EP1406226A2 - Verfahren zur Güteverbesserung von Verkehrsstörungsmeldeverfahren - Google Patents
Verfahren zur Güteverbesserung von Verkehrsstörungsmeldeverfahren Download PDFInfo
- Publication number
- EP1406226A2 EP1406226A2 EP03016767A EP03016767A EP1406226A2 EP 1406226 A2 EP1406226 A2 EP 1406226A2 EP 03016767 A EP03016767 A EP 03016767A EP 03016767 A EP03016767 A EP 03016767A EP 1406226 A2 EP1406226 A2 EP 1406226A2
- Authority
- EP
- European Patent Office
- Prior art keywords
- traffic
- quality indicator
- traffic flow
- measurement data
- quality
- 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.)
- Granted
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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 traffic disturbance reporting methods and more particularly to the rating and optimization of such methods.
- Such traffic disturbance reporting procedures take into account through processing locally measured data the spatial and temporal evolution of the traffic flow and apply the knowledge gained in the form of control algorithms for route control systems and alternate route systems on the one hand and for the automatic generation of traffic jamming messages, on the other hand around.
- These messages are e.g. distributed by radio or by mobile phone.
- the invention relates to a method for improving the quality of traffic jam reporting methods, especially with the aim to optimize this quality. This will achieved an improvement in traffic flow. This happens in several ways.
- a reliable, i. spatially and temporally precise error notification provided This leads to the fact that the disturbance location is avoided if possible. For the road user exposed to the disturbance this also means a relief, as the inflow of other road users in the fault area decreases with the result of being able to leave the fault area faster again.
- the automatic generation of traffic reports usually precedes a traffic jamming detection method in which measurement data from one or more several measuring stations, for example on induction loops, video cameras, Infrared detectors and the like access to be provided. These Measurement data may be in the form of time-averaged velocities, for example. time-averaged traffic densities, count rates of vehicles and the like available. Traffic disturbance detection methods determine from these data Switching states that make up the traffic disruption messages in a traffic control center be derived automatically.
- FCD vehicle-generated data
- FCD i.d.R. to messages that be obtained from vehicles and communicated by air to a central office become.
- the vehicles function as "floating" in this mode Sensors. (see DE 10064934 A).
- the pearl necklace contains i.d.R. estimates obtained from GPS signals a time series of georeferenced positions (i.e., a timestamp per point and latitude and longitude).
- the data processing chain is endeavored by the so-called data fusion from several independent sources the blurring and error rates reduce and complete the incomplete information.
- data fusion from several independent sources the blurring and error rates reduce and complete the incomplete information.
- FCD Fibre Channel
- traffic data from stationary detection devices which are used, for example, in traffic control systems, be used.
- the spatial density and temporal frequency of detection and transmission is directly related to quality the information that results from the data refinement.
- the driving variables along a route can affect, in particular the travel time or the potential danger, such as due to sharp speed gradients, understand.
- navigation services in the vehicle is not just the current traffic situation, but also the future traffic situation of interest, because the ride will take place in the future.
- traffic forecasts called generated.
- a traffic forecast can be calculated, for example, on the basis of traffic flow models. The Traffic forecast goes but with additional blurring, incompleteness, and Associated error rates, which is usually the degradation of information quality increases with increasing forecast horizon.
- Communication channels also influence the quality of the traffic reports. Because The traffic is a highly dynamic system, so that any delay in the Initially, a message chain means a loss of up-to-dateness. There Delays due to the communication channels but unavoidable, it is possible and also useful to use traffic forecasts to even these delays to compensate. The above-mentioned degradation of information quality through the additional forecasting horizon represents a lesser evil than the neglect of delays.
- the object of the invention is to provide a method which has an automatic rating and optimization of traffic jamming notification procedures.
- a quality indicator is determined, which is a measure It provides, how well the assignment of traffic reports to the actual Traffic disruption is.
- FCD is about Messages that are obtained from vehicles and the airway to a Central will be communicated. These data will be referred to as "XFCD” below.
- the test vehicles are on the track with a predetermined clocking cleverly.
- the vehicles are equipped with telephone cards. These serve for Transmission of XFCD to a central computer.
- the stationary traffic data is spatially and temporally selected for all Routes sorted and smoothed at 15-minute intervals.
- FIG. 1 this is the example of the BAB A9 Kunststoff driving direction Nuremberg for the Illustrated March 11, 2002.
- FIG. 1 shows a spatio-temporal representation of FIG Minutes aggregated velocity field v (x, t).
- This (representation) figure R1 is representative of the existing traffic jam.
- the speeds are linearly interpolated and a contour line calculated at 50 km / h. It results in a continuous Space-time velocity field that represents the real traffic flow.
