Population mobility generator and simulator

• US 20040088392A1
• Filed: 03/18/2002
• Published: 05/06/2004
• Est. Priority Date: 03/18/2002
• Status: Abandoned Application

• Current Assignee: Regents of the University of California (University of California)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Smith, James P., Stretz, Paula E., Marathe, Madhav V., Barrett, Christopher L., Beckman, Richard J., Eubank, Stephen G., McKay, Michael D., Berkbigler, Kathryn P., Konjevod, Goran, Esser, Joerg, Speckman, Paul L., Nagel, Kai, Campbell, Katherine, Bush, Brian W., Baggerly, Keith A., Jacob, Rudiger R.
• Application Number:
  US10/100,501
• Publication Number:
  US 20040088392A1
• Time in Patent Office: Days
• US Class Current: 709/223
• CPC Class Codes: G01C 21/26 specially adapted for navigation in a road network
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions

Abstract

A system and method provides a simulation of a complex network and movement and interdependencies between entities in the network. The system receives aggregated population data and a population synthesizer generates disaggregated population data representative of two different types of entities. The different entity types are then coupled to one another to form interdependent relationships. An activity generator generates typical activities for the entities. A route planner generates travel plans, including departure times and travel modes, for each entity to achieve daily activities. A micro-simulation module simulates movement of the individual entities in compliance with their travel plans. The system may include parallel processors to simulate thousands of roadway and transit segments, intersection signals and signs, transfer facilities between various transportation modes, traveler origins and destinations, and entities and vehicles. The system includes a framework and selector module that gathers the travel times from the simulation and uses them to re-plan activities and trips and re-run the simulation. The methods of the present invention produce appropriate dynamic behavior of the transportation network as a whole.

Claims

1. A system for simulating movement of entities within a network, the system comprising:

a processor for executing instructions; and

a memory device in communication with the processor and storing modules executable by the processor, the modules comprising;

a population synthesizer to receive aggregated population data representative of first and second population sets, to generate disaggregated entities for each population set, and to form relationships between first entities associated with the first population set and second entities associated with the second population set;

an activity generator for receiving the entities and generating activities located in the network for each entity;

a route planner for receiving the activities and generating travel plans for each entity for travel within the network; and

a micro-simulation module for simulating movement of each entity within the network and generating simulation output data.

2. The system of claim 1, wherein the first entities are representative of humans and the second entities are representative of non-humans.

3. The system of claim 1, wherein the second entities are dependent upon the first entities for movement.

4. The system of claim 1, wherein the population synthesizer comprises a population generator to receive the aggregated population data and generate first and second baseline populations corresponding to the first and second population sets respectively.

5. The system of claim 4, wherein the population synthesizer further comprises a population locator to receive network data representative of the network and the first and second baseline populations and place first and second entities within the network.

6. The system of claim 4, wherein the population synthesizer further comprises a vehicle assignment module to receive the baseline populations and baseline vehicle data and generate vehicle data.

7. The system of claim 4, wherein the population synthesizer further comprises an interdependency coupling module to receive the entities and form relationships between first and second entities.

8. The system of claim 1, wherein the activity generator comprises an activity patterns module to receive aggregated activity data and to generate activity patterns.

9. The system of claim 8, wherein the activity generator further comprises a matching module to receive the entities, the activity patterns, and households, and match the activity patterns and entities to households.

10. The system of claim 9, wherein the activity generator further comprises an activity location generator to generate locations in the network for activities.

11. The system of claim 10, wherein the location generator comprises:

a discrete choice module to select locations for primary activities in the network;

and

a trip-chaining module to select locations for remaining activities in the network.

12. The system of claim 9, wherein the activity generator further comprises a make household file module to create a set of household files containing the households.

13. The system of claim 9, wherein the activity generator further comprises an activity regenerator module to partially modify existing activities and generate new activities for households.

14. The system of claim 1, wherein the route planner comprises an internal planner network module to receive network data and to construct an internal network.

15. The system of claim 14, wherein the route planner further comprises a requests module to receive activities and travel times and to generate trip requests.

16. The system of claim 15 wherein the trip requests include a source activity location, a destination activity location, and allowed travel modes.

17. The system of claim 15, wherein the route planner further comprises a paths module in communication with the internal planner network module and the requests module, the paths module configured to review trip requests from the requests module and generate travel plans for each entity.

