EP3227875A1 - Method for clustering vehicles - Google Patents

Method for clustering vehicles

Info

Publication number
EP3227875A1
EP3227875A1 EP14830878.6A EP14830878A EP3227875A1 EP 3227875 A1 EP3227875 A1 EP 3227875A1 EP 14830878 A EP14830878 A EP 14830878A EP 3227875 A1 EP3227875 A1 EP 3227875A1
Authority
EP
European Patent Office
Prior art keywords
vehicles
streams
traffic
route
particle
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.)
Ceased
Application number
EP14830878.6A
Other languages
German (de)
French (fr)
Inventor
Carsten KAUSCH
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.)
Audi AG
Original Assignee
Audi 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 Audi AG filed Critical Audi AG
Publication of EP3227875A1 publication Critical patent/EP3227875A1/en
Ceased legal-status Critical Current

Links

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
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control
    • 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
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0141—Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096833—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/22—Platooning, i.e. convoy of communicating vehicles

Definitions

  • the invention relates to a method for clustering vehicles into traffic streams.
  • US 2006/0161341 Al shows a method for providing vehicles with a navigation service, the method comprising the steps of: building by a mediation server, a group of two or more vehicles, each vehicle comprising a communication unit coupled with a navigation unit, wherein one vehicle of the group is classified as master vehicle leading the group and the remaining vehicles of the group are classified as slave vehicles following the master vehicle; storing communication addresses allocated to the communication units assigned to the vehicles of the group, and communicating, by the mediation server the stored communication addresses to the navigation units assigned to the vehicles of the group; determining geographical position data of the master vehicle and the slave vehicles; communicating geographical position data of the master vehicle and the slave vehicles to one or more data processing units; calculating by the one or more data processing units for each of the slaves vehicles route instructions in accordance with the route travelled by the master vehicle based on the received geographical position data of the master vehicle and the respective slave vehicles; communicating the respective route instructions to a driver of each slave vehicle.
  • DE 10 2012 212 339 Al shows a method for grouping vehicles, the method comprising the step of receiving a request to participate in l grouping of vehicles by a single vehicle.
  • a planned travel route and specifications of the vehicle are assigned to the request, and the grouping of the vehicles is determined, wherein a travel route of the vehicles corresponds to the travel route of the vehicle.
  • a minimum power consumption of the grouping is determinable based on power consumption of the vehicles in the grouping and the specifications.
  • a response to the request is sent by transmission of data required for grouping to the vehicles of the grouping.
  • the vehicles specifications are selected from a group consisting of a vehicle type, vehicle proportions, an identification number, an air resistance factor, an unloaded weight, a loading weight, momentary power consumption, a covered distance route, a route for covering distance for a time interval and/or vehicle dimensions.
  • linear time-to-distance calculations for example, traffic management systems or navigation systems of vehicles.
  • a linear calculation is used to determine a journey time required by a vehicle to travel from a starting point to a predetermined arrival point.
  • it has been shown that such linear calculation is faulty in metropolitan traffic situations.
  • the invention relates to a method for clustering, i.e. grouping vehicles into traffic streams by means of at least one particle stream calculation model in which the vehicles are regarded as particles forming particle streams representing the traffic streams.
  • the method comprises a first step in which a first amount or subset of the vehicles is clustered or grouped into a first one of the particle streams, the first amount or subset of the vehicles travelling along a first route. In other words, the vehicles belonging to the first particle stream travel along a first route.
  • the method further comprises a second step in which a second amount or subset of the vehicles are clustered or grouped into a second one of the particle streams, the second amount of the vehicles travelling along a second route being different from the first route at least partially.
  • the idea behind the invention is to use particle stream clustering calculation, i.e. fluid dynamics instead of linear time-to-distance calculation since movements of vehicles, in particular motor vehicles, especially in heavy traffic were found to be at least substantially similar to the movement of a fluid flow or particles moving in streams flowing like a fluid, in particular a liquid.
  • particle stream calculation model which is, for example, a fluid dynamics model
  • traffic densities can be represented by densities of the particle streams or densities of fluid flows which can be in turn represented by well-known equations of fluid dynamics.
  • the vehicles are clustered, i.e. grouped into the traffic streams in such a way that all vehicles of the traffic streams arrive at their respective destinations after the same journey time with regard to respective starting points of the vehicles.
