Sensor Technology at the Smart
Public Intersection Aschaffenburg
Michael Goldhammer, Ulrich Brunsmann, Konrad Doll
Hochschule Aschaffenburg
Sensorik und Intelligenz der
öffentlichen Testkreuzung Aschaffenburg
Overview
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• Cooperative perception - Concept
• Test setup at public intersection
• Sensors
• Experimental results
Cooperative perception -
Concept
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MMI
Driver Intention
Risk Analysis
Scene Interpretation
Inter-Vehicle (Cooperative) Perception
I2V- and V2V-Communication
Use Cases Safety Functions
Intersection-based
Local Perception
Vehicle-based
Local Perception,
Self-Localization
Intersection based perception
• Test site
• Hardware architecture
• Laserscanners
• Cameras
• Calibration
• Experiments and results
Test setup at public intersection
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Intersection in an
urban area
• 5 and 3 lanes
• 3 crosswalks
• Bicycle lane
• Approx. 23,000
vehicles per day
UAB
Architecture of perception system
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Traffic
Lights
co
mp
lem
en
tary
Laserscanner subsystem
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14 SICK LD-MRS research multilayer laserscanners:
• 4 horizontally aligned for central intersection area and crosswalks
• 8 vertically aligned for incoming lanes, range up to 100m
• 2 for sidewalks, crosswalks and bicycle lane
Simulated fields of view Measured Lidar reflections
Camera subsystem
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10 monochrome cameras:
• 4 wide angle cameras for central intersection area
• 3 cameras for intersection approaches
• 1 top view camera for critical area
• 2 high definition cameras for crosswalks and critical area,
representing a wide angle stereo system
Simulated fields of view
Sensor mounting positions
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Experimental results:
Evaluation of cross calibration
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Spatial alignment
Target position by standard camera
system (green) and person‘s position by
laserscanner system (blue) (extract)
x-Coordinate (m)
y-C
oo
rdin
ate
(m
)
Tracking of camera reference target
Experimental results:
Evaluation of cross calibration
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Temporal alignment
Results
Standard deviation in position
∆𝑥2 + ∆𝑦2 < 17cm
Temporal alignment < 80 ms
No
rm. C
ross-C
ova
ria
nce
of LS
vs. S
D c
am
era
sam
ple
s
Time lag of position on y-axis
In multiples of LS sample time (80ms)
Experimental results:
High definition stereo system
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Target device placed at 10 globally measured (DGPS)
positions in the fields of view of both cameras
Results
Absolute position error of the
HD camera stereo subsystem
∆𝑥2 + ∆𝑦2 + ∆𝑧2
< 20mm (on ground plane)
< 30mm (2 m above ground)
Application:
Pedestrian intention detection
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Visualization of estimated trajectory (sigmoid model)
(Slow motion 1/10, 0.2 s/div)
Application:
Pedestrian intention detection
2.4 2.0 1.6 1.2 0.8 0.4 s
Comparison: Estimation and reference measurement
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[1] S. Köhler, M. Goldhammer, S. Bauer, S. Zecha, K. Doll, U. Brunsmann, K. Dietmayer:
“Stationary Detection of the Pedestrian’s Intention at Intersections,” accepted for publication in:
IEEE Intelligent Transportation Systems Magazine ITSC 2012 Special Issue, invited Paper.
Conclusion
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• Comprehensive sensor network at public urban intersection
• Adaption to local surroundings by 3D software simulation
• Occlusion resistant vision range
• Calibrated system provides positions in world coordinates
Thank you!
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