Elastic Clustering of Vehicles Equipped with Broadband Wireless Communication Devices

• US 20140159923A1
• Filed: 12/07/2012
• Published: 06/12/2014
• Est. Priority Date: 12/07/2012
• Status: Abandoned Application

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Koodli, Rajeev, Oswal, Anand, Athreya, Arjun Prasanna
• Application Number:
  US13/708,399
• Publication Number:
  US 20140159923A1
• Time in Patent Office: Days
• US Class Current: 340/905
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/093 Data selection, e.g. prioritizing information, managing message queues, selecting the information to be output
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station

Abstract

The techniques described herein provide mechanism that allows a Vehicular Communication Systems (VCSs) server, e.g., a cluster server, or other network attached device to group or cluster a set of vehicles into a multicast group according to common mobility characteristics shared by the set of vehicles. For example, the set of vehicles may be in close proximity to each other and are traveling on the same road, or share a common destination. Information pertinent to the cluster, can be broadcast to the multicast group in lieu of traditional individual unicast messages that would typically be sent to each vehicle.

Claims

1. A method comprising:

receiving mobility parameters from a plurality of vehicles at a network device;

analyzing the mobility parameters in order to determine whether a subset of the plurality of vehicles can be clustered based on common mobility parameters of the subset of vehicles; and

clustering the subset of vehicles into a multicast group when it is determined that the subset of vehicles can be clustered based on the common mobility parameters of the subset of vehicles.

2. The method of claim 1, further comprising broadcasting information to the multicast group corresponding to the common mobility parameters of the subset of vehicles.

3. The method of claim 1, wherein receiving comprises receiving mobility parameters comprising one or more of vehicle location, vehicle speed, vehicle destination, vehicle intermediate destination, and vehicle operator preferences.

4. The method of claim 1, wherein receiving comprises receiving the mobility parameters from the subset of vehicles via a plurality of intermediate receivers stationed at locations configured to provide travel segment information along a travel path to the subset of vehicles.

5. The method of claim 1, further comprising:

extracting traffic parameters from a traffic data set;

computing average travel times for one or more predetermined prediction periods; and

generating a bottleneck prediction matrix from the average travel times using a bottleneck prediction function.

6. The method of claim 1, further comprising:

extracting traffic parameters from a traffic data set;

computing average travel times for one or more predetermined detection periods; and

generating a bottleneck matrix from the average travel times using a bottleneck detection function.

7. The method of claim 1, further comprising:

observing vehicular traffic for a predetermined time period;

generating current traffic data from the observed vehicular traffic;

computing bottleneck statistics based on the current traffic data and corresponding historical data; and

predicting whether a bottleneck will occur during a prediction period based on the computed bottleneck statistics.

8. The method of claim 7, further comprising:

determining a range of tolerable bottleneck vehicle speeds;

determining a vehicle occupant'"'"'s tolerance for an average travel time to a destination; and

wherein predicting comprises predicting whether the bottleneck will occur during the prediction period based on one or more of the range of tolerable bottleneck vehicle speeds and the vehicle occupant'"'"'s tolerance for an average travel time to a destination.

9. An apparatus comprising:

a network interface unit configured to enable network communications over a network;

a memory;

a processor coupled to the network interface unit and to the memory, wherein the processor is configured to;

receive mobility parameters from a plurality of vehicles via the network interface unit;

analyze the mobility parameters in order to determine whether a subset of the plurality of vehicles can be clustered based on common mobility parameters of the subset of vehicles; and

cluster the subset of vehicles into a multicast group when it is determined that the subset of vehicles can be clustered based on the common mobility parameters of the subset of vehicles.

10. The apparatus of claim 9, wherein the processor is further configured to broadcasting information to the multicast group corresponding to the common mobility parameters of the subset of vehicles.

11. The apparatus of claim 9, wherein the processor is further configured to receive comprises receiving mobility parameters comprising one or more of vehicle location, vehicle speed, vehicle destination, vehicle intermediate destination, and vehicle operator preferences.

12. The apparatus of claim 9, wherein the processor is further configured to:

extract traffic parameters from a traffic data set;

compute average travel times for one or more predetermined prediction periods; and

generate a bottleneck prediction matrix from the average travel times using a bottleneck prediction function.

13. The apparatus of claim 9, wherein the processor is further configured to:

extract traffic parameters from a traffic data set;

compute average travel times for one or more predetermined detection periods; and

generate a bottleneck matrix from the average travel times using a bottleneck detection function.

14. The apparatus of claim 9, wherein the processor is further configured to:

observe vehicular traffic for a predetermined time period;

generate current traffic data from the observed vehicular traffic;

compute bottleneck statistics based on the current traffic data and corresponding historical data; and

predict whether a bottleneck will occur during a prediction period based on the computed bottleneck statistics.

15. The apparatus of claim 14, wherein the processor is further configured to:

determine a range of tolerable bottleneck vehicle speeds;

determine a vehicle occupant'"'"'s tolerance for an average travel time to a destination; and

wherein the processor is configured to predict whether the bottleneck will occur during the prediction period based on one or more of the range of tolerable bottleneck vehicle speeds and the vehicle occupant'"'"'s tolerance for an average travel time to a destination.

19. The apparatus of claim 9, wherein the processor is further configured to:

observe vehicular traffic for a predetermined time period;

generate current traffic data from the observed vehicular traffic;

compute bottleneck statistics based on the current traffic data and corresponding historical data; and

predict whether a bottleneck will occur during a prediction period based on the computed bottleneck statistics.

16. One or more computer readable storage media encoded with software comprising computer executable instructions and when the software is executed operable to:

receive mobility parameters from a plurality of vehicles;

analyze the mobility parameters in order to determine whether a subset of the plurality of vehicles can be clustered based on common mobility parameters of the subset of vehicles; and

cluster the subset of vehicles into a multicast group when it is determined that the subset of vehicles can be clustered based on the common mobility parameters of the subset of vehicles.

17. The computer readable storage media of claim 16, wherein the computer executable instructions, when executed are further operable to broadcast information to the multicast group corresponding to the common mobility parameters of the subset of vehicles.

18. The computer readable storage media of claim 16, wherein the computer executable instructions, when executed are further operable to receive mobility parameters comprising one or more of vehicle location, vehicle speed, vehicle destination, vehicle intermediate destination, and vehicle operator preferences.

20. A method comprising:

receiving mobility parameters from a plurality of mobile user devices at a network device;

analyzing the mobility parameters in order to determine whether a subset of the plurality of mobile user devices can be clustered based on common mobility parameters of the subset of mobile user devices; and

clustering the subset of mobile user devices into a multicast group when it is determined that the subset of mobile user devices can be clustered based on the common mobility parameters of the subset of mobile user devices.