This talk presents the basic contents, methods and strategies of DriveBuild.

1. DriveBuild
Interactive session and demonstration
Stefan Huber
University of Passau
June 12, 2019

2. Overview
1 Components of a Test
Environment
Participants
AIs
Criteria
2 Execution of Tests
3 How to use it?

3. Components of a Test

5. Lanes
Lanes = Positions + widths

6. Lanes
Lanes = Positions + widths

7. Obstacles

8. Obstacles

9. Obstacles

10. Obstacles

11. Obstacles

12. Obstacles

13. Questions so far?

14. What about these?

15. What about these?
Can I model hills?

16. What about these?
Can I model hills?
Any chance to model “ramps”?

17. What about these?
Can I model hills?
Any chance to model “ramps”?
How does the rotation work?

18. What about these?
Can I model hills?
Any chance to model “ramps”?
How does the rotation work?
Can I change the lane material?

19. What about these?
Can I model hills?
Any chance to model “ramps”?
How does the rotation work?
Can I change the lane material?
What about the weather and the time of day?

20. What about these?
Can I model hills?
Any chance to model “ramps”?
How does the rotation work?
Can I change the lane material?
What about the weather and the time of day?
Have lanes additional information like direction or position on the lane?

21. Description of Participants

22. Description of Participants

23. Description of Participants

24. Description of Participants

25. Description of Participants

26. Description of Participants

27. Description of Movements

28. Waypoint

29. Waypoint

30. Waypoint
tolerance

31. Movement Modes

32. Movement Modes
MANUAL

33. Movement Modes
MANUAL
AUTONOMOUS

34. Movement Modes
MANUAL
AUTONOMOUS
TRAINING

35. Movement Modes
MANUAL
AUTONOMOUS
TRAINING

36. MANUAL Mode Feature

37. MANUAL Mode Feature

38. MANUAL Mode Feature

39. User :AI :Simulation
simulate()
start()
wait()
ready
request()
data
control()
RepeatRepeat

40. Available Information

41. Available Information
Sensor data

42. Available Information
Sensor data
Camera (front, back, left, right, dash)

43. Available Information
Sensor data
Camera (front, back, left, right, dash)
colored

44. Available Information
Sensor data
Camera (front, back, left, right, dash)
colored
annotated

45. Available Information
Sensor data
Camera (front, back, left, right, dash)
colored
annotated
depth

46. Available Information
Sensor data
Camera (front, back, left, right, dash)
colored
annotated
depth
Speed

47. Available Information
Sensor data
Camera (front, back, left, right, dash)
colored
annotated
depth
Speed
Damage

48. Available Information
Sensor data
Camera (front, back, left, right, dash)
colored
annotated
depth
Speed
Damage
LiDAR

49. Available Information
Sensor data
Camera (front, back, left, right, dash)
colored
annotated
depth
Speed
Damage
LiDAR
Additional data

50. Available Information
Sensor data
Camera (front, back, left, right, dash)
colored
annotated
depth
Speed
Damage
LiDAR
Additional data
Position

51. Available Information
Sensor data
Camera (front, back, left, right, dash)
colored
annotated
depth
Speed
Damage
LiDAR
Additional data
Position
Steering angle

53. Python Client

54. Still no questions?

55. What about these?

56. What about these?
What do I have to do to implement an AI?

57. What about these?
What do I have to do to implement an AI?
Do I need to wait()?

58. What about these?
What do I have to do to implement an AI?
Do I need to wait()?
Do I have to use Python?

59. What about these?
What do I have to do to implement an AI?
Do I need to wait()?
Do I have to use Python?
How does the TRAINING mode work?

60. What about these?
What do I have to do to implement an AI?
Do I need to wait()?
Do I have to use Python?
How does the TRAINING mode work?
Can I “fake” an AI or try out a test without an actual AI?

61. What about these?
What do I have to do to implement an AI?
Do I need to wait()?
Do I have to use Python?
How does the TRAINING mode work?
Can I “fake” an AI or try out a test without an actual AI?
Do I need an AI when doing TRAINING?

62. What about these?
What do I have to do to implement an AI?
Do I need to wait()?
Do I have to use Python?
How does the TRAINING mode work?
Can I “fake” an AI or try out a test without an actual AI?
Do I need an AI when doing TRAINING?
Can I use the built-in AI of BeamNG?

63. What about these?
What do I have to do to implement an AI?
Do I need to wait()?
Do I have to use Python?
How does the TRAINING mode work?
Can I “fake” an AI or try out a test without an actual AI?
Do I need an AI when doing TRAINING?
Can I use the built-in AI of BeamNG?
Does the MANUAL mode recognize the tolerance of waypoints?

