so-called traffic strength curve, which is found in vehicles per hour from 1-minute measurements.
  • the Figure shows the unsmoothed and the exponentially smoothed Values for a two-lane motorway cross-section.
  • the Figure shows the effect of smoothing on the fluctuation range of the measured values.
  • the smoothing is done exponentially.
  • Figures 1 to 3 show very clearly that at the beginning of a strongly increasing traffic volume a sharp drop in speed takes place and to a very high traffic density leads, which begins to normalize again over time.
  • Figures 4 and 5 show the course of a linear Trend factor of a trend calculation over the day. Here shows that in particular with inhomogeneous traffic flow, for example at night or in the event of faults, the trend factor is one has high fluctuation range. This is also confirmed according to Figure 5, in which the change in linear trend is listed.
  • Figures 6 and 7 represent so-called fundamental diagrams for two different cross-sections.
  • fundamental diagrams the speed v over the traffic volume q applied.
  • the letters A to F are six different ones Quality levels are shown, where A is a free Traffic corresponds, F to a traffic jam.
  • D it happens already Stop-and-go or viscous traffic signs that as are to be viewed critically.
  • the illustrations show how with the method according to the invention concrete values related to the measuring point recorded respectively calculated and related to cross-section or route Condition values or quality levels processed further become. All recorded, calculated and processed Data and results are now available to the To provide road users with relevant traffic information. For example, travel times for planned Calculate routes or different alternative routes and represent. Corresponding warnings and Provide forecasts, including forecast probabilities.

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  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)
  • Circuits Of Receivers In General (AREA)
  • Devices For Checking Fares Or Tickets At Control Points (AREA)
  • Crystals, And After-Treatments Of Crystals (AREA)
  • Nitrogen And Oxygen Or Sulfur-Condensed Heterocyclic Ring Systems (AREA)

Claims (22)

  1. Procédé de détermination d'informations concernant le trafic sur des tronçons de routes, en particulier sur des autoroutes, selon lequel des lignes transversales d'enregistrement locales sont formées par des détecteurs fixes, des valeurs mesurées liées au trafic sont enregistrées, prétraitées à l'aide d'ordinateurs locaux et, en étant normées selon un protocole de données prédéfini, et agrégées, sont transférées à une installation de traitement des données hiérarchiquement supérieure,
    caractérisé en ce que, à partir des données déterminées, des codes d'état qui représentent des étages de qualité du trafic sont déterminés en cadence et le transfert des données à l'installation de traitement des données hiérarchiquement supérieure est réalisé par transmission sans fil, le taux de transfert de données étant fixé en fonction des codes d'état et les taux de transfert de données étant comparés à des lignes transversales d'enregistrement voisines.
  2. Procédé selon la revendication 1, caractérisé en ce que des détecteurs fixes sont placés à des accès d'autoroute, à des carrefours et à d'autres endroits.
  3. Procédé selon l'une des revendications précédentes, caractérisé en ce que la densité selon laquelle on dispose les détecteurs fixes est déterminée en fonction des estimations prévues du trafic.
  4. Procédé selon l'une des revendications précédentes, caractérisé en ce que, pour prétraiter localement les données, on vérifie leur vraisemblance par comparaison à des modèles.
  5. Procédé selon l'une des revendications précédentes, caractérisé en ce que, pour prétraiter localement les données, on calcule des moyennes.
  6. Procédé selon l'une des revendications précédentes, caractérisé en ce qu'on établit des facteurs de tendance à partir de la modification des valeurs mesurées.
  7. Procédé selon l'une des revendications précédentes, caractérisé en ce qu'on enregistre la vitesse du véhicule, la densité de la circulation et l'occupation pour servir de valeurs mesurées.
  8. Procédé selon l'une des revendications précédentes, caractérisé en ce que les valeurs mesurées sont enregistrées en se référant à des voies de circulation.
  9. Procédé selon l'une des revendications précédentes, caractérisé en ce que, pour servir de valeur mesurée, on enregistre des valeurs qui différencient les types de véhicule.
  10. Procédé selon l'une des revendications précédentes, caractérisé en ce que le cycle d'exploitation des données est déterminé de façon variable.
  11. Procédé selon l'une des revendications précédentes, caractérisé en ce qu'on associe des installations de traitement des données hiérarchiquement supérieures au moins à des lignes transversales d'enregistrement voisines rassemblées en groupes.
  12. Procédé selon l'une des revendications précédentes, caractérisé en ce que, pour servir d'installation de traitement des données hiérarchiquement supérieure, on associe une centrale à toutes les lignes transversales d'enregistrement d'un réseau ou à plusieurs installations de traitement des données hiérarchiquement supérieures.
  13. Procédé selon l'une des revendications précédentes, caractérisé en ce que, dans au moins une installation de traitement des données hiérarchiquement supérieure, des informations sur le trafic en fonction du trajet sont calculées en combinant les données transférées provenant de lignes transversales d'enregistrement voisines.
  14. Procédé selon l'une des revendications précédentes, caractérisé en ce que des séquences de données calculées sont vérifiées ou corrigées en effectuant des comparaisons à des modèles prédéfinis.
  15. Procédé selon l'une des revendications précédentes, caractérisé en ce que les données sont exploitées centralement pour reconnaítre des cas de perturbation.
  16. Procédé selon l'une des revendications précédentes, caractérisé en ce que les rapports source / cible sont établis en analysant les données de toutes les lignes transversales d'enregistrement d'un réseau.
  17. Procédé selon l'une des revendications précédentes, caractérisé en ce que les données sont exploitées pour rechercher un itinéraire.
  18. Procédé selon l'une des revendications précédentes, caractérisé en ce que les données sont exploitées pour produire des informations destinées à contrôler le trafic.
  19. Procédé selon l'une des revendications précédentes, caractérisé en ce que les données sont exploitées pour émettre des pronostics sur l'évolution de la circulation.
  20. Procédé selon l'une des revendications précédentes, caractérisé en ce que les données sont exploitées pour produire des informations sur la durée du voyage.
  21. Procédé selon l'une des revendications précédentes, caractérisé en ce que les données sont exploitées pour produire des informations sur les embouteillages.
  22. Procédé selon l'une des revendications précédentes, caractérisé en ce que les données sont utilisées pour préciser des analyses statistiques.
EP98117163A 1997-09-11 1998-09-10 Procédé de détermination d'information sur le trafic Expired - Lifetime EP0902404B1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
DK98117163T DK0902404T3 (da) 1997-09-11 1998-09-10 Fremgangsmåde til bestemmelse af trafikinformation