  • 250 cars travel along a first route at a speed of 20 km/h
  • 50 cars travel along a second route at a speed of 12 km/h
  • 2000 cars travel along a third route at a speed of 52 km/h.
  • the cars are clustered in such a way that every car arrives after the same journey time.
  • an existing infrastructure which can be used by the cars can be used particularly efficiently since the infrastructure can be used to its full capacity.
  • the idea is to realize an at least substantially optimal, in particular short journey time for all vehicles.
  • the model comprises equations of fluid dynamics. These equations can represent respective speeds and/or densities of fluid flows and, thus, the particle streams in the model. It has been shown that equations of fluid dynamics can be advantageously used to describe or simulate the movement of vehicles , especially in heavy traffic.
  • an arrival time at which one of the vehicles will arrive at its predetermined arrival location is determined on the basis of that traffic streams.
  • the method can be used in a navigation system of a vehicle, in particular a passenger vehicle, to calculate the journey time and, thus, the arrival time. It has been shown that using the method according to the present invention instead of linear models to calculate the arrival time allows for calculating the journey time and, thus, the arrival time much more precisely, i.e. with a much smaller error.
  • a traffic management system is operated on the basis of the traffic streams.
  • the method according to the present invention can be used to operate a traffic management system used for clustering or grouping the vehicles into the particle streams.
  • an infrastructure comprising roads for vehicles can be used particularly effectively and efficiently so that excessive traffic jams and excessive journey times for the vehicle can be avoided.
  • the invention further relates to a navigation system for a vehicle, the navigation system being configured to perform the method according to the present invention.
  • Advantages and advantageous embodiments of the method according to the present invention are to be regarded as advantages and advantageous embodiments of the navigation system according to the present invention and vice versa.
  • Figure 1 shows a flow diagram for illustrating a method for clustering vehicles into traffic streams by means of at least one particle stream calculation model.
  • Figure 1 shows a flow diagram illustrating a method for clustering vehicles, in particular motor vehicles, into traffic streams.
  • the vehicles are clustered, i.e. grouped into the traffic streams with the help of at least one particle stream calculation model comprising equations of fluid dynamics.
  • the vehicles are regarded as particles forming particle streams representing the traffic streams.
  • the particle streams are fluid streams or fluid flows, in particular liquid streams or liquid flows which can be represented by said equations.
  • Said equations can represent densities of the fluid flows and, thus, the particle streams, said densities representing densities of the traffic streams and, thus, traffic densities.
  • said equations can represent pressures and/or speeds of the particle streams, the pressures and/or speeds representing respective speeds of the vehicles and, thus, the traffic streams.
  • a first amount or subset of the vehicles are clustered or grouped into a first one of the particle streams, wherein the first amount or subset of the vehicles travels along a first route.
  • a second amount or subset of the vehicles is clustered or grouped into a second one of the particle streams, the second amount or subset of the vehicles travelling along a second route being different from the first route at least partially.
  • a traffic management system is operated on the basis of the method in such a way that the vehicles are clustered into the traffic streams or particle streams in such a way that all vehicles of the traffic streams arrive at their respective destinations after the same journey time with regard to respective starting points of the vehicles.
  • an infrastructure comprising roads on which the vehicles can travel can be used to its full capacity and, thus, particularly effectively and efficiently.
  • an at least substantially optimal journey time for all the vehicles can be realized since excessive differences between the respective journey times of the individual vehicles can be avoided.
  • every vehicle has the same traffic delay which means the traffic delay for all vehicles on the whole can be kept to a minimum.
  • information on the vehicles and their movements can be provided by a traffic observation system on the basis of which information the particle streams can be calculated.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Mathematical Physics (AREA)
  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Navigation (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention relates to a method for clustering vehicles into traffic streams by means of at least one particle stream calculation model in which the vehicles are regarded as particles forming particle streams representing the traffic streams, the method comprising: clustering a first amount of the vehicles into a first one of the particle streams, the first amount of the vehicles travelling along a first route, and clustering a second amount of the vehicles into a second one of the particle streams, the second amount of the vehicles travelling along a second route being different from the first route at least partially.

