EP0903711A2 - Procédé de transmission d'information sur le trafic - Google Patents

Procédé de transmission d'information sur le trafic Download PDF

Info

Publication number
EP0903711A2
EP0903711A2 EP98117283A EP98117283A EP0903711A2 EP 0903711 A2 EP0903711 A2 EP 0903711A2 EP 98117283 A EP98117283 A EP 98117283A EP 98117283 A EP98117283 A EP 98117283A EP 0903711 A2 EP0903711 A2 EP 0903711A2
Authority
EP
European Patent Office
Prior art keywords
data
traffic
section
detection
mml
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Withdrawn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
EP98117283A
Other languages
German (de)
English (en)
Other versions
EP0903711A3 (fr
Inventor
Thomas Sachse
Fritz Dr. Busch
Andrea Ghio
Johannes Konrad
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
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Siemens AG filed Critical Siemens AG
Publication of EP0903711A2 publication Critical patent/EP0903711A2/fr
Publication of EP0903711A3 publication Critical patent/EP0903711A3/fr
Withdrawn legal-status Critical Current

Links

Images

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 traffic information related to motorways, local detection cross sections by means of fixed detectors formed, traffic-related measured values recorded, preprocessed by means of local computers and to a given one Data protocol standardized, aggregated and sent by radio a higher-level data processing system is transferred, wherein the transmitted data in at least one calculation method edited to determine traffic information whose input data is at least vehicle speed v and traffic volume q are and that as the starting data at least cruising speed and traffic density k can produce on a detection cross section.
  • DE-P 44 08 547 describes a method for traffic detection and traffic situation detection on highways, preferably Motorways, known.
  • 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 Track 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 the ratio of the traffic volumes of both measuring points as well a traffic intensity trend.
  • Using a Fuzzy logic the probability of a critical traffic situation derived. When a probability threshold is reached can then be a control signal for a Variable message signs are generated.
  • 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. Especially no methods are known to determine the traffic information route section variable, event-oriented if necessary and enable with little data transfer effort.
  • a low data transmission effort is on the one hand Implementation of an energy-saving process required on the other hand, as transparent and easy to maintain as possible Generate databases.
  • An essential aspect of the present invention is the optimal one Evaluation and further processing of the received data in a central unit to the from an economic point of view data collected and sent so comprehensive and To process as meaningfully as possible, but also to achieve results to arrive, the meaning of which is so clear and is as safe as possible.
  • the present invention is based on the object of providing an area-wide traffic data acquisition of the generic type, through which reliable and sufficiently meaningful data bases for different traffic information services are provided with simple sensors and low data transmission and energy expenditure, in such a way that the recorded ones and sent data are analyzed and processed as comprehensively and meaningfully as possible, and the results are as clear and reliable as possible.
  • the invention proposes a method for determining traffic information relating to road routes, in particular motorways, wherein local detection cross sections are formed by means of fixed detectors, traffic-related measured values are recorded, preprocessed by means of local computers and standardized, aggregated and per using a predetermined data protocol are transmitted wirelessly to a higher-level data processing system, the transmitted data being processed in at least one calculation method for determining traffic information, the input data of which are at least vehicle speed v and traffic intensity q and which can produce at least travel speed and traffic density k on a detection cross section as output data, and wherein the data then in at least one complex extended processing method for determining traffic information related to routes mations are processed further.
  • the invention enables the implementation of a step organized processing system, being short term Results can be achieved by expanding into the individual levels can be consolidated and refined. By the resolution into individual subtasks or stages results a high degree of flexibility and reliability through the formation of fallback levels. Through the local pre-analysis of traffic there are opportunities to extreme energy-saving, event-oriented data transmission too the higher-level data processing systems or centers.
  • Fixed detectors are preferably used at connection points, Positioned nodes and the like. Furthermore the arrangement density of the fixed detectors becomes dependent determined by traffic expectation estimates. Consequently can be arranged by arranging many local detection systems Build comprehensive networks. With the invention it is also possible to organize an overall network structure. On Local detectors become critical traffic positions and preprocessor arranged by radio in preferably digital technology, the data to superordinate ones Forward data processing systems or centers. Further traffic models can then be applied to the data there become.
  • 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 are determined.