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE19739737 1997-09-11
DE19739737 1997-09-11

Publications (3)

Publication Number Publication Date
EP0902404A2 EP0902404A2 (fr) 1999-03-17
EP0902404A3 EP0902404A3 (fr) 2000-08-23
EP0902404B1 true EP0902404B1 (fr) 2004-11-17

Family

ID=7841874

Family Applications (1)

Application Number Title Priority Date Filing Date
EP98117163A Expired - Lifetime EP0902404B1 (fr) 1997-09-11 1998-09-10 Procédé de détermination d'information sur le trafic

Country Status (6)

Country Link
EP (1) EP0902404B1 (fr)
AT (1) ATE282872T1 (fr)
DE (1) DE59812267D1 (fr)
DK (1) DK0902404T3 (fr)
ES (1) ES2231931T3 (fr)
PT (1) PT902404E (fr)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE10246184A1 (de) * 2002-10-02 2004-09-30 Bayerische Motoren Werke Ag Verfahren zur Güteverbesserung von Verkehrsstörungsmeldeverfahren
CN102289932B (zh) * 2011-06-17 2013-10-23 同济大学 基于车辆自动识别设备的动态od矩阵估计方法

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0740280A2 (fr) * 1995-04-28 1996-10-30 INFORM Institut für Operations Research und Management GmbH Méthode de détection des pertubations pour trafic routièr

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5289183A (en) * 1992-06-19 1994-02-22 At/Comm Incorporated Traffic monitoring and management method and apparatus
SE9203474L (sv) * 1992-11-19 1994-01-31 Kjell Olsson Sätt att prediktera trafikparametrar
DE4408547A1 (de) * 1994-03-14 1995-10-12 Siemens Ag Verfahren zur Verkehrserfassung und Verkehrssituationserkennung auf Autostraßen, vorzugsweise Autobahnen

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0740280A2 (fr) * 1995-04-28 1996-10-30 INFORM Institut für Operations Research und Management GmbH Méthode de détection des pertubations pour trafic routièr

Also Published As

Publication number Publication date
EP0902404A3 (fr) 2000-08-23
PT902404E (pt) 2005-02-28
DK0902404T3 (da) 2005-01-31
ES2231931T3 (es) 2005-05-16
EP0902404A2 (fr) 1999-03-17
DE59812267D1 (de) 2004-12-23
ATE282872T1 (de) 2004-12-15

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