EP0902405B1 - Procédé d'investigation d'information sur le trafic - Google Patents

Procédé d'investigation d'information sur le trafic Download PDF

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Publication number
EP0902405B1
EP0902405B1 EP98117164A EP98117164A EP0902405B1 EP 0902405 B1 EP0902405 B1 EP 0902405B1 EP 98117164 A EP98117164 A EP 98117164A EP 98117164 A EP98117164 A EP 98117164A EP 0902405 B1 EP0902405 B1 EP 0902405B1
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EP
European Patent Office
Prior art keywords
traffic
data
calculation
speed
section
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.)
Revoked
Application number
EP98117164A
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German (de)
English (en)
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EP0902405A3 (fr
EP0902405A2 (fr
Inventor
Thomas Sachse
Fritz Dr. Busch
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Siemens AG
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Siemens AG
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Application filed by Siemens AG filed Critical Siemens AG
Publication of EP0902405A2 publication Critical patent/EP0902405A2/fr
Publication of EP0902405A3 publication Critical patent/EP0902405A3/fr
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    • 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

Definitions

  • the invention relates to a method for determining Road routes, especially traffic information related to motorways, local detection cross sections using stationary detectors formed, traffic-related measured values recorded, preprocessed by means of local computers and to a given one Data protocol standardized, aggregated and sent to a higher level by radio Data processing system are transmitted.
  • a traffic control and Information system which uses stationary Guide beacons and transmitting or receiving units arranged in vehicles Traffic flow information determined. From these Traffic flow information becomes, in particular, interference information determined to switch control signals.
  • DE-P 44 08 547 describes a method for traffic detection and traffic situation detection on highways, preferably Motorways, known.
  • lane-related measuring points are set up, which are equipped with traffic sensors, for example induction loops, for vehicle detection and with a traffic data processing device are provided.
  • Traffic data such as vehicle speed, Traffic strength and traffic density determined and from it certain traffic parameters in a traffic data preparation educated.
  • Two adjacent ones form Measuring points a measuring section with a certain distance. Traffic parameters become from the traffic data of two such measuring points educated.
  • This is a speed density difference, calculated from local traffic data of medium speed and traffic density, a trend factor over a period of time from the ratio of traffic levels both measuring points as well as a traffic volume trend.
  • this data becomes the probability derived for a critical traffic situation. at A probability threshold can then be reached Control signal for a variable message sign can be generated.
  • Detectors are also known in the prior art that determine the presence and detect the speed of a moving object can. For example, such detectors work according to a passive infrared process, which may also be used with others Procedure can be combined.
  • a passive infrared process which may also be used with others Procedure can be combined.
  • No method is known to date, traffic information covering the entire area to record and evaluate.
  • An essential aspect of the present invention is the optimal one Evaluation and further processing of the received data in one Central unit to the from an economic point of view recorded and sent data so comprehensive and meaningful to process as possible, but also to produce results arrive, the information content as clear and reliable as possible is. In this regard, only individual solutions are known.
  • the present invention is based on the object of providing an area-wide traffic data acquisition of the generic type, by means of which simple and sensible data transfer and energy expenditure are reliable and sufficiently meaningful data bases for different traffic information services, such that the detected and data sent 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 wireless transmission are transmitted to a higher-level data processing system, the transmitted data being processed in at least two redundant, different and independent calculation methods for determining route-related traffic information.
  • 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. Through the There is a resolution into individual subtasks or stages high 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.
  • Fixed detectors are preferably used at connection points, Positioned nodes and the like. Beyond that the arrangement density of the fixed detectors depending determined by traffic expectation estimates. So you can through the arrangement of many local recording systems Build networks. With the invention it is also possible organize an overall network structure. On traffic critical positions are local detectors and preprocessing computers arranged by radio in preferably digital Technology the data to higher-level data processing systems forward or control centers. There can then be more Traffic models to which data are applied.