  • Measured data After a detector, for example a passive infrared detector, Measured data are delivered, they will be 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. The same applies the data transfer rate, which depends, for example of the determined status code is used, for example one transmission every 30 minutes when traffic is free with averaging every 5 minutes. Depending on the fault condition the transmission density can be increased. In doing so the data transfer rates of adjacent acquisition cross sections matched to each other.
  • a detector for example a passive infrared detector
  • Measured data are delivered, they will be preprocessed, for example by calculating mean values, Plaus
  • the measured values can be recorded in relation to the lane, but what is not absolutely necessary, other detection 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.
  • 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 to 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 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 by linking 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.
  • the transmitted data can be calculated in two ways of different complexity. It is provided that one of the at least two calculation methods a simple interpolation procedure of low complexity is.
  • the input data of the calculation process is lower Complexity is vehicle speed v and traffic volume q, baseline data are cruising speed and traffic density k. It is also provided that the calculation method low complexity an additional traffic jam message issues.
  • a procedure as described requires only a minimum of input data and can be very reliable very quickly Statements about the traffic condition in the area of a measurement cross section to meet. The interpolation becomes simplistic assumed that all vehicles behave the same.
  • Another calculation method can be based on data analysis process based on a fundamental diagram high complexity.
  • Is a fundamental diagram a known curve related to a measurement cross section.
  • the display is the curve of traffic q above the assignment k.
  • the curve corresponds in simplified and heavily smoothed form essentially an asymmetrical Gaussian distribution and leaves statements about critical and uncritical States too.
  • Input data of the calculation method high Complexity is vehicle speed v, traffic volume q and occupancy b, output data related to a travel tent Cruising speed and traffic density k.
  • the calculation method of high complexity additionally a traffic situation status signal, at least differentiates according to free / critical / traffic jam. This too the second method requires only a minimum of input data and can very quickly make very reliable statements about traffic conditions meet in the area of a measuring cross-section.
  • the redundant application of at least two methods increased significantly increases security and enables a review of the Quality results.
  • the present invention begins at this point and relates focus on analyzing the data for larger sections of the transport network. It is suggested that the transmitted data in at least a third, highly complex Calculation method for an advanced situation detection to be edited. The results are also included of the previous calculation methods.
  • the highly complex Methods of extended situation detection are expanded Called machining process.
  • the invention proposes that the advanced processing method fuzzy logic is used, to create an interpretation symbol from the preprocessed data the current traffic flow and an associated probability to determine.
  • the symbols of interpretation and probabilities be linked using a locking matrix.
  • One of the sensible upstream individual processes provides that by means of a further extended processing method based on the at a detection cross section determined data the traffic flow data until the next Acquisition cross section using a traffic model estimated with the closest acquisition cross section determined corresponding data compared and from the deviations Correction values determined and in a next one Estimation cycle are introduced. It is advantageously proposed that that the distance between one and the next detection cross section is segmented. The segment number and segment length is not without influence and are parameter dependent definable. It is also proposed that the correction values as a parameter in the basis of the estimate Traffic model can be introduced. Another advantage is that Invention that the captured, determined and estimated Values supplemented by the simulated values of a fictitious fault location become.
  • fuzzy logic is used. This can be used specifically for fault identification be used. It is advantageous that the further advanced machining process, which using Fuzzy logic determines faults from the preprocessed data, the advanced machining process with use Upstream of the filter estimation technology from the data flow point of view becomes.
  • the invention proposes that neuro-fuzzy logic be used becomes.
  • the following example deals with traffic engineering Evaluation of a new procedure with the help of a before and after examination on the A9 federal highway, between Eching and pine garden (Photo 1).
  • the installed there conventional procedure for accident detection was used as a reference used.
  • the real traffic data on this test route were captured using the (multi-model logic) MML method to test off-line.
  • video recordings were made carried out, e.g. analyzing police accident reports, to make an objective review.
  • the following Explanation describes the methodical procedure the traffic evaluation, provides the results obtained and leads the conclusion of the example from.
  • the MML procedure for extended situation detection should be compared to the conventional method with regard to the defined evaluation indicators.
  • the appropriate topological scope of the MML method should be estimated where possible. In particular, it should be checked how the Increasing the distance between adjacent measuring cross sections on the detection quality of the to be compared Impact procedures.
