EP0889454A2 - Procédé et centrale de pronostic et d'analyse d'un réseau de circulation - Google Patents

Procédé et centrale de pronostic et d'analyse d'un réseau de circulation Download PDF

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Publication number
EP0889454A2
EP0889454A2 EP98250243A EP98250243A EP0889454A2 EP 0889454 A2 EP0889454 A2 EP 0889454A2 EP 98250243 A EP98250243 A EP 98250243A EP 98250243 A EP98250243 A EP 98250243A EP 0889454 A2 EP0889454 A2 EP 0889454A2
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EP
European Patent Office
Prior art keywords
functional
traffic
nodes
edges
node
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Withdrawn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
EP98250243A
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German (de)
English (en)
Other versions
EP0889454A3 (fr
Inventor
Christian Dipl.-Ing. Hort
Oliver Dipl.-Geograph Michael
Werner Dr. Rer. Nat. Schulz
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.)
ATX Europe GmbH
Original Assignee
Mannesmann 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 Mannesmann AG filed Critical Mannesmann AG
Publication of EP0889454A2 publication Critical patent/EP0889454A2/fr
Publication of EP0889454A3 publication Critical patent/EP0889454A3/fr
Withdrawn legal-status Critical Current

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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
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions

Definitions

  • the invention relates to a method for analyzing a traffic network, Traffic analysis, traffic forecast and a traffic analysis and - forecasting center.
  • maps of transport networks for electronics-based navigation purposes necessarily a high level of detail. They include in particular Information about curves, descents, turning regulations, distances etc., which in approximate reality as closely as possible from the graphic representation of the map to the user, for example one with the help of this card navigating drivers to allow safe and easy navigation.
  • a geographic reality and database containing further details for display and local referencing of traffic reports with reference to the cartographic database are in the The information contained in the map base and the details above is insignificant and unsuitable.
  • the high level of detail due to the spatial approximation Such a card leads in the data referencing with respect to the database and a traffic forecast based on it that can hardly be overcome Problems.
  • one consumes details of a cartographic Database-based traffic network description considerable computing power and does not allow usable forecasts.
  • Another problem is the exchange of information between various places, for example in the transmission of traffic information or when using historical traffic data for traffic analysis or forecast.
  • the use of different but highly detailed cards carries the risk of incompatibilities between used by different bodies Traffic data etc. due to differences in level of detail or Detail errors in used maps stored in databases.
  • the object of the invention is to prepare one in one Cartographic database represented traffic network to simplify the Integration of data collected by traffic detectors and the exchange of Information with other bodies.
  • the task is accomplished by a method for analyzing a traffic network according to the independent claim 1, by a method for generating a historical Database according to claim 12, by a method for traffic analysis and prognosis according to independent process claim 13 and one Traffic forecasting center according to independent device claim 16 solved.
  • the traffic network analysis method according to the invention allows Computer-aided simple and efficient analysis of a through a cartographic, A traffic network that is suitable for navigation purposes.
  • the invention created database is very much due to functional analysis and data reduction well suited for analyzing and forecasting the state of a transport network because it is reduced to particularly important information for this. In particular can e.g.
  • An edge or functional edge in the sense of claim 1 can e.g. a single-lane lane or a multi-lane Be roadway.
  • the map material lies as Output file before and includes edges, i.e. lanes or lane sections and nodes that have multiple lanes at intersections, junctions or Connect departures or which lane sections of a lane connect.
  • the generated target file includes functional edges and functional nodes between Functional edges.
  • Fig. 1 shows schematically a motorway junction 1 with one when looking at the Drawing in landscape format from the left in the picture to the right in the picture, in the Reality e.g. from west to east A2 motorway and one in the Drawing when viewed in landscape format from top to bottom A3 motorway.
  • the depiction of the traffic network is shown in e.g. to Navigation suitable output file saved.
  • edges 101 to 139 correspond to road sections in the output file, that is, in the case of the present highways, highway segments.
  • An edge i.e. a road section 101 to 139, is defined here between two nodes.
  • a node is an intersection, junction, junction etc. or the boundary between two arbitrarily defined sections lying one behind the other, i.e. edges of a road or roadway or roadway group.
  • the two lane groups of a motorway, each assigned to a direction are represented everywhere by their own edges.