Description

Method for Clustering Vehicles Field of the Invention
The invention relates to a method for clustering vehicles into traffic streams.
Background Art
US 2006/0161341 Al shows a method for providing vehicles with a navigation service, the method comprising the steps of: building by a mediation server, a group of two or more vehicles, each vehicle comprising a communication unit coupled with a navigation unit, wherein one vehicle of the group is classified as master vehicle leading the group and the remaining vehicles of the group are classified as slave vehicles following the master vehicle; storing communication addresses allocated to the communication units assigned to the vehicles of the group, and communicating, by the mediation server the stored communication addresses to the navigation units assigned to the vehicles of the group; determining geographical position data of the master vehicle and the slave vehicles; communicating geographical position data of the master vehicle and the slave vehicles to one or more data processing units; calculating by the one or more data processing units for each of the slaves vehicles route instructions in accordance with the route travelled by the master vehicle based on the received geographical position data of the master vehicle and the respective slave vehicles; communicating the respective route instructions to a driver of each slave vehicle.
Moreover, DE 10 2012 212 339 Al shows a method for grouping vehicles, the method comprising the step of receiving a request to participate in l grouping of vehicles by a single vehicle. A planned travel route and specifications of the vehicle are assigned to the request, and the grouping of the vehicles is determined, wherein a travel route of the vehicles corresponds to the travel route of the vehicle. A minimum power consumption of the grouping is determinable based on power consumption of the vehicles in the grouping and the specifications. A response to the request is sent by transmission of data required for grouping to the vehicles of the grouping. The vehicles specifications are selected from a group consisting of a vehicle type, vehicle proportions, an identification number, an air resistance factor, an unloaded weight, a loading weight, momentary power consumption, a covered distance route, a route for covering distance for a time interval and/or vehicle dimensions.
Furthermore, it is known from the general prior art to use linear time-to-distance calculations to run, for example, traffic management systems or navigation systems of vehicles. For example, such a linear calculation is used to determine a journey time required by a vehicle to travel from a starting point to a predetermined arrival point. However, it has been shown that such linear calculation is faulty in metropolitan traffic situations.
Summary of the Invention
Technical problem to be solved
It is therefore an object of the present invention to provide a method which allows for realizing a better traffic management and/or a better navigation of vehicles. This object is solved by a method having the features of patent claim 1. Advantageous embodiments with expedient developments of the invention are indicated in the other patent claims. Technical solution
The invention relates to a method for clustering, i.e. grouping vehicles into traffic streams by means of at least one particle stream calculation model in which the vehicles are regarded as particles forming particle streams representing the traffic streams. The method comprises a first step in which a first amount or subset of the vehicles is clustered or grouped into a first one of the particle streams, the first amount or subset of the vehicles travelling along a first route. In other words, the vehicles belonging to the first particle stream travel along a first route. The method further comprises a second step in which a second amount or subset of the vehicles are clustered or grouped into a second one of the particle streams, the second amount of the vehicles travelling along a second route being different from the first route at least partially.
The idea behind the invention is to use particle stream clustering calculation, i.e. fluid dynamics instead of linear time-to-distance calculation since movements of vehicles, in particular motor vehicles, especially in heavy traffic were found to be at least substantially similar to the movement of a fluid flow or particles moving in streams flowing like a fluid, in particular a liquid. On the basis of the method according to the present invention better traffic management systems as well as improved navigation possibilities for vehicles can be provided since the movements of the vehicles in traffic can be simulated more realistically and, thus, calculated more precisely in comparison with linear calculation models. For example, in the particle stream calculation model which is, for example, a fluid dynamics model, traffic densities can be represented by densities of the particle streams or densities of fluid flows which can be in turn represented by well-known equations of fluid dynamics.
In an advantageous embodiment of the invention, the vehicles are clustered, i.e. grouped into the traffic streams in such a way that all vehicles of the traffic streams arrive at their respective destinations after the same journey time with regard to respective starting points of the vehicles. For example, 250 cars travel along a first route at a speed of 20 km/h, 50 cars travel along a second route at a speed of 12 km/h and 2000 cars travel along a third route at a speed of 52 km/h. Preferably, the cars are clustered in such a way that every car arrives after the same journey time. Thereby, an existing infrastructure which can be used by the cars can be used particularly efficiently since the infrastructure can be used to its full capacity. The idea is to realize an at least substantially optimal, in particular short journey time for all vehicles.