  • the basic concept of the MML process is integration various new ones developed recently Methods for automatic situation detection. Because the individual Methods can complement each other is expected that the quality of the integrated process to expand Situation detection (ESE) is increased overall.
  • ESE Situation detection
  • the MML method is able to handle the following critical situations to recognize and distinguish:
  • a situation is defined as a traffic bottleneck at which the number of available lanes due to a traffic event, e.g. an accident or a broken down vehicle, reduced, and yourself as a result, a jam is formed within the section Has.
  • a section is blocked when the traffic density in the entire section exceeds a defined size and the speed at the two section boundaries falls below the defined size.
  • the three-lane was used to record the required data Route of the A9 between Eching (KM 514,830) and Kieferngarten (KM 525,000), direction Kunststoff included as test field (Image 1). With four exits (Eching, Garching-Nord, Garching-Süd and pine garden) and the motorway junction Munich-North this route is heavily burdened. In particular, traffic jams are often during the morning hours to observe.
  • the traffic data were measured by, video, or police record of the accident.
  • the police accident log was under investigation the defined system features as an objective basis for assessment used. It was also used as a basis used for the selection of traffic data. (Because of the The available logs could easily represent the accident however, they are used only to a limited extent.)
  • Video recording is another source of information to form the basis of assessment (e.g. confirmation of a fault recognized by the system).
  • a suitable video recording can provide adequate and reliable information deliver about the real traffic situations. In The video recordings were therefore agreed with the client carried out in two places for several days.
  • the measured data (minute values of speed and traffic volume ) were used in the context of the present work to carry out the off-line tests.
  • the same traffic data was used to determine the defined characteristics of the methods to be compared. This enables a real comparison of the procedures.
  • the measurement data were recorded for a total of 22 days (see Table 3).
  • the system data are used to determine the system reactions on traffic situations.
  • the data acquisition was essentially carried out by Siemens. Table 2 gives an overview of the data collected. Overview of the data collected Data type Recorded data Measurement data May 2nd, May 3rd, May 13th, May 19th, May 24th, May 27th, May 29th, June 2nd, June 8th, June 14th, June 22nd, June 25th, June 29th, July 2nd, August 25th, 02.09., 04.10., 09.10., 10.10., 16.10.-31.12. 01.01.-29.02.
  • FL system data May 2nd, May 3rd, May 13th, May 19th, May 24th, May 27th, May 29th, June 2nd, June 8th, June 14th, June 22nd, June 25th, June 29th, July 2nd, August 25th, 02.09., 04.10., 09.10., 10.10., 16.10.-31.12. 01.01.-29.02.
  • FIG. 3 shows the course of the fault indicators as an example STk, STf, STkal or STm of the conventional, FL, Kalman filter, or MML procedure and the EZk, EZf or EZm: Detection time of the conventional, FL or MML method represented a malfunction.
  • Table 4 gives an overview of the evaluated events.
  • the expected value of the difference between the recognition tents lies in the range between 7.45 and 11.59 minutes.
  • the MML method can thus increase the recognition time of the conventional Shorten the procedure significantly. According to the present Examination can be carried out by anyone using the MML procedure Incident an average of 616 vehicles (potential traffic jams) additionally be warned what a considerable Increased traffic safety means. The earlier detection The accidents can also potentially cause the traffic jam situation improve if e.g. a corresponding traffic control or - Information system for alternate signage, route recommendation or is also available for pre-trip travel planning.
  • the aim should be to choose the necessary distance between adjacent measuring cross-sections so that a reasonable compromise between the number of measuring cross-sections on the one hand and the achievable detection quality of the system on the other hand is achieved.
  • a corresponding random check was carried out, cf. Table 5. Representation of the sections with increased distance between measuring cross sections
  • Cross section MQ kilometers Section length [m] MQ1 514,830 3830 MQ3 518.660 2170 MQ5 520.830 1940 MQ8 522,770 1240 MQ9 524.010 1600 MQ11 525.610
  • KS> 30 0 ⁇ m KS> 40 0 ⁇ m KS> 50 0 ⁇ m KS> 60 0 um KS> 70 0 ⁇ m MQ1-MQ3 07.11 8:47 8:45 - - - - MQ1-MQ3 07.11 9:39 9:40 9:40 9:40 9:40 MQ1-MQ3 07.11 - 9:11 - - - - MQ1-MQ3 07.11 - 9:23 - - - - MQ1-MQ3 16.02 6:15 6:17 6:17 6:17 6:17 6:17 MQ1-MQ3 16.02 - 6:52 6:52 6:53 6:53 MQ1-MQ3 28.02 6:53 - - - - MQ1-MQ3 28.02 6:53 - - - - MQ1-MQ3 28.02 6:53 - - - - MQ1
  • the results of the analysis show that in the exemplary considered situations out of the 15 accidents involving the MML process detected at normal distance from Kalman filter 11 can be detected at about the same time even at a greater distance (this corresponds to a detection rate of approx. 73%); Farther the method 9 detects other critical traffic conditions, that from the basic information is not an accident are classified (police report is missing, no detection by conventional or MML method), due to the data situation but clearly correspond to situations with critical traffic flow. (These cases were in the short section lengths obvious from the MML procedure in the higher-level logic sorted out because they are not clearly the pattern of a predefined one characteristic traffic situation were assignable.) The detection rate is based on the entire sample of approximately 83%.

