Traffic prediction system, vehicle-mounted display apparatus, vehicle, and traffic prediction method

• US 10,424,195 B2
• Filed: 03/31/2016
• Issued: 09/24/2019
• Est. Priority Date: 10/27/2015
• Status: Active Grant

• Current Assignee: Hyundai Motor Company (Hyundai Motor Group)
• Original Assignee: Hyundai Motor Company (Hyundai Motor Group)
• Inventors: Kim, ChulMin, Lee, Dongyoul, Kim, Young Su, Kim, SiJun
• Primary Examiner(s): Antonucci, Anne M
• Assistant Examiner(s): Stroud, James E
• Application Number:
  US15/087,055
• Publication Number:
  US 20170116850A1
• Time in Patent Office: 1,272 Days
• Field of Search: 701117
• CPC Class Codes: G01C 21/3694 Output thereof on a road map
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0125 Traffic data processing
• 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 1/052 with provision for determining speed or overspeed speed measuring in general G01P
• CPC Class Codes: G08G 1/065 by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096758 where no selection takes place on the transmitted or the received information
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: G08G 1/096827 where the route is computed onboard
• CPC Class Codes: G08G 1/096844 where the complete route is dynamically recomputed based on new data
• CPC Class Codes: G08G 1/096866 where the complete route is shown to the driver

Abstract

Disclosed herein are a traffic prediction system, a vehicle-mounted display apparatus, a vehicle, and a traffic prediction method. The traffic prediction system includes: a vehicle configured to acquire a driving probability for at least one drivable route; and a server apparatus configured to receive the driving probability for the at least one drivable route from the vehicle, and to calculate a volume of traffic for the at least one drivable route based on the driving probability for the at least one drivable route.

Claims

1. A traffic prediction system comprising:

a server apparatus configured to;

receive a driving probability for at least one drivable route from a vehicle configured to acquire the driving probability for the at least one drivable route;

retrieve, from a database, a road network data structure comprised of nodes and links, wherein the nodes represent at least one of a straight road, an intersection, an overpass, a underpass, an exit, or a rotary within an area;

calculate a volume of traffic for the at least one drivable route using the driving probability for the at least one drivable route, wherein the vehicle is configured to calculate a driving probability for the at least one drivable route based on the road network data structure;

calculate a predicted volume of vehicles for each link based on the driving probability for each link and an entering time point of vehicles for each link;

calculate the volume of traffic for the at least one drivable route based on the predicted volume of vehicles for each link;

decide a route existing in a range to which the vehicle is able to travel for a predetermined time period;

retrieve, from the database, map information corresponding to a three-dimensional map, wherein the map information includes a three-dimensional coordinate identifying a location of the vehicle; and

acquire a driving probability for the route existing in the range based on the map information.

2. The traffic prediction system according to claim 1, wherein the vehicle is configured to calculate the driving probability for each link by further considering a lane change history of the vehicle.

3. The traffic prediction system according to claim 1, wherein the at least one drivable route includes a route existing in a range to which the vehicle is able to travel for a predetermined time period.

4. The traffic prediction system according to claim 1, wherein the server apparatus is configured to transmit information about the volume of traffic to the vehicle.

5. The traffic prediction system according to claim 1, further comprising a terminal configured to receive information about the volume of traffic from the server apparatus.

6. The traffic prediction system according to claim 1, wherein the vehicle comprises a vehicle-mounted display apparatus configured to acquire the driving probability for the at least one drivable route.

7. A traffic prediction system comprising:

a server apparatus configured to;

receive a driving probability for at least one drivable route from a vehicle configured to acquire the driving probability for the at least one drivable route, wherein the vehicle is configured to acquire an image about a front view of the vehicle, to extract lines from the image to acquire information about lanes, and to acquire a lane change history based on the information about the lanes;

retrieve, from a database, a road network data structure comprised of nodes and links representing roads within an area;

calculate a volume of traffic for the at least one drivable route using the driving probability for the at least one drivable route, wherein the vehicle is configured to calculate the driving probability for the at least one drivable route based on the road network data structure;

wherein the server apparatus is further configured to;

calculate a predicted volume of vehicles for each link based on the driving probability for each link and an entering time point of vehicles for each link;

calculate the volume of traffic for the at least one drivable route based on the predicted volume of vehicles for each link;

decide a route existing in a range to which the vehicle is able to travel for a predetermined time period;

retrieve, from the database, map information corresponding to a three-dimensional map, wherein the map information includes a three-dimensional coordinate identifying a location of the vehicle; and

acquire a driving probability for the route existing in the range based on the map information and the lane change history.