18. The system of claim 17, wherein the route planner further comprises a retimes module to review and update the duration of travel plans.

19. The system of claim 15, wherein the route planner is configured to recognize activities that generate an anomaly in the travel plans.

20. The system of claim 1, wherein the micro-simulation module includes an output module that collects and stores simulation output data.

21. The system of claim 1, wherein the simulation output data includes traveler event records, snapshot data, and summary data.

22. The system of claim 1, wherein the micro-simulation module is configured to perform a cellular automata process, comprising:

dividing the network into a plurality of cells;

examining cells for vehicle occupancy;

determining whether to accelerate or de-accelerate a vehicle; and

advancing vehicles to adjacent cells.

23. The system of claim 1, wherein the micro-simulation module is configured to perform a method during a discrete time step, comprising:

updating traffic signals;

preparing nodes in the network;

moving vehicles to adjacent lanes;

moving transit vehicles to stops;

moving transit vehicles from stops; and

cleaning up nodes in the network.

24. The system of claim 1, wherein the modules further comprise a framework module and a selector module to receive the activities, travel plans, and simulation output data and generate selections for the activity generator, route planner, and micro-simulation module.

25. The system of claim 24, wherein the selector module comprises:

an iteration database containing iteration data including activities, travel plans, and simulation output data from a plurality of iterations; and

a selector, in communication with the iteration database, and configured to make selections responsive to the iteration data.

26. The system of claim 25, further comprising an iteration script for invoking the selector and iteration database.

27. A computer readable medium having stored thereon computer executable instructions for performing a method for simulating movement of entities within a network, the method comprising:

receiving aggregated population data representative of first and second population sets;

generating disaggregated first entities associated with the first population set and disaggregated second entities associated with the second population set;

forming relationships between the first and second entities;

generating activities located in the network for each entity;

generating travel plans for each entity for travel within the network;

simulating movement of each entity within the network; and

generating simulation output data.

28. The computer readable medium of claim 27 wherein the first entities are representative of humans and the second entities are representative of non-humans.

29. The computer readable medium of claim 27 wherein the second entities are dependent upon the first entities for movement.

30. The computer readable medium of claim 27, wherein the method further comprises generating first and second baseline populations corresponding to the first and second population sets respectively.

31. The computer readable medium of claim 30, wherein the method further comprises:

receiving network data representative of the network; and

placing entities within the network based on the network data and the first and second baseline populations.

32. The computer readable medium of claim 30, wherein the method further comprises generating vehicle data based on baseline populations and baseline vehicle data.

33. The computer readable medium of claim 27, wherein the method further comprises:

receiving aggregated activity data; and

generating activity patterns based on the aggregated activity data.

34. The computer readable medium of claim 33, wherein the method further comprises:

receiving synthetic households; and

matching the activity patterns and entities to the synthetic households.

35. The computer readable medium of claim 33, wherein the method further comprises generating locations in the network for the activities.

36. The computer readable medium of claim 34, wherein the method further comprises:

partially modifying existing activities; and

generating new activities for the synthetic households.

37. The computer readable medium of claim 27, wherein the method further comprises:

receiving network data; and

constructing an internal network based on the network data.

38. The computer readable medium of claim 27, wherein the method further comprises:

receiving travel times; and

generating trip requests based on the travel times.

39. The computer readable medium of claim 38, wherein the method further comprises:

reviewing trip requests; and

generating travel plans for each entity based on the trip requests.

40. The computer readable medium of claim 39, wherein the method further comprises:

reviewing the travel plans;

comparing the travel plans to actual travel durations; and

updating the duration of travel plans to reflect the actual travel plans.

41. The computer readable medium of claim 39, wherein the method further comprises recognizing activities that generate an anomaly in the travel plans.

42. The computer readable medium of claim 27, wherein the simulation output data includes traveler event records, snapshot data, and summary data.

43. The computer readable medium of claim 27, wherein the method further comprises:

dividing the network into a plurality of cells;

examining cells for vehicle occupancy;

determining whether to accelerate or de-accelerate a vehicle; and

advancing vehicles to adjacent cells.