Landscapes

  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)
EP98117283A 1997-09-18 1998-09-11 Procédé de transmission d'information sur le trafic Withdrawn EP0903711A3 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE19741229 1997-09-18
DE19741229 1997-09-18

Publications (2)

Publication Number Publication Date
EP0903711A2 true EP0903711A2 (fr) 1999-03-24
EP0903711A3 EP0903711A3 (fr) 2000-08-23

Family

ID=7842850

Family Applications (1)

Application Number Title Priority Date Filing Date
EP98117283A Withdrawn EP0903711A3 (fr) 1997-09-18 1998-09-11 Procédé de transmission d'information sur le trafic

Country Status (1)

Country Link
EP (1) EP0903711A3 (fr)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19856704A1 (de) * 1998-12-09 2000-06-21 Daimler Chrysler Ag Verfahren und Vorrichtung zur Fahrzeugzielführung und/oder Reisezeitschätzung
EP1118972A2 (fr) * 2000-01-19 2001-07-25 DDG Gesellschaft für Verkehrsdaten mbH Allocation stable des messages routiers et de leurs informations additionelles indicatives de leur origine
DE10036364A1 (de) * 2000-07-18 2002-02-07 Ddg Ges Fuer Verkehrsdaten Mbh Verfahren zur Erstellung prognostizierter Verkehrsdaten für Verkehrsinformationen
CN109285344A (zh) * 2018-06-25 2019-01-29 江苏智通交通科技有限公司 交通高危人员重点监测对象识别方法和智能决策系统
DE102020105527A1 (de) 2020-03-02 2021-09-02 Bayerische Motoren Werke Aktiengesellschaft Verfahren und system zum ermitteln von ursachen für eine verkehrsstörung

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0256483A1 (fr) * 1986-08-13 1988-02-24 Siemens Aktiengesellschaft Système pour guider et informer le trafic
WO1994011839A1 (fr) * 1992-11-19 1994-05-26 Kjell Olsson Procede de prevision de parametres de circulation
DE4408547A1 (de) * 1994-03-14 1995-10-12 Siemens Ag Verfahren zur Verkehrserfassung und Verkehrssituationserkennung auf Autostraßen, vorzugsweise Autobahnen

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0256483A1 (fr) * 1986-08-13 1988-02-24 Siemens Aktiengesellschaft Système pour guider et informer le trafic
WO1994011839A1 (fr) * 1992-11-19 1994-05-26 Kjell Olsson Procede de prevision de parametres de circulation
DE4408547A1 (de) * 1994-03-14 1995-10-12 Siemens Ag Verfahren zur Verkehrserfassung und Verkehrssituationserkennung auf Autostraßen, vorzugsweise Autobahnen

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
RITTICH D ET AL: "PERSPEKTIVEN DER VERKEHRSLEITTECHNIK" NACHRICHTENTECHNISCHE BERICHTE,DE,ANT NACHRICHTENTECHNIK GMB. BACKNANG, Nr. 9, 1. April 1992 (1992-04-01), Seiten 111-119, XP000331875 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19856704A1 (de) * 1998-12-09 2000-06-21 Daimler Chrysler Ag Verfahren und Vorrichtung zur Fahrzeugzielführung und/oder Reisezeitschätzung
DE19856704C2 (de) * 1998-12-09 2001-09-13 Daimler Chrysler Ag Verfahren und Vorrichtung zur Fahrzeugzielführung und/oder Reisezeitschätzung
EP1118972A2 (fr) * 2000-01-19 2001-07-25 DDG Gesellschaft für Verkehrsdaten mbH Allocation stable des messages routiers et de leurs informations additionelles indicatives de leur origine
EP1118972A3 (fr) * 2000-01-19 2002-07-17 DDG Gesellschaft für Verkehrsdaten mbH Allocation stable des messages routiers et de leurs informations additionelles indicatives de leur origine
DE10036364A1 (de) * 2000-07-18 2002-02-07 Ddg Ges Fuer Verkehrsdaten Mbh Verfahren zur Erstellung prognostizierter Verkehrsdaten für Verkehrsinformationen
DE10036364C2 (de) * 2000-07-18 2003-08-28 Ddg Ges Fuer Verkehrsdaten Mbh Verfahren zur Erstellung prognostizierter Verkehrsdaten für Verkehrsinformationen
CN109285344A (zh) * 2018-06-25 2019-01-29 江苏智通交通科技有限公司 交通高危人员重点监测对象识别方法和智能决策系统
CN109285344B (zh) * 2018-06-25 2021-05-28 江苏智通交通科技有限公司 交通高危人员重点监测对象识别方法和智能决策系统
DE102020105527A1 (de) 2020-03-02 2021-09-02 Bayerische Motoren Werke Aktiengesellschaft Verfahren und system zum ermitteln von ursachen für eine verkehrsstörung