8. A traffic prediction system comprising:

a server apparatus configured to;

receive a driving probability for at least one drivable route from a vehicle configured to acquire the driving probability for the at least one drivable route;

retrieve, from a database, a road network data structure comprised of nodes and links representing roads within an area;

calculate a volume of traffic for the at least one drivable route using the driving probability for the at least one drivable route, wherein the vehicle is configured to calculate a driving probability for the at least one drivable route in the road network using driving vectors of the vehicle;

wherein the server apparatus is further configured to;

calculate a predicted volume of vehicles for each link based on the driving probability for each link and an entering time point of vehicles for each link;

calculate the volume of traffic for the at least one drivable route based on the predicted volume of vehicles for each link;

decide a route existing in a range to which the vehicle is able to travel for a predetermined time period;

retrieve, from the database, map information corresponding to a three-dimensional map, wherein the map information includes a three-dimensional coordinate identifying a location of the vehicle; and

acquire a driving probability for the route existing in the range based on the map information.

9. The traffic prediction system according to claim 8, wherein the vehicle is configured to acquire information about a position of the vehicle several times, and configured to acquire the driving vectors of the vehicle based on the information about the position of the vehicle.

10. The traffic prediction system according to claim 8, wherein the three-dimensional coordinate includes an altitude of the vehicle.

11. A traffic prediction system comprising:

a server apparatus configured to;

receive a driving probability for at least one drivable route from a vehicle configured to acquire the driving probability for the at least one drivable route;

retrieve, from a database, a road network data structure comprised of nodes and links representing roads within an area;

calculate a volume of traffic for the at least one drivable route using the driving probability for the at least one drivable route;

wherein the vehicle is configured to calculate a driving probability for for the at least one drivable route based on the road network data structure;

wherein the server apparatus is configured to calculate a predicted volume of vehicles for each link based on the driving probability for each link and an entering time point of vehicles for each link, and configured to calculate the volume of traffic for the at least one drivable route based on the result of the calculation;

retrieve, from the database, map information corresponding to a three-dimensional map, wherein the map information includes a three-dimensional coordinate identifying a location of the vehicle; and

wherein the server apparatus is configured to decide a route existing in a range to which the vehicle is able to travel for a predetermined time period, and acquire a driving probability for the route existing in the range based on the map information.

12. A traffic prediction system comprising:

a server apparatus configured to;

receive a driving probability for at least one drivable route from a vehicle configured to acquire the driving probability for the at least one drivable route;

retrieve, from a database, a road network data structure comprised of nodes and links representing roads within an area;

calculate a volume of traffic for the at least one drivable route using the driving probability for the at least one drivable route;

wherein the vehicle is configured to calculate a driving probability for the at least one drivable route based on the road network data structure;

wherein the vehicle is configured to calculate a driving probability for each route included in the road network using the driving probability for the at least one link; and

wherein the server apparatus is further configured to;

calculate a predicted volume of vehicles for each link based on the driving probability for each link and an entering time point of vehicles for each link;

calculate the volume of traffic for the at least one drivable route based on the predicted volume of vehicles for each link;

decide a route existing in a range to which the vehicle is able to travel for a predetermined time period;

retrieve, from the database, map information corresponding to a three-dimensional map, wherein the map information includes a three-dimensional coordinate identifying a location of the vehicle; and

acquire a driving probability for the route existing in the range based on the map information.

13. The traffic prediction system according to claim 12, wherein the vehicle is configured to calculate the driving probability for each route using an Electronic Horizon (EH) method.

14. The traffic prediction system according to claim 12, wherein the server apparatus is configured to calculate a predicted volume of vehicles based on the driving probability for each route, and the vehicle is configured to calculate the volume of traffic for the at least one drivable route based on the result of the calculation.