44. The computer readable medium of claim 27, wherein the method further comprises:

updating traffic signals;

preparing nodes in the network;

moving vehicles to adjacent lanes;

moving transit vehicles to stops;

moving transit vehicles from stops; and

cleaning up nodes in the network.

45. The computer readable medium of claim 27, wherein the method further comprises generating selections for the activity generator, route planner, and micro-simulation module.

46. The computer readable medium of claim 45, wherein the method further comprises:

storing iteration data including activities, travel plans, and simulation output data from a plurality of iterations; and

generating selections responsive to the iteration data.

47. The computer readable medium of claim 27, wherein simulating movement of each entity comprises:

partitioning the network into subnetworks; and

assigning subnetworks to a plurality of processors.

48. A method for simulating movement of entities within a network, the method comprising:

receiving aggregated population data representative of first and second population sets;

generating disaggregated first entities associated with the first population set and disaggregated second entities associated with the second population set;

forming relationships between the first and second entities;

generating activities located in the network for each entity;

generating travel plans for each entity for travel within the network;

simulating movement of each entity within the network; and

generating simulation output data.

49. The method of claim 48 wherein the first entities are representative of humans and the second entities are representative of non-humans.

50. The method of claim 48 wherein the second entities are dependent upon the first entities for movement.

51. The method of claim 48, further comprising generating first and second baseline populations corresponding to the first and second population sets respectively.

52. The method of claim 51, further comprising:

receiving network data representative of the network; and

placing entities within the network based on the network data and the first and second baseline populations.

53. The method of claim 51, further comprising generating vehicle data based on baseline populations and baseline vehicle data.

54. The method of claim 51, further comprising:

receiving aggregated activity data; and

generating activity patterns based on the aggregated activity data.

55. The method of claim 54, further comprising:

receiving synthetic households; and

matching the activity patterns and entities to the synthetic households.

56. The method of claim 54, further comprising generating locations in the network for the activities.

57. The method of claim 55, further comprising:

partially modifying existing activities; and

generating new activities for synthetic households.

58. The method of claim 48, further comprising:

receiving network data; and

constructing an internal network based on the network data.

59. The method of claim 48, further comprising:

receiving travel times; and

generating trip requests based on the travel times.

60. The method of claim 59, further comprising:

reviewing trip requests; and

generating travel plans for each entity based on the trip requests.

61. The method of claim 60, further comprising:

reviewing the travel plans;

comparing the travel plans to actual travel durations; and

updating the duration of travel plans to reflect the actual travel plans.

62. The method of claim 60, further comprising recognizing activities that generate an anomaly in the travel plans.

63. The method of claim 48, wherein the simulation output data includes traveler event records, snapshot data, and summary data.

64. The method of claim 48, further comprising:

dividing the network into a plurality of cells;

examining cells for vehicle occupancy;

determining whether to accelerate or de-accelerate a vehicle; and

advancing vehicles to adjacent cells.

65. The method of claim 48, further comprising:

updating traffic signals;

preparing nodes in the network;

moving vehicles to adjacent lanes;

moving transit vehicles to stops;

moving transit vehicles from stops; and

cleaning up nodes in the network.

66. The method of claim 48, further comprising generating selections for the activity generator, route planner, and micro-simulation module.

67. The method of claim 66, further comprising:

storing iteration data including activities, travel plans, and simulation output data from a plurality of iterations; and

generating selections responsive to the iteration data.

68. The method of claim 48, wherein simulating movement of each entity comprises:

partitioning the network into subnetworks; and

assigning subnetworks to a plurality of processors.

69. A system for simulating movement of entities within a network, the system comprising:

a plurality of processors in electrical communication with one another and configured for parallel processing; and

a memory device in communication with the processors and storing modules executable by the processors, the modules comprising;

a population synthesizer to receive aggregated population data representative of first and second population sets, to generate disaggregated entities for each population set, and to form relationships between first entities associated with the first population set with second entities associated with the second population set;

an activity generator for receiving the entities and generating activities located in the network for each entity;

a route planner for receiving the activities and generating travel plans for each entity for travel within the network; and

a micro-simulation module for simulating movement of each entity within the network and generating simulation output data.