In a further advantageous embodiment of the invention, the model comprises equations of fluid dynamics. These equations can represent respective speeds and/or densities of fluid flows and, thus, the particle streams in the model. It has been shown that equations of fluid dynamics can be advantageously used to describe or simulate the movement of vehicles , especially in heavy traffic.
In a further advantageous embodiment of the invention, an arrival time at which one of the vehicles will arrive at its predetermined arrival location is determined on the basis of that traffic streams. For example, the method can be used in a navigation system of a vehicle, in particular a passenger vehicle, to calculate the journey time and, thus, the arrival time. It has been shown that using the method according to the present invention instead of linear models to calculate the arrival time allows for calculating the journey time and, thus, the arrival time much more precisely, i.e. with a much smaller error.
In a further advantageous embodiment of the invention, a traffic management system is operated on the basis of the traffic streams. In other words, the method according to the present invention can be used to operate a traffic management system used for clustering or grouping the vehicles into the particle streams. By operating the traffic management system on the basis of the method according to the present invention an infrastructure comprising roads for vehicles can be used particularly effectively and efficiently so that excessive traffic jams and excessive journey times for the vehicle can be avoided.
The invention further relates to a navigation system for a vehicle, the navigation system being configured to perform the method according to the present invention. Advantages and advantageous embodiments of the method according to the present invention are to be regarded as advantages and advantageous embodiments of the navigation system according to the present invention and vice versa.
Further advantages, features and details of the invention derive from the following description of a preferred embodiment as well as from the drawing. The features and feature combinations previously mentioned in the description as well as the features and feature combinations mentioned in the following description of the figure and/or shown in the figure alone can be employed not only in the respective indicated combination but also in any other combination or taken alone without leaving the scope of the invention. Brief Description of the Drawings
Figure 1 shows a flow diagram for illustrating a method for clustering vehicles into traffic streams by means of at least one particle stream calculation model.
Detailed Description of Embodiments
Figure 1 shows a flow diagram illustrating a method for clustering vehicles, in particular motor vehicles, into traffic streams. The vehicles are clustered, i.e. grouped into the traffic streams with the help of at least one particle stream calculation model comprising equations of fluid dynamics.
In said model the vehicles are regarded as particles forming particle streams representing the traffic streams. For example, the particle streams are fluid streams or fluid flows, in particular liquid streams or liquid flows which can be represented by said equations. Said equations can represent densities of the fluid flows and, thus, the particle streams, said densities representing densities of the traffic streams and, thus, traffic densities. Moreover, said equations can represent pressures and/or speeds of the particle streams, the pressures and/or speeds representing respective speeds of the vehicles and, thus, the traffic streams. By using such a model and, thus, equations of fluid dynamics, the respective movement of the vehicles in heavy traffic can be simulated much more precisely and realistically in comparison with linear calculations. Thus, for example, the method can be used to operate a traffic management system and/or to calculate a journey time of at least one of the vehicles travelling from a starting point to an arrival point.
In a first step S 1 of the method a first amount or subset of the vehicles are clustered or grouped into a first one of the particle streams, wherein the first amount or subset of the vehicles travels along a first route. In a second step S2 of the method a second amount or subset of the vehicles is clustered or grouped into a second one of the particle streams, the second amount or subset of the vehicles travelling along a second route being different from the first route at least partially. Preferably, a traffic management system is operated on the basis of the method in such a way that the vehicles are clustered into the traffic streams or particle streams in such a way that all vehicles of the traffic streams arrive at their respective destinations after the same journey time with regard to respective starting points of the vehicles. Thereby, an infrastructure comprising roads on which the vehicles can travel can be used to its full capacity and, thus, particularly effectively and efficiently. Moreover, an at least substantially optimal journey time for all the vehicles can be realized since excessive differences between the respective journey times of the individual vehicles can be avoided. Thereby, every vehicle has the same traffic delay which means the traffic delay for all vehicles on the whole can be kept to a minimum.
For example, information on the vehicles and their movements can be provided by a traffic observation system on the basis of which information the particle streams can be calculated.
Moreover, by realizing an at least substantially optimal journey time for all vehicles an acceptance for using such traffic management systems can be generated among the drivers of the vehicles since an optimal time-to-distance calculation for all of the vehicles can be realized.