64. What about these?
What do I have to do to implement an AI?
Do I need to wait()?
Do I have to use Python?
How does the TRAINING mode work?
Can I “fake” an AI or try out a test without an actual AI?
Do I need an AI when doing TRAINING?
Can I use the built-in AI of BeamNG?
Does the MANUAL mode recognize the tolerance of waypoints?
Can I control things like the gear or the parking brake?

65. Types of planned Criteria
Type VC SC
position
area
lane
speed
damage
time
distance
TTC
light
waypoint

66. Description of Criteria
evaluation
criterionconnective
and ornot SC VC

67. Description of Criteria
evaluation
criterionconnective
and ornot SC VC

68. Example

71. Example with VCs
Speed limit on a certain lane

72. Criteria on Client Side
:Simulation :AI
data
check criteria
do calculations
check more criteria
control

73. Really? No questions?

74. What about these?

75. What about these?
Why is there a speed criterion if there are already a target speed as well as a
speed limit in the MANUAL mode?

76. What about these?
Why is there a speed criterion if there are already a target speed as well as a
speed limit in the MANUAL mode?
Which of the planned criteria do you need?

77. What about these?
Why is there a speed criterion if there are already a target speed as well as a
speed limit in the MANUAL mode?
Which of the planned criteria do you need?
Do you need any further criteria?

78. What about these?
Why is there a speed criterion if there are already a target speed as well as a
speed limit in the MANUAL mode?
Which of the planned criteria do you need?
Do you need any further criteria?
Do you need additional information during simulation?

79. Execution of Tests

80. Runtime verification/Synchronous Simulation
Verify
criteria
Request
AIs
Control
Start
Resume
Pause

81. Checking Criteria
Preconditions
skipped
Fail criteria
failed
Success criteria
succeeded
undetermined

82. GUI
A “GUI” is missing so far. . .

83. GUI
A “GUI” is missing so far. . .
And it may never come. . .

84. GUI
A “GUI” is missing so far. . .
And it may never come. . .
Currently stick to HTTP GET requests, i. e. the provided client

85. How to use it?

86. Test Generation
Goal: Generate XML files
Therefore:

87. Test Generation
Goal: Generate XML files
Therefore:
1 Implement the methods and strategies of your paper

88. Test Generation
Goal: Generate XML files
Therefore:
1 Implement the methods and strategies of your paper
2 Implement a converter translating the output to DriveBuild files

89. Test Generation
Goal: Generate XML files
Therefore:
1 Implement the methods and strategies of your paper
2 Implement a converter translating the output to DriveBuild files
3 Test generated files

90. Training AIs
Goal: Collect training data for AIs (e. g. neural networks)
Therefore:

91. Training AIs
Goal: Collect training data for AIs (e. g. neural networks)
Therefore:
1 Think about the data you need

92. Training AIs
Goal: Collect training data for AIs (e. g. neural networks)
Therefore:
1 Think about the data you need
2 Think about an scenario presumably delivering that data

93. Training AIs
Goal: Collect training data for AIs (e. g. neural networks)
Therefore:
1 Think about the data you need
2 Think about an scenario presumably delivering that data
Lanes

94. Training AIs
Goal: Collect training data for AIs (e. g. neural networks)
Therefore:
1 Think about the data you need
2 Think about an scenario presumably delivering that data
Lanes
Obstacles

95. Training AIs
Goal: Collect training data for AIs (e. g. neural networks)
Therefore:
1 Think about the data you need
2 Think about an scenario presumably delivering that data
Lanes
Obstacles
Participants

96. Training AIs
Goal: Collect training data for AIs (e. g. neural networks)
Therefore:
1 Think about the data you need
2 Think about an scenario presumably delivering that data
Lanes
Obstacles
Participants
Movements (E. g. do participants meet?)

97. Training AIs
Goal: Collect training data for AIs (e. g. neural networks)
Therefore:
1 Think about the data you need
2 Think about an scenario presumably delivering that data
Lanes
Obstacles
Participants
Movements (E. g. do participants meet?)
3 Train an AI

98. Training AIs
Goal: Collect training data for AIs (e. g. neural networks)
Therefore:
1 Think about the data you need
2 Think about an scenario presumably delivering that data
Lanes
Obstacles
Participants
Movements (E. g. do participants meet?)
3 Train an AI
4 Test trained AI

99. Any other application you want me to
explain or to think about?

100. Last chance for questions!
Use it!