Street Parking Availability Estimation

• US 20130257632A1
• Filed: 03/30/2012
• Published: 10/03/2013
• Est. Priority Date: 03/30/2012
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Original Assignee: Toyota Infotechnology Center Co., Ltd. (Toyota Motor Corporation), Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Inventors: Harber, Dustin, Rai, Vinuth, Kresse, Matthew
• Granted Patent: US 8,797,187 B2
• Time in Patent Office: Days
• US Class Current: 340/932.2
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/143 inside the vehicles
• CPC Class Codes: G08G 1/144 on portable or mobile units, e.g. personal digital assistant [PDA]
• CPC Class Codes: G08G 1/147 where the parking area is within an open public zone, e.g. city centre
• CPC Class Codes: G08G 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching

Abstract

A system and method for estimating street parking availability for a user is disclosed. The system comprises a communication module and a parking probability generator. The communication module receives data describing a set of traces for a group of vehicles associated with a group of users. The parking probability generator assigns the set of traces to one or more street segments based at least in part on street segment data describing the one or more street segments. The parking probability generator generates one or more parking probabilities for the one or more street segments based at least in part on one or more user densities in the one or more street segments.

Claims

1. A computer-implemented method, comprising:

receiving data describing a set of traces for a group of vehicles associated with a group of users;

assigning the set of traces to one or more street segments based at least in part on street segment data describing the one or more street segments; and

generating one or more parking probabilities for the one or more street segments based at least in part on one or more user densities in the one or more street segments.

2. The method of claim 1, wherein the street segment is a length of street between a certain number of intersections.

3. The method of claim 1, wherein the parking probability for one street segment is a probability that a future user will find parking in the street segment.

4. The method of claim 1, wherein the user density in one street segment describes a density of users that have driven through the street segment in a certain period of time.

5. The method of claim 1, wherein the user density in one street segment is the ratio of the number of users that have one or more traces assigned to the street segment to the number of users that have one or more traces assigned to a certain range around the street segment.

6. The method of claim 1 further comprising generating a probabilistic map layer based at least in part on the one or more parking probabilities, the probabilistic map layer including an image of the one or more street segments with indicators that indicate the one or more parking probabilities for the one or more street segments.

7. The method of claim 6 further comprising:

generating a probabilistic map based at least in part on the probabilistic map layer; and

displaying the probabilistic map to a user.

8. A system, comprising:

a communication module for receiving data describing a set of traces for a group of vehicles associated with a group of users; and

a parking probability generator communicatively coupled to the communication module, the parking probability generator assigning the set of traces to one or more street segments based at least in part on street segment data describing the one or more street segments and generating one or more parking probabilities for the one or more street segments based at least in part on one or more user densities in the one or more street segments.

9. The system of claim 8, wherein the street segment is a length of street between a certain number of intersections.

10. The system of claim 8, wherein the parking probability for one street segment is a probability that a future user will find parking in the street segment.

11. The system of claim 8, wherein the user density in one street segment describes a density of users that have driven through the street segment in a certain period of time.

12. The system of claim 8, wherein the user density in one street segment is the ratio of the number of users that have one or more traces assigned to the street segment to the number of users that have one or more traces assigned to a certain range around the street segment.

13. The system of claim 8 further comprising a map layer rendering module communicatively coupled to the parking probability generator, the map layer rendering module generating a probabilistic map layer based at least in part on the one or more parking probabilities, the probabilistic map layer including an image of the one or more street segments with indicators that indicate the one or more parking probabilities for the one or more street segments.

14. The system of claim 13 further comprising an application interface communicatively coupled to the map layer rendering module, the application interface generating a probabilistic map based at least in part on the probabilistic map layer and displaying the probabilistic map to a user.

15. A computer program product comprising a non-transitory computer readable medium encoding instructions that, in response to execution by a computing device, cause the computing device to perform operations comprising:

receiving data describing a set of traces for a group of vehicles associated with a group of users;

assigning the set of traces to one or more street segments based at least in part on street segment data describing the one or more street segments; and

generating one or more parking probabilities for the one or more street segments based at least in part on one or more user densities in the one or more street segments.

16. The computer program product of claim 15, wherein the street segment is a length of street between a certain number of intersections.

17. The computer program product of claim 15, wherein the parking probability for one street segment is a probability that a future user will find parking in the street segment.

18. The computer program product of claim 15, wherein the user density in one street segment describes a density of users that have driven through the street segment in a certain period of time.

19. The computer program product of claim 15, wherein the user density in one street segment is the ratio of the number of users that have one or more traces assigned to the street segment to the number of users that have one or more traces assigned to a certain range around the street segment.

20. The computer program product of claim 15, wherein instructions encoded in the computer readable medium when executed cause the computing device to perform operations further comprising generating a probabilistic map layer based at least in part on the one or more parking probabilities, the probabilistic map layer including an image of the one or more street segments with indicators that indicate the one or more parking probabilities for the one or more street segments.

21. The computer program product of claim 20, wherein instructions encoded in the computer readable medium when executed cause the computing device to perform operations further comprising:

generating a probabilistic map based at least in part on the probabilistic map layer; and

displaying the probabilistic map to a user.

22. A computer-implemented method, comprising:

receiving data describing a set of traces for a group of vehicles associated with a group of users;

assigning the set of traces to one or more street segments based at least in part on street segment data describing the one or more street segments; and

generating one or more estimates measuring successful street parking in the one or more street segments based at least in part on one or more user densities in the one or more street segments.