Also Published As

Publication number Publication date
EP0903711A3 (fr) 2000-08-23

Similar Documents

Publication Publication Date Title
EP0879460B1 (fr) Procede et dispositif pour l'obtention de donnees relatives a une situation de trafic
EP0740280B1 (fr) Méthode de détection des pertubations pour trafic routièr
EP0798684B1 (fr) Procédé et système de saisie de situation de la circulation par un dispositif fixe de saisie de données
EP0750774B1 (fr) Procede de detection du trafic et de situations de trafic sur des axes routiers, de preference sur des autoroutes
DE102008021260A1 (de) Verfahren zur Güteprüfung von Verkehrsstörungsmeldeverfahren
EP0978811A2 (fr) Procédé et appareil de saisie de durée de trajets de véhicules
DE102017217450A1 (de) Verfahren zur Zustandsbestimmung von wenigstens einer entlang einer Fahrstrecke verlaufenden Fahrleitung
EP2811466B1 (fr) Procédé et dispositifs de détection des erreurs dans un système de péage
EP0903711A2 (fr) Procédé de transmission d'information sur le trafic
EP1659550A2 (fr) Procédé pour détecter des données de traffic
EP0902405B1 (fr) Procédé d'investigation d'information sur le trafic
DE4328939C2 (de) Verfahren zur Erfassung von streckenbezogenen Verkehrsgrößen
EP0902404B1 (fr) Procédé de détermination d'information sur le trafic
CH697821B1 (de) Verfahren zum Ermitteln des Verkehrszustandes auf einem Streckenabschnitt eines Strassennetzes sowie Verkehrsmanagementzentrale zur Durchführung des Verfahrens.
EP3655934B1 (fr) Concept de surveillance d'un espace de stationnement
DE19944891A1 (de) Verkehrslageerfassung mit Fuzzy-Klassifikation und mehrdimensionaler morphologischer Datenfilterung und dynamischer Domänenbildung
EP0908861A2 (fr) Procédé de transmission d'information sur le trafic
DE102020105527A1 (de) Verfahren und system zum ermitteln von ursachen für eine verkehrsstörung
EP0654771A1 (fr) Procédé pour éviter les fausses alarmes dans un système de détection d'incendie et dispositif pour la réalisation de la méthode
EP1280118B1 (fr) Procédé pour déterminer des situations de la circulation routière
EP0753444B1 (fr) Procédé pour la détection d'erreurs pour compteurs d'essieux à sections multiples
EP0902403B1 (fr) Procédé de détection d'information sur le trafic
EP1413999B1 (fr) Méthode de génération d'informations implicites à partir de données de véhicules flottants
EP2887332A1 (fr) Procédé et système de détermination d'une situation de trafic sur une voie de circulation
DE2911734A1 (de) Verfahren zur messung von verkehrsstoerungen

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

AK Designated contracting states

Kind code of ref document: A2

Designated state(s): AT BE CH CY DE DK ES FI FR GB GR IE IT LI LU MC NL PT SE

AX Request for extension of the european patent

Free format text: AL;LT;LV;MK;RO;SI

PUAL Search report despatched

Free format text: ORIGINAL CODE: 0009013

AK Designated contracting states

Kind code of ref document: A3

Designated state(s): AT BE CH CY DE DK ES FI FR GB GR IE IT LI LU MC NL PT SE

AX Request for extension of the european patent

Free format text: AL;LT;LV;MK;RO;SI

17P Request for examination filed

Effective date: 20010219

AKX Designation fees paid

Free format text: AT BE CH CY DE DK ES FI FR GB GR IE IT LI LU MC NL PT SE

17Q First examination report despatched

Effective date: 20031013

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION IS DEEMED TO BE WITHDRAWN

18D Application deemed to be withdrawn

Effective date: 20040423