70. A system for simulating movement of entities within a network, the system comprising:

processing means; and

memory means in communication with the processing means for storing modules executable by the processing means, the modules comprising;

population synthesizer means for receiving aggregated population data representative of first and second population sets, for generating disaggregated entities for each population set, and for forming relationships between first entities associated with the first population set and second entities associated with the second population set;

activity generator means for receiving the entities and for generating activities located in the network for each entity;

route planner means for receiving the activities and for generating travel plans for each entity for travel within the network; and

micro-simulation means for simulating movement of each entity within the network and for generating simulation output data.

71. The system of claim 70, wherein the population synthesizer means comprises population generator means for receiving the aggregated population data and for generating first and second baseline populations corresponding to the first and second population sets respectively.

72. The system of claim 71, wherein the population synthesizer means further comprises population locator means for receiving network data representative of the network and the first and second baseline populations and for placing first and second entities within the network.

73. The system of claim 71, wherein the population synthesizer means further comprises vehicle assignment means for receiving the baseline populations and baseline vehicle data and for generating vehicle data.

74. The system of claim 70, wherein the population synthesizer means comprises interdependency coupling means for receiving the entities and for forming relationships between first and second entities.

75. The system of claim 70, wherein the activity generator means comprises an activity location generator means for generating locations in the network for activities.

76. The system of claim 70, wherein the activity generator means comprises activity patterns means for receiving aggregated activity data and for generating activity patterns.

77. The system of claim 76, wherein the activity generator means further comprises matching means for receiving the entities, the activity patterns, and households, and for matching the activity patterns and entities to households.

78. The system of claim 77, wherein the activity generator means further comprises activity regenerator means for modifying existing activities and for generating new activities for households.

79. The system of claim 70, wherein the route planner means comprises internal planner network means for receiving network data and for constructing an internal network.

80. The system of claim 79, wherein the route planner means further comprises requests means for receiving activities and travel times and for generating trip requests.

81. The system of claim 80, wherein the route planner means further comprises path means, in communication with the internal planner network means and the requests means, for reviewing trip requests and generating travel plans for each entity.

82. The system of claim 70, wherein the route planner means further comprises retimes means for reviewing and updating the duration of travel plans .

83. The system of claim 70, wherein the micro-simulation means includes output means for collecting and storing simulation output data.

84. The system of claim 83, wherein the simulation output data includes traveler event records, snapshot data, and summary data.

85. The system of claim 70, wherein the modules further comprise framework and selector means for receiving the activities, travel plans, and simulation output data and for generating selections for the activity generator means, route planner means, and micro-simulation means.

86. The system of claim 85, wherein the framework and selector means comprises:

iteration database means for storing iteration data including activities, travel plans, and simulation output data from a plurality of iterations; and

selector means, in communication with the iteration database means, for generating selections responsive to the iteration data.

87. A system for generating disaggregated population data from aggregated population data, the system comprising:

a processor for executing instructions; and

a memory device in communication with the processor and storing modules executable by the processor, the modules including,

a population synthesizer to receive aggregated population data representative of first and second population sets, to generate disaggregated entities for each population set, and to form relationships between first entities associated with the first population set and second entities associated with the second population set, the population synthesizer including,

a population generator to receive the aggregated population data and generate first and second baseline populations corresponding to the first and second population sets respectively,

a population locator to receive network data representative of the network and the first and second baseline populations and place first and second entities within the network, and

an interdependency coupling module to receive the entities and form relationships between the first and second entities.

88. The system of claim 87, wherein the first entities are representative of humans and the second entities are representative of non-humans.

89. The system of claim 87, wherein the second entities are dependent upon the first entities for movement.

90. The system of claim 87, wherein the population synthesizer further comprises a vehicle assignment module to receive the baseline populations and baseline vehicle data and generate vehicle data.

91. A method for generating disaggregated population data from aggregated population data, the method comprising:

receiving aggregated population data representative of first and second population sets;

generating first and second baseline populations corresponding to the first and second population sets respectively;

generating disaggregated first entities associated with the first population set and disaggregated second entities associated with the second population set;

forming relationships between the first and second entities;

receiving network data representative of the network; and

locating first and second entities within the network based on the network data.

92. The method of claim 91 wherein the first entities are representative of humans and the second entities are representative of non-humans.

93. The method of claim 91 wherein the second entities are dependent upon the first entities for movement.

94. The method of claim 91, further comprising generating vehicle data based on baseline populations and baseline vehicle data.