  • the section of this motorway A2 shown on the far left comprises edge 118, in which vehicles move from left to right, and edge 101, in which vehicles move in the opposite direction, i.e.
  • a motorway section can also be represented by only one edge in an output file; it is also possible to display a section of a motorway using, for example, three edges for each direction of travel on three-lane motorways; Also, in particular in an output file in front of a motorway junction, a separate edge can be provided for a turning possibility and thus a separate lane on a motorway that leads in or out from it.
  • the edges 101 to 139 are connected by nodes A to Z2, respectively.
  • Knots A to Z2 can have one, two or more than two edges 101 to 139.
  • the spatial position of traffic network elements can e.g. through edges, knots or both can be saved.
  • a passable connection between edge ends can be in the Traffic navigation suitable output file in different ways be saved; in particular, in the directions shown here distinctive representation, for example, that the edge 131st a connection, that is to say a possibility of driving a vehicle 9, with the edge 129 and has 132. For the edge 116 this would mean that there is stored that a Vehicle can continue from it to edge 112 and 115.
  • a traffic network exists e.g. from different street classes, like Motorways, country roads, side streets, exits and entrances to parking lots etc., with an edge and / or a node the road class, which he or she listened to can be saved in a file. Furthermore, in a file for Edges and / or nodes, in particular the name of the street to which they are located Edge belongs to be saved, such as "A2" or "B17". Can also different attributes for edges and / or nodes can be stored.
  • the street class to which the street belongs is one Knots or an edge is assigned to each, the name of the street, a Indication of whether the edge represents one or both directions, how many Roadways that have edges, whether there are any turn marks, how many Turn tracks are provided, in which direction can be turned and the like
  • the represented representation of that saved in the original file Traffic network includes various details that are very helpful for navigation. So it is clear from the map that a vehicle 9, which is on the edge 131 of the Motorway A3 is moving towards the cross and following the drawing shown left, that is as vehicle 9 'in the direction of arrow V9' on the A2 motorway should continue on the edges 131, 129, 127, 113, 114, 104, 135, 101 moved.
  • the representation of the edge 113 shows that, although spatially the vehicle coming from the bottom in the map, i.e. from the south to the left, therefore to the west, to continue, it is necessary that the vehicle is in front of the edge 113 turns right. This is advantageous as a navigation aid because e.g. the driver the indication can be given to already position oneself in edge 129 on the right and turn right and at the end of edge 113 carefully turn onto the Butt edge 114.
  • a method according to the invention for analyzing the Traffic network presented which creates a target file from the source file, which is better suited for traffic analysis and traffic forecasting.
  • the Target file can also be called an abstract map layer or AKL.
  • suitable target file is made up of several mutually assignable nodes and possibly edges a functional node 10 and generates a target file, in which 10 connected functional edges or connected via functional edges Functional nodes which are located outside of this functional node 10, Functional connection data are stored, which individual or summarized, passable, direct or over edges within the Functional node leading connections of the ends of the functional node define the latter functional edges or functional nodes with one another.
  • Functional nodes and / or functional edges are stored in the target file.
  • these are the functional nodes 10 (FIG. 2), A, B, F, G, Z2, Z1, W, X or the Functional edges 101, 118, 136, 137, 117, 139, 130, 131.
  • the nodes A, B, F, G, Z2, Z1, W, X can e.g. B. evaluated functional nodes or in the process still unevaluated nodes of the source file. The same applies to the designated edges. If another functional node in the form of a Motorway junction, nodes A, B would not become functional nodes. Alternatively, it would also be possible to define and save the virtual, only in figure 2 apparent edges shown on the functional node 10 as further functional edges.
  • the functional node 10 in such a way that nodes A, B, C, D, E, F, G, H, N, Z, Z1, Z2, U, V, W, X, 10 are functional nodes. 2, the functional node 10 is functional as a star in the middle of the intersections of the A2 and A3 motorways.
  • the functional node 10 spatially replaces the nodes P, I, J, K, L, M, P2, Q, T, Y, R, S.
  • the functional node 10 in the target file also contains the Functional node connection points E, H, N, Z, V, U, C, D. soft functional edges abutting the functional node 10 with which other ones Functional edges adjacent to functional node 10 are connected. Then would be the functional edge 131 abutting the functional node 10 with the Functional edges into which a vehicle 9 passes over the functional node 10 can retract, connected, namely with the edges 101, 136, 139, 130.
  • the target file is the functional node 10 here only via the center of the intersection Are defined.
