Object-level fusion for surround environment perception in automated driving applications:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Düsseldorf
VDI Verlag GmbH
[2017]
|
| Ausgabe: | Als Manuskript gedruckt |
| Schriftenreihe: | Fortschritt-Berichte VDI. Reihe 12, Verkehrstechnik/Fahrzeugtechnik
Nr. 804 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XV, 199 Seiten Illustrationen, Diagramme |
| ISBN: | 9783183804122 |
Internformat
MARC
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| 100 | 1 | |a Aeberhard, Michael |d 1983- |e Verfasser |0 (DE-588)1136141693 |4 aut | |
| 245 | 1 | 0 | |a Object-level fusion for surround environment perception in automated driving applications |c Michael Aeberhard, M.Sc., München |
| 246 | 1 | 3 | |a Object level fusion for surround environment perception in automated driving applications |
| 246 | 1 | 3 | |a Object level fusion in automated driving |
| 250 | |a Als Manuskript gedruckt | ||
| 264 | 1 | |a Düsseldorf |b VDI Verlag GmbH |c [2017] | |
| 264 | 4 | |c © 2017 | |
| 300 | |a XV, 199 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Fortschritt-Berichte VDI. Reihe 12, Verkehrstechnik/Fahrzeugtechnik |v Nr. 804 | |
| 502 | |b Dissertation |c Technische Universität Dortmund |d 2017 | ||
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| 650 | 0 | 7 | |a Umweltmodell |g Informatik |0 (DE-588)4250471-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Datenfusion |0 (DE-588)4582612-2 |2 gnd |9 rswk-swf |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-029961354 | ||
Datensatz im Suchindex
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|---|---|
| adam_text | CONTENTS
ABBREVIATIONS VIII
LIST OF SYMBOLS X
ABSTRACT XV
1 INTRODUCTION 1
1.1 M
OTIVATION............................................................................................................
2
1.2 AUTOMATION IN DRIVER ASSISTANCE AND SAFETY S Y S TE M S
...................................
3
1.2.1 LEVEL 0 - NO