- Fig. 1 and Fig. 2 are two-dimensional, the actual and the from the Traffic reports derivable traffic events over the measuring cross-section and plotted based on the respective time of day.
- the appropriate motorway junctions AS are supplemented.
- the 7:45 starts and has a constant length between 8:00 and 9:30 and from km 11 (according to AS Garching south) to AS M-Freimann enough and also against 9:45 dissolves.
- QKZ1 Intersection of events and messages as a percentage of events
- QKZ 2 1 - ( intersection Events and messages) (Total messages) in percent
- QKZ1 means the measure of the coverage of the figurehead of Fig. 1 for the actual traffic (congestion) events by which the traffic reports resulting representation figure and QKZ2 outside the Representation figure R1 lying amounts of the figurehead R2, related on the figurehead R2.
- the issue of traffic reports may be in cases where due to previous Analyzes for the current case a lower quality indicator QKZ1 too is expected to be blocked automatically.
- the current case be characterized by the failure of sensors.
- Essential is the possibility of changing the process chain for different General conditions the selection of the individual components of the process chain to determine that the result in the form of issued traffic jams optimal. This not only means the best possible coverage the representation figures R1 and R2, but also refers to the Use of the means effective in the process chain. For example, for the respective n Framework conditions the number and position of the effective traffic flow sensors be automatically optimized or in the event of a disruption of the process chain (eg a sensor failure) are judged how high the resulting loss of quality is.
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- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
- Monitoring And Testing Of Exchanges (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Investigating Or Analyzing Non-Biological Materials By The Use Of Chemical Means (AREA)
Abstract
Description
kein Sensorelement (Fahrzeug) ist vorhanden
die Meldung kommt nicht an
das Straßenelement wird falsch zugeordnet
die Bedingungen zur Auslösung werden nicht korrekt erkannt.
Claims (9)
- Verfahren zur Güteverbesserung von Verkehrsstörungsmeldeverfahren, bei dem zeitabhängige Verkehrsfluss-Messdaten aufgenommen und verarbeitet werden und bei dem ferner den Messdaten zeitabhängige Schaltzustände zur automatischen Ausgabe von Meldungen zur Beeinflussung des Verkehrsflusses zugeordnet werden, mit den Schritten:Speichern der Messdaten über einen vorgegebenen Auswertezeitraum,Speichern der Schaltzustände über denselben Auswertezeitraum,Vergleichen der sich aus den Messdaten ergebenden tatsächlichen Verkehrsstörungen mit den aus den Schaltzuständen ableitbaren Verkehrsstörungen,Bestimmen eines Güteindikators durch Vergleichen der tatsächlichen mit den ableitbaren Verkehrsstörungen,Verändern der aus den Schritten Aufnehmen, Verarbeiten, Zuordnen und Wiedergeben bestehenden Prozesskette mindestens an einer Stelle,Bewerten der sich als Folge dieser Änderung einstellenden Änderung des Güteindikators.
- Verfahren nach Anspruch 1, dadurch gekennzeichnet, dass die Verkehrsfluss-Messdaten von stationären Verkehrsfluss-Sensoren geliefert werden.
- Verfahren nach Anspruch 1 oder 2, dadurch gekennzeichnet, dass die Verkehrsfluss-Messdaten von mobilen Verkehrsfluss-Sensoren geliefert werden.
- Verfahren nach einem der Ansprüche 1 bis 3, dadurch gekennzeichnet, dass aus den Messdaten und den Schaltzuständen Repräsentationsfiguren gewonnen und zur Bildung des Güteindikators einander gegenübergestellt werden.
- Verfahren nach Anspruch 4, dadurch gekennzeichnet, dass als ein erster Güteindikator der Grad der gegenseitigen Bedeckung der Repräsentationsfiguren bestimmt wird.
- Verfahren nach Anspruch 4 oder 5, dadurch gekennzeichnet, dass als ein zweiter Güteindikator der Grad der Nicht-Bedeckung der Repräsentionsfiguren bestimmt wird.
- Verfahren nach Anspruch 5 oder 6, dadurch gekennzeichnet, dass die Güteindikatoren gespeichert werden.
- Verfahren nach einem der Ansprüche 4 bis 7, dadurch gekennzeichnet, dass jeder Güteindikator mit einem vorgegebenen entsprechenden Güteindikator verglichen wird.