  • a functional node in addition to information about adjacent functional edges or / and functional nodes may also store additional data as attributes: It is particularly useful to determine the position of the functional node or the Save the functional edge, which e.g. from the positions adjacent Knots and / or edges can be obtained. Furthermore, at one Functional nodes or a functional edge each have attributes, such as the positions of Edges and / or knots or the information whether you go from an edge to a certain other edge of the functional node or the functional edge on the right or turn left must be saved with.
  • a street traffic network is again an example of this for verification purposes based on.
  • the source file is first sorted into a classified source file, where edges and / or nodes with a certain classification feature, for example, a road type, such as "freeway", can be considered separately.
  • a certain classification feature for example, a road type, such as "freeway”
  • Fig. 1 example shows a spatial section of the street type "Highway" part of a traffic network considered.
  • step 20 the road elements, i.e. edges or / and nodes in step 20a according to their street class, e.g. Classified "Autobahn".
  • the Start of a motorway here in the form of the two nodes A, B in Fig. 1, searched.
  • the traffic network now becomes a node, for example from node B analyzed.
  • node B e.g. in the possible direction of travel of the vehicles, i.e. in Direction of edge 118, analyzed progressively.
  • edges 119 and 120 are also involved around highway segments. If it is e.g. at edge 120 by one Parking lot access would act, would be in step 23 of the flow chart decide that this should not be considered, the node D should be eliminated, would not become a functional node and the flowchart would be under point 21 proceeding with the road in the direction of travel.
  • step 23 e.g. due to the spatial location and / or Link with other nodes or edges or based on the name etc. in each case decided whether a node is to be assigned to a functional node or a Functional node.
  • step 24 further edges leading to node D would have to be searched.
  • the supply of vehicles through others Edges can be seen at node Y, for example Continue the analysis in the direction of travel, that is, via node Y to edge 134 would be found at node Y that there is a leading edge, that is that vehicles from the edge 132 also flow into the node Y.
  • the edges determined according to number 24 in the flow chart in FIG. 3 can form a Functional nodes in the form of those connected to it as inflow edges or e.g. in Form of the functional nodes connected to it via functional edges can be saved.
  • step 25 of the Flowchart is searched for further associated edges, that is to say for further Approaches or exits of vehicles from the node. All of this information are in step 26 for a functional node or a functional edge as "Attribute" saved.
  • the Starting database of turnable instructions that can be generated or entered, such as for example "turn right from edge 131 to edge 114", evaluated and possibly also saved as an attribute in step 27.
  • step 27 the spatial center of the node now becomes the functional node "Autobahn Regen 10" node or a functional edge position preferably calculated on the basis of geocoordinates of the original file and for the functional node or a functional edge is also saved. Furthermore receives a Functional nodes, such as the motorway junction, provide clear identification. This Identification can be related to the real geographic location of the Functional node, for example with its geographic longitude and Width.
  • step 28 The determination of the functional node center coordinates is in the flow chart referred to as step 28.
  • a functional node such as a motorway junction 10
  • nodes and / or edges evaluated the connections and for the Functional node 10 stored.
  • those in a functional node contained nodes and / or edges in step 29 of the flowchart attributes, such as For example, the instruction to turn left, evaluated and as attributes of the Functional node also saved.
  • Functional edges can also specify their position and / or their start and End nodes are stored in a database; furthermore for a Functional edge can be saved, in which functional edge or - the traffic flow edged away from her.
  • a target file obtained according to the above procedure is a traffic analysis for current traffic information or for creating historical data as well a traffic forecast is much better possible.
  • An assignment from one Traffic data valid at the time such as traffic data from traffic detectors and / or traffic information such as verbal traffic jam reports etc.
  • Functional nodes and / or functional edges of the above target file and storage allows the construction of a historical database. This allows a high quality Traffic analysis and, in particular, a traffic forecast through extrapolation.
  • Such a database is also because of the standardization of the assignment of Data particularly suitable for processing in a computer.
  • the traffic forecasting center is an input device, e.g. a Receiver for local traffic parameters sent by traffic detectors, such as Data relating to traffic flow, traffic density and / or vehicle speeds intended.
  • the traffic analysis or forecasting center has a memory for a target file that can be generated according to the above method and represents the traffic network and a memory for a historical database. For one because of the An output unit must be provided for the traffic forecast that can be generated in the target file; a Output is on a screen and / or via radio and / or by printing etc. possible.