Claims

What is claimed is:
1. A method for clustering vehicles into traffic streams by means of at least one particle stream calculation model in which the vehicles are regarded as particles forming particle streams representing the traffic streams, the method comprising:
- clustering a first amount of the vehicles into a first one of the particle streams, the first amount of the vehicles travelling along a first route, and
- clustering a second amount of the vehicles into a second one of the particle streams, the second amount of the vehicles travelling along a second route being different from the first route at least partially.
2. The method according to claim 1,
characterized in that
the vehicles are clustered into the traffic streams in such a way that all vehicles of the traffic streams arrive at their respective destinations after the same journey time with regard to respective starting points of the vehicles.
3. The method according to any one of claims 1 or 2,
characterized in that
the model comprises equations of fluid dynamics.
4. The method according to any one of the preceding claims,
characterized in that
an arrival time at which at least one of the vehicles will arrive at its predetermined arrival location is determined on the basis of the traffic streams.
5. The method according to any one of the preceding claims,
characterized in that a traffic management system is operated on the basis of the traffic streams.
6. A navigation system for a vehicle, the navigation system being configured to perform the method according to any one of the preceding claims.
EP14830878.6A 2014-12-05 2014-12-05 Method for clustering vehicles Ceased EP3227875A1 (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/IB2014/066630 WO2016087907A1 (en) 2014-12-05 2014-12-05 Method for clustering vehicles

Publications (1)

Publication Number Publication Date
EP3227875A1 true EP3227875A1 (en) 2017-10-11

Family

ID=52424060

Family Applications (1)

Application Number Title Priority Date Filing Date
EP14830878.6A Ceased EP3227875A1 (en) 2014-12-05 2014-12-05 Method for clustering vehicles

Country Status (3)

Country Link
EP (1) EP3227875A1 (en)
CN (1) CN107004348B (en)
WO (1) WO2016087907A1 (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111915875B (en) * 2019-05-08 2024-07-19 阿里巴巴集团控股有限公司 A method, device and electronic device for processing vehicle flow path distribution information
CN113763701B (en) * 2021-05-26 2024-02-23 腾讯科技（深圳）有限公司 Road condition information display method, device, equipment and storage medium

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EP1681663B1 (en) * 2005-01-14 2007-08-01 Alcatel Lucent Navigation service
CN1731467A (en) * 2005-07-07 2006-02-08 上海交通大学 Construction method of urban traffic signal self-organization rules based on fluid dynamics
CN101515407A (en) * 2009-03-04 2009-08-26 同济大学 Self-organization method of municipal traffic control signal based on fluid dynamics
DE102011085644A1 (en) * 2011-11-03 2013-05-08 Robert Bosch Gmbh Route computation method of navigation device, involves choosing dynamically changing position as route destination, and performing route computation of route navigation device based on dynamic destination
DE102012212339A1 (en) 2012-07-13 2014-01-16 Siemens Aktiengesellschaft Method for platooning of vehicles on road, involves determining minimum power consumption of grouping, and sending response to request to participate in grouping by transmission of data required for grouping to vehicles of grouping
US20140159923A1 (en) * 2012-12-07 2014-06-12 Cisco Technology, Inc. Elastic Clustering of Vehicles Equipped with Broadband Wireless Communication Devices
US9412271B2 (en) * 2013-01-30 2016-08-09 Wavetronix Llc Traffic flow through an intersection by reducing platoon interference
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Also Published As

Publication number Publication date
WO2016087907A1 (en) 2016-06-09
CN107004348A (en) 2017-08-01
CN107004348B (en) 2021-02-09

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