EP0902405A2 - Procédé de transmission d'information sur le trafic - Google Patents

Procédé de transmission d'information sur le trafic Download PDF

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Publication number
EP0902405A2
EP0902405A2 EP98117164A EP98117164A EP0902405A2 EP 0902405 A2 EP0902405 A2 EP 0902405A2 EP 98117164 A EP98117164 A EP 98117164A EP 98117164 A EP98117164 A EP 98117164A EP 0902405 A2 EP0902405 A2 EP 0902405A2
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EP
European Patent Office
Prior art keywords
traffic
data
vehicle
calculation
speed
Prior art date
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Granted
Application number
EP98117164A
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German (de)
English (en)
Other versions
EP0902405A3 (fr
EP0902405B1 (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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Publication of EP0902405B1 publication Critical patent/EP0902405B1/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 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 to a higher-level radio Data processing system are transmitted.
  • a traffic control and Information system which uses stationary Beacons and transmitter or receiver 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 intensity and traffic density determined and from it certain traffic parameters in a traffic data preparation educated.
  • Two neighboring 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 volumes both measuring points as well as a traffic volume trend.
  • this data becomes the probability derived for a critical traffic situation.
  • Control signal for a variable message sign are generated.
  • Detectors are also known in the prior art that detect 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.
  • Detectors In the state of the art No method is known to date, traffic information covering the entire area to record and evaluate. In particular, there are none Method known that the traffic information determination route section variable, event-oriented if necessary and enable with little data transfer effort.
  • 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, 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 related to road routes, in particular highways, 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 technology 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.
  • 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 traffic flow, 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 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 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, 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 motorists use 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 the further development on the upcoming 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, 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 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 issues.
  • 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 Occupancy 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 of road between adjacent junctions or junctions (e.g. Federal Motorway (BAB) sections) and to the current one at the headquarters Measurement 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 corridors taken 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.
  • the standard deviation gives the fluctuation range of the speed again.
  • the 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 directional average speed of the vehicles.
  • V Fz, mom 0.974
  • the travel time band indicates the bandwidth of the travel time, which is calculated from the standard deviation of the speed.
  • ⁇ t R ⁇ 1 S v ⁇ 60 [min / km]
  • 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.
  • 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 Vehicle Q Vehicle 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 measuring cross-sections
  • Q i Vehicle [Vehicle / min]
  • K Vehicle Q Vehicle V Fz, mom ⁇ Number of lanes ⁇ 60 [vehicle / km]
  • the travel time band is calculated as in case 1.
  • k 1 and k 2 are adjustable.
  • V Q the forecast speed on the main carriageway
  • 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.
  • V QP the forecast speed on the main carriageway
  • prog - V QL 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.
  • V QP the forecast speed on the main carriageway
  • prog ⁇ V traffic jam 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:
  • Minimum number of vehicles The parameters V traffic jam , V diff and the minimum number of vehicles are adjustable.
  • the module performs an iterative calculation of the matrix elements based on the pre-weighting and the matrix row 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 the traffic situation made in the section made.
  • a section in ESE relates to the model approach always on the distance between two measuring cross sections.
  • Section used in the field test is limited by nodes or junctions.
  • the ESE sections or segments must correspond to 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 newly calculated ESE situations.
  • a traffic-technical bottleneck is defined as a situation in which the number of available lanes is reduced due to a traffic-related event, for example an accident or a broken down vehicle, 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 A m 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 of 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)
  • Mobile Radio Communication Systems (AREA)
  • Circuits Of Receivers In General (AREA)
  • Nitrogen And Oxygen Or Sulfur-Condensed Heterocyclic Ring Systems (AREA)
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)

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

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ID=7842002

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Application Number Title Priority Date Filing Date
EP98117164A Revoked EP0902405B1 (fr) 1997-09-11 1998-09-10 Procédé d'investigation d'information sur le trafic

Country Status (6)

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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)