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  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
EP98250243A 1997-07-04 1998-07-02 Procédé et centrale de pronostic et d'analyse d'un réseau de circulation Withdrawn EP0889454A3 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE19729914 1997-07-04
DE1997129914 DE19729914A1 (de) 1997-07-04 1997-07-04 Verfahren zur Analyse eines Verkehrsnetzes, Verkehrsanalyse, Verkehrsprognose sowie Erzeugung einer historischen Verkehrsdatenbank und Verkehrsanalyse- und -prognosezentrale

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EP0889454A2 true EP0889454A2 (fr) 1999-01-07
EP0889454A3 EP0889454A3 (fr) 2000-09-27

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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001035370A1 (fr) * 1999-11-11 2001-05-17 Gedas Telematics Gmbh Procede pour decrire et produire des reseaux routiers et reseau routier correspondant
AU2005100125B4 (en) * 2005-02-11 2006-11-30 Mojarrabi, Bahram Mr Scale free network of urban traffic
WO2006128819A1 (fr) * 2005-05-31 2006-12-07 Siemens Aktiengesellschaft Procede pour determiner des taux de changement de direction dans un reseau routier
WO2007140527A1 (fr) * 2006-06-05 2007-12-13 Sensis Pty Ltd Système et procédé pour des informations de route améliorées
CN100385473C (zh) * 2006-01-06 2008-04-30 北京工业大学 双层信号灯控制平交组合节点及其设置方法
EP2097883A1 (fr) * 2006-11-30 2009-09-09 SK Marketing & Company Co., Ltd. Procédé et système fournissant des informations sur la circulation à l'aide d'une carte numérique pour la collecte d'informations sur la circulation
CN102592455A (zh) * 2012-03-09 2012-07-18 西安费斯达自动化工程有限公司 一种基于离散模型的公路交通流检测器设置方法
CN102610097A (zh) * 2012-03-08 2012-07-25 西安费斯达自动化工程有限公司 一种基于改进离散模型的路段交通流检测器设置方法
CN102610096A (zh) * 2012-03-08 2012-07-25 西安费斯达自动化工程有限公司 一种基于改进离散模型的公路交通流检测器设置方法
DE10052109B4 (de) * 1999-11-11 2014-10-30 Deutsche Telekom Ag Verfahren zum Beschreiben und Erzeugen von Straßennetzen und Straßennetz

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CN102610098B (zh) * 2012-03-09 2014-05-07 西安费斯达自动化工程有限公司 一种基于离散模型的路段交通流检测器设置方法
CN103366556B (zh) * 2013-07-10 2015-08-12 南京洛普股份有限公司 协调控制干线的自动组织方法

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Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6850840B1 (en) 1999-11-11 2005-02-01 Volkswagen Ag Method for describing and generating road networks and corresponding road network
WO2001035370A1 (fr) * 1999-11-11 2001-05-17 Gedas Telematics Gmbh Procede pour decrire et produire des reseaux routiers et reseau routier correspondant
DE10052109B4 (de) * 1999-11-11 2014-10-30 Deutsche Telekom Ag Verfahren zum Beschreiben und Erzeugen von Straßennetzen und Straßennetz
AU2005100125B4 (en) * 2005-02-11 2006-11-30 Mojarrabi, Bahram Mr Scale free network of urban traffic
US7894979B2 (en) 2005-05-31 2011-02-22 Siemens Aktiengesellschaft Methods for determining turning rates in a road network
WO2006128819A1 (fr) * 2005-05-31 2006-12-07 Siemens Aktiengesellschaft Procede pour determiner des taux de changement de direction dans un reseau routier
CN101006481B (zh) * 2005-05-31 2010-10-06 西门子公司 用于确定在道路网中的转向率的方法
CN100385473C (zh) * 2006-01-06 2008-04-30 北京工业大学 双层信号灯控制平交组合节点及其设置方法
WO2007140527A1 (fr) * 2006-06-05 2007-12-13 Sensis Pty Ltd Système et procédé pour des informations de route améliorées
EP2097883A4 (fr) * 2006-11-30 2011-04-27 Sk Marketing & Company Co Ltd Procédé et système fournissant des informations sur la circulation à l'aide d'une carte numérique pour la collecte d'informations sur la circulation
US8041503B2 (en) 2006-11-30 2011-10-18 SK Marketing & Company, Co., Ltd Traffic information providing system using digital map for collecting traffic information and method thereof
EP2097883A1 (fr) * 2006-11-30 2009-09-09 SK Marketing & Company Co., Ltd. Procédé et système fournissant des informations sur la circulation à l'aide d'une carte numérique pour la collecte d'informations sur la circulation
CN102610097A (zh) * 2012-03-08 2012-07-25 西安费斯达自动化工程有限公司 一种基于改进离散模型的路段交通流检测器设置方法
CN102610096A (zh) * 2012-03-08 2012-07-25 西安费斯达自动化工程有限公司 一种基于改进离散模型的公路交通流检测器设置方法
CN102592455A (zh) * 2012-03-09 2012-07-18 西安费斯达自动化工程有限公司 一种基于离散模型的公路交通流检测器设置方法
CN102592455B (zh) * 2012-03-09 2014-06-11 西安费斯达自动化工程有限公司 一种基于离散模型的公路交通流检测器设置方法

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DE19729914A1 (de) 1999-01-07
EP0889454A3 (fr) 2000-09-27

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