  • the possibility of local evaluation results from the local evaluation State identification By linking the data to neighboring local acquisition cross sections can be a so-called route-related level of service in a higher-level data processing system or one assigned to the overall network Central can be determined.
  • Measurement data are delivered, they are preprocessed, for example by calculating mean values, checking plausibility and trend factor determinations carried out become. From the changes in the data or the data itself status codes are then determined, for example in the form a numerical value for conditions such as free flow of traffic, traffic jam, Stop and go, traffic jam or standstill etc. evaluation cycles can be selected every 1 to 5 minutes, for example. However, the evaluation cycle can be set variably, for example depending on the status codes or the Traffic conditions. The same applies to the data transfer rate, which, for example, depending on the determined Status code is applied, for example, with free flow of traffic Averaging every 30 minutes every 5 minutes. Depending on the fault condition, the transmission density increase. The data transfer rates neighboring acquisition cross-sections compared.
  • 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.
  • 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, for Clarification subjected to statistical analysis and that the data evaluated for the submission of traffic development forecasts become.
  • the invention provides methods for different Types and qualities of traffic information data to provide.
  • the main task is to provide such data for to prepare the motor vehicle drivers and expedient them Provide information. It can be, for example for travel time displays, route displays, traffic forecast, Act traffic jams and the like.
  • vehicles are arranged with information displays, on which the drivers of their planned routes and get the travel time information displayed. You can then, for example, under different alternatives choose the fastest route. Additionally or alternatively you can Indications of traffic jam developments, probabilities in relation on 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, comprehensive traffic information system is buildable, which data for different Provides informational purposes. It can be conventional and already known models and processes 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 be artificial intelligence. For the calculation of mean values usual formulas are used.
  • the invention proposes that the transferred data in two different calculation methods 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, output data are a cruising speed and Traffic density k.
  • the calculation method low complexity an additional traffic jam message outputs.
  • a procedure as described is required only a minimum of input data and can be very fast very reliable statements about the traffic conditions in the area of a measurement cross section. With interpolation it is assumed for simplicity that all vehicles behave the same.
  • the other one of the at least two calculation methods is based on the data analysis based on a fundamental diagram Is a highly complex process.
  • a fundamental diagram is a known, on a measurement cross section related curve.
  • the representation is the curve of traffic volume q above the assignment k.
  • the curve corresponds in simplified and highly smoothed form essentially one asymmetrical Gaussian distribution and leaves statements about critical and uncritical states too.
  • the invention strikes before that input data of the calculation method of high complexity Vehicle speed v, traffic strength q and Allocation b are based on a travel time Cruising speed and traffic density are k.
  • the calculation method be of high complexity additionally a traffic situation status signal, at least differentiates according to free / critical / traffic jam. This second procedure also requires only a minimum of Input data and can very quickly make very reliable statements about the traffic condition in the area of a measurement cross-section to meet.
  • Impairment parameters such as construction sites, accidents and the like can be entered.
  • the 3 levels differ in the complexity of the used Process for evaluating traffic data and thus in the quality and type of the calculated traffic parameters.
  • Preprocessing and plausibility checks are carried out in the individual stages of the incoming data. Get all results on sections between adjacent junctions or junctions (e.g. Federal Motorway (BAB) sections) and the current, available at the headquarters Measured data interval. To travel times for selected Determining routes through the network are also the route-related travel speeds of different time intervals according to the route length and the total travel time required; these have to be from archived waterways withdrawn or forecast on the basis thereof. Route-related travel times are not yet calculated here, can, however, be determined on the basis of all 3 levels if necessary become.
  • BAB Federal Motorway
  • the aim is to check and, if necessary, correct the aggregation modules upcoming measurement data.