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1061491A1 (fr) * 1999-06-11 2000-12-20 DDG Gesellschaft für Verkehrsdaten mbH Procédé de filtrage de données du trafic pour déterminer la vitesse sur les routes
EP1071058A1 (fr) * 1999-07-23 2001-01-24 DDG Gesellschaft für Verkehrsdaten mbH Procédé et dispositif pour rétroaction l'état en cascade
EP1071057A1 (fr) * 1999-07-23 2001-01-24 DDG Gesellschaft für Verkehrsdaten mbH Procédé et dispositif de pronostic de l'état du trafic par retroaction l'état en cascade
EP1174842A1 (fr) * 2000-07-18 2002-01-23 DDG Gesellschaft für Verkehrsdaten mbH Méthode pour créer les données de trafic pronostic pour des informations sur la circulation
US6522970B2 (en) 2000-07-28 2003-02-18 Daimlerchrysler Ag Method for determining the traffic state in a traffic network with effective bottlenecks
EP1480184A2 (fr) * 2003-05-19 2004-11-24 TransVer GmbH Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès
EP2228779A2 (fr) 2009-03-09 2010-09-15 LStar Technologies LLC Modèle de flux de trafic pour fournir des informations de flux de trafic
CN105118289A (zh) * 2015-06-17 2015-12-02 河南理工大学 一种交通态势评估方法

Citations (2)

* 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
US5610821A (en) * 1994-11-18 1997-03-11 Ibm Corporation Optimal and stable route planning system

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5610821A (en) * 1994-11-18 1997-03-11 Ibm Corporation Optimal and stable route planning system
EP0740280A2 (fr) * 1995-04-28 1996-10-30 INFORM Institut für Operations Research und Management GmbH Méthode de détection des pertubations pour trafic routièr

Non-Patent Citations (2)

* 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 *
SADAO TAKABA ET AL: "ESTIMATION AND MEASUREMENT OF TRAVEL TIME BY VEHICLE DETECTORS AND LICENSE PLATE READERS" PROCEEDINGS OF THE VEHICLE NAVIGATION AND INFORMATION SYSTEMS CONFERENCE,US,NEW YORK, IEEE, Bd. -, 1991, Seiten 257-267, XP000348211 ISBN: 0-7803-0488-8 *

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1061491A1 (fr) * 1999-06-11 2000-12-20 DDG Gesellschaft für Verkehrsdaten mbH Procédé de filtrage de données du trafic pour déterminer la vitesse sur les routes
EP1071058A1 (fr) * 1999-07-23 2001-01-24 DDG Gesellschaft für Verkehrsdaten mbH Procédé et dispositif pour rétroaction l'état en cascade
EP1071057A1 (fr) * 1999-07-23 2001-01-24 DDG Gesellschaft für Verkehrsdaten mbH Procédé et dispositif de pronostic de l'état du trafic par retroaction l'état en cascade
EP1174842A1 (fr) * 2000-07-18 2002-01-23 DDG Gesellschaft für Verkehrsdaten mbH Méthode pour créer les données de trafic pronostic pour des informations sur la circulation
US6522970B2 (en) 2000-07-28 2003-02-18 Daimlerchrysler Ag Method for determining the traffic state in a traffic network with effective bottlenecks
EP1480184A2 (fr) * 2003-05-19 2004-11-24 TransVer GmbH Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès
EP1480184A3 (fr) * 2003-05-19 2006-06-07 TransVer GmbH Méthode pour détecter des caractéristiques de la circulation routière aux points d'accès
EP2228779A2 (fr) 2009-03-09 2010-09-15 LStar Technologies LLC Modèle de flux de trafic pour fournir des informations de flux de trafic
EP2228779A3 (fr) * 2009-03-09 2010-11-17 LStar Technologies LLC Modèle de flux de trafic pour fournir des informations de flux de trafic
US8838370B2 (en) 2009-03-09 2014-09-16 Empire Technology Development Llc Traffic flow model to provide traffic flow information
US9927254B2 (en) 2009-03-09 2018-03-27 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

Also Published As

Publication number Publication date
DK0902405T3 (da) 2004-09-13
ATE266888T1 (de) 2004-05-15
ES2221105T3 (es) 2004-12-16
DE59811367D1 (de) 2004-06-17
EP0902405A3 (fr) 2000-08-23
EP0902405B1 (fr) 2004-05-12
PT902405E (pt) 2004-10-29

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