- Verfahren nach Anspruch 8, dadurch gekennzeichnet, dass der vorgegebene Güteindikator aus der Durchführung des Verfahrens zur Güteverbesserung nach einem der Ansprüche 1 bis 8 für mehrere Zeiträume gewonnen wird, die hinsichtlich des Verkehrsflusses vergleichbare Rahmenbedingungen besitzen.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE10246184A DE10246184A1 (de) | 2002-10-02 | 2002-10-02 | Verfahren zur Güteverbesserung von Verkehrsstörungsmeldeverfahren |
DE10246184 | 2002-10-02 |
Publications (3)
Publication Number | Publication Date |
---|---|
EP1406226A2 true EP1406226A2 (de) | 2004-04-07 |
EP1406226A3 EP1406226A3 (de) | 2004-06-09 |
EP1406226B1 EP1406226B1 (de) | 2005-02-23 |
Family
ID=31984377
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP03016767A Expired - Lifetime EP1406226B1 (de) | 2002-10-02 | 2003-07-23 | Verfahren zur Güteverbesserung von Verkehrsstörungsmeldeverfahren |
Country Status (2)
Country | Link |
---|---|
EP (1) | EP1406226B1 (de) |
DE (2) | DE10246184A1 (de) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102008021260A1 (de) | 2008-04-29 | 2009-11-05 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren zur Güteprüfung von Verkehrsstörungsmeldeverfahren |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE19737440A1 (de) * | 1997-02-14 | 1998-08-27 | Mannesmann Ag | Verfahren zur Bestimmung von Verkehrsdaten und Verkehrsinformationszentrale |
EP0902404A2 (de) * | 1997-09-11 | 1999-03-17 | Siemens Aktiengesellschaft | Verfahren zur Ermittlung von Verkehrsinformationen |
DE19833614A1 (de) * | 1998-07-25 | 2000-01-27 | Bayerische Motoren Werke Ag | Verfahren zur Verkehrsqualitätserkennung und Fahrzeug als Mittel dazu |
EP1071057A1 (de) * | 1999-07-23 | 2001-01-24 | DDG Gesellschaft für Verkehrsdaten mbH | Verfahren und Vorrichtung zur Verkehrszustandsprognose durch rückgekoppelte Zustandskaskade |
EP1174842A1 (de) * | 2000-07-18 | 2002-01-23 | DDG Gesellschaft für Verkehrsdaten mbH | Verfahren zur Erstellung prognostizierter Verkehrsdaten für Verkehrsinformationen |
DE10062856A1 (de) * | 2000-12-16 | 2002-06-20 | Daimler Chrysler Ag | Verfahren zur fahrzeugindividuellen Verkehrsprognose |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE19730794A1 (de) * | 1997-07-18 | 1999-01-21 | Bosch Gmbh Robert | Verfahren und Telematikgerät zum Erstellen und Aussenden von verkehrsrelevanten Daten |
DE19944891A1 (de) * | 1998-02-19 | 2000-04-20 | Mannesmann Ag | Verkehrslageerfassung mit Fuzzy-Klassifikation und mehrdimensionaler morphologischer Datenfilterung und dynamischer Domänenbildung |
DE19937894B4 (de) * | 1999-08-15 | 2010-08-12 | Marcus Hoops | Verfahren zur Bewertung und Verfahren zur Optimierung von Verkehrsstörungserkennungsverfahren |
-
2002
- 2002-10-02 DE DE10246184A patent/DE10246184A1/de not_active Withdrawn
-
2003
- 2003-07-23 DE DE50300323T patent/DE50300323D1/de not_active Expired - Lifetime
- 2003-07-23 EP EP03016767A patent/EP1406226B1/de not_active Expired - Lifetime
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE19737440A1 (de) * | 1997-02-14 | 1998-08-27 | Mannesmann Ag | Verfahren zur Bestimmung von Verkehrsdaten und Verkehrsinformationszentrale |
EP0902404A2 (de) * | 1997-09-11 | 1999-03-17 | Siemens Aktiengesellschaft | Verfahren zur Ermittlung von Verkehrsinformationen |
DE19833614A1 (de) * | 1998-07-25 | 2000-01-27 | Bayerische Motoren Werke Ag | Verfahren zur Verkehrsqualitätserkennung und Fahrzeug als Mittel dazu |
EP1071057A1 (de) * | 1999-07-23 | 2001-01-24 | DDG Gesellschaft für Verkehrsdaten mbH | Verfahren und Vorrichtung zur Verkehrszustandsprognose durch rückgekoppelte Zustandskaskade |
EP1174842A1 (de) * | 2000-07-18 | 2002-01-23 | DDG Gesellschaft für Verkehrsdaten mbH | Verfahren zur Erstellung prognostizierter Verkehrsdaten für Verkehrsinformationen |
DE10062856A1 (de) * | 2000-12-16 | 2002-06-20 | Daimler Chrysler Ag | Verfahren zur fahrzeugindividuellen Verkehrsprognose |
Also Published As
Publication number | Publication date |
---|---|
DE50300323D1 (de) | 2005-03-31 |
DE10246184A1 (de) | 2004-09-30 |
EP1406226A3 (de) | 2004-06-09 |
EP1406226B1 (de) | 2005-02-23 |
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