  • the conversion takes place to track-related values. Extrapolation of directional variables Lane-related sizes.
  • Input is lane-related data from the aggregation module in 1 min intervals.
  • V i Fz q i car ⁇ V i car + q i truck ⁇ V i truck q i car + q i truck
  • the standard deviation gives the fluctuation range of the speed again.
  • the back calculation of the lane-related cruising speed from the cross-sectional cruising speed can also be used.
  • FIG. 2 shows how the detector D uses Section A of a main carriageway H between a first ramp R1 and a second ramp R2 is characterized.
  • the cruising speed in the section is calculated in a first approximation from the local direction-related average speed of the vehicles.
  • V Fz, mom 0.974 V Fz, lok ,
  • the standard deviation of the current speed is equal to the standard deviation of the local speed.
  • FIG. 3 it is shown how a section A one Main roadway H between a first ramp R1 and one second ramp R2 by means of a first detector D1 and one second detector D2 is characterized.
  • Cruising speed in the section is the arithmetic mean of the mean instantaneous speeds of the m measuring cross sections in the section.
  • Traffic volume in the section is the arithmetic mean of the local directional traffic volumes of the m measurement cross-sections in the section
  • K Fz Q Fz V Fz, mom ⁇ Number of lanes ⁇ 60 [vehicle / km]
  • the travel time band is calculated as in case 1.
  • FIG 4 it is shown how a main carriageway H in 3 sections A1, A2 and A3 divided between different ramps R. is, in the first section A1 a first detector D1 and in the third section A3 a second detector D2 is provided is.
  • the standard deviation of the speed is calculated as in case 1.
  • Traffic volume in the section is the arithmetic mean of the local directional traffic volumes of the surrounding measurement cross-sections
  • K Fz Q Fz V Fz, mom ⁇ Number of lanes ⁇ 60 [vehicle / km]
  • the travel time band is calculated as in case 1.
  • FIG. 5 shows case 4, with two detectors D1 and D2 are arranged in sections A1 and A2, respectively.
  • k 1 and k 2 are adjustable.
  • Case 1 relates to the situation shown in FIG. 3.
  • Case 2 relates to the situation shown in FIG. 4. arithmetic mean of the QB of the neighboring MQ
  • Traffic jam on a measuring cross-section is detected when the forecast speed on the main carriageway: V Q, prog ⁇ V traffic jam on the condition that the difference between the forecast speeds of the cars and the trucks (as an absolute value) does not exceed a certain value. ie:
  • V traffic jam 35 km / h
  • V Diff 25 km / h
  • Minimum number of vehicles 600 vehicles / h
  • the module performs an iterative calculation of the matrix elements based on the pre-weighting and the matrix line and column totals.
  • the FDG is shown in FIG.
  • the key data of the individual fundamental diagrams are in the appendix listed.
  • the reference interval is 1 minute.
  • Traffic mapping with ESE Extended Situation Detection: With the traffic model ESE, profiles of traffic volume, Speed and traffic density for individual segments of one Section generated. In addition, statements about made the traffic situation in the section.
  • a section in ESE relates to the model approach always on the distance between two measuring cross-sections.
  • the Section used in the field test (visualization) is limited by nodes or junctions.
  • For visualization the ESE sections or segments must match the visualization sections be assigned.
  • FIG. 8 A federal highway BAB is shown in FIG. 8, which is divided into three sections A1, A2 and A3, each with a detector D1, D2 and D3.
  • ESE there is an ESE section ESE A1 between the first detector D1 and the second detector D2 in 3 segments S 1 m , S 2 m S 3 m and corresponding to the ESE section ESE-A2 between the second detector D2 and the third Detector D3 divided into three segments S 1 n , S 2 n and S 3 n .
  • a Visu ⁇ S m i + ⁇ S n i
  • the traffic situation is determined for the ESE section. To adapt to the BAB section is for the individual situations a corresponding logic is proposed. The Situation is set to zero in the next interval and with the newly calculated ESE situations.
  • a traffic-technical bottleneck is defined as a situation in which the number of available lanes is reduced by a traffic-related event, for example an accident or a vehicle that has broken down, and consequently there are discontinuities in the flow of traffic.
  • ESE A n-1 S3 S4 S5 S6 ESE A n S1 S1 S1 S1 S1 S1 ESE A n + 1 BAB A m-1 S4 BAB A m S3 S1 S5 BAB A m + 1 S1
  • 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 a defined size.
  • ESE A n-1 S4 S5 S6 ESE A n S5 S5 S5 S5 ESE A n + 1 BAB A m-1 BAB on S3 S5 S5 S6 BAB A m + 1 S3
  • the raw data of the detectors are written to a file per detector and day.
  • the parameterization data are for each change and for each detector or aggregation module with the date of the change save.
  • An off-line evaluation accesses the raw data from the detectors, on the results of the three tier models and on the Parameterization data back.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)
  • Devices For Checking Fares Or Tickets At Control Points (AREA)
  • Circuits Of Receivers In General (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Nitrogen And Oxygen Or Sulfur-Condensed Heterocyclic Ring Systems (AREA)

Claims (22)

  1. Procédé pour déterminer des informations de trafic se rapportant à des trajets routiers, notamment à des autoroutes, dans lequel on forme des sections de détection locales au moyen de détecteurs stationnaires, on détecte des valeurs mesurées se rapportant au trafic, on les prépare au moyen de calculateurs locaux, on les norme selon un protocole de données prédéterminé, on les regroupe et on les transmet via une transmission sans fil à une installation de traitement de données supérieure, caractérisé par le fait qu'on traite les données transmises dans au moins deux procédés de calcul redondants, différents et indépendants l'un de l'autre, pour déterminer des informations de trafic se rapportant au trajet.
  2. Procédé selon la revendication 1, caractérisé par le fait qu'on prépare les données transmises pour élaborer un bloc de données de base standard.
  3. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on traite les données transmises dans deux procédés de calcul de complexité différente.
  4. Procédé selon l'une des revendications précédentes, caractérisé par le fait que, pour le traitement des données, on vérifie leur vraisemblance.
  5. Procédé selon l'une des revendications précédentes, caractérisé par le fait que l'un des deux ou plus procédés de calcul est un procédé d'interpolation simple de petite complexité.
  6. Procédé selon la revendication 5, caractérisé par le fait que des données d'entrée du procédé de calcul de petite complexité sont la vitesse de véhicule v et l'intensité de trafic q et que des données de sortie sont une vitesse de croisière et la densité de trafic k.
  7. Procédé selon la revendication 6, caractérisé par le fait que le procédé de calcul de petite complexité fournit en plus un message d'alerte d'embouteillage.
  8. Procédé selon l'une des revendications précédentes, caractérisé par le fait que l'un des deux ou plus procédés de calcul est un procédé de grande complexité basé sur l'analyse de données à l'aide d'un diagramme fondamental.
  9. Procédé selon la revendication 8, caractérisé par le fait que des données d'entrée du procédé de calcul de grande complexité sont la vitesse de véhicule v, l'intensité de trafic q et l'occupation b et qu'une donnée de sortie est une durée de trajet en fonction de la vitesse de croisière et de la densité de trafic k.
  10. Procédé selon la revendication 9, caractérisé par le fait que le procédé de calcul de grande complexité fournit en plus un signal d'état de situation de trafic, au moins différencié selon libre / critique / embouteillage.
  11. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on traite les données transmises dans au moins un troisième procédé de calcul très complexe pour une reconnaissance étendue de la situation.
  12. Procédé selon la revendication 11, caractérisé par le fait qu'on utilise la logique floue dans le procédé de calcul très complexe.
  13. Procédé selon l'une des revendications précédentes, caractérisé par le fait que, dans les procédés de calcul, on entre des paramètres de point de perturbation comme les travaux, les accidents et autres.
  14. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on détecte comme valeurs mesurées une vitesse de véhicule, une intensité de trafic et une occupation.
  15. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on détecte les valeurs mesurées selon les files de circulation.
  16. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on détecte comme valeurs mesurées des valeurs de distinction de type de véhicule.
  17. Procédé selon l'une des revendications précédentes, caractérisé par le fait que, dans l'installation de traitement de données supérieure, on calcule des informations de trafic se rapportant au trajet en combinant les données transmises de sections de détection voisines.
  18. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on évalue les données en vue d'une recherche d'itinéraire.
  19. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on évalue les données pour fournir des informations de gestion de trafic.
  20. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on évalue les données pour fournir des pronostics d'évolution de trafic.
  21. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on évalue les données pour fournir des informations de durée de trajet.
  22. Procédé selon l'une des revendications précédentes, caractérisé par le fait qu'on évalue les données pour fournir des informations d'embouteillage.
EP98117164A 1997-09-11 1998-09-10 Procédé d'investigation d'information sur le trafic Revoked EP0902405B1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE19739918 1997-09-11
DE19739918 1997-09-11

Publications (3)

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EP0902405A2 EP0902405A2 (fr) 1999-03-17
EP0902405A3 EP0902405A3 (fr) 2000-08-23
EP0902405B1 true EP0902405B1 (fr) 2004-05-12

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EP98117164A Revoked EP0902405B1 (fr) 1997-09-11 1998-09-10 Procédé d'investigation d'information sur le trafic

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EP (1) EP0902405B1 (fr)
AT (1) ATE266888T1 (fr)
DE (1) DE59811367D1 (fr)
DK (1) DK0902405T3 (fr)
ES (1) ES2221105T3 (fr)
PT (1) PT902405E (fr)

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DE19928082C2 (de) * 1999-06-11 2001-11-29 Ddg Ges Fuer Verkehrsdaten Mbh Filterungsverfahren zur Bestimmung von Reisegeschwindigkeiten bzw. -zeiten und Domänen-Restgeschwindigkeiten
DE19935770A1 (de) * 1999-07-23 2001-02-01 Ddg Ges Fuer Verkehrsdaten Mbh Rückgekoppelte Zustandskaskade
DE19935769C2 (de) * 1999-07-23 2002-02-07 Ddg Ges Fuer Verkehrsdaten Mbh Verkehrszustandsprognose durch rückgekoppelte Zustandskaskade
DE10036364C2 (de) * 2000-07-18 2003-08-28 Ddg Ges Fuer Verkehrsdaten Mbh Verfahren zur Erstellung prognostizierter Verkehrsdaten für Verkehrsinformationen
DE10036789A1 (de) 2000-07-28 2002-02-07 Daimler Chrysler Ag Verfahren zur Bestimmung des Verkehrszustands in einem Verkehrsnetz mit effektiven Engstellen
EP1480184A3 (fr) * 2003-05-19 2006-06-07 TransVer GmbH Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès
US8838370B2 (en) 2009-03-09 2014-09-16 Empire Technology Development Llc Traffic flow model to provide traffic flow information
CN105118289A (zh) * 2015-06-17 2015-12-02 河南理工大学 一种交通态势评估方法

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US5610821A (en) * 1994-11-18 1997-03-11 Ibm Corporation Optimal and stable route planning system
ES2135134T3 (es) * 1995-04-28 1999-10-16 Inform Inst Operations Res & M Procedimiento para la deteccion de perturbaciones en el trafico rodado.

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Publication number Publication date
ES2221105T3 (es) 2004-12-16
EP0902405A3 (fr) 2000-08-23
DE59811367D1 (de) 2004-06-17
PT902405E (pt) 2004-10-29
DK0902405T3 (da) 2004-09-13
ATE266888T1 (de) 2004-05-15
EP0902405A2 (fr) 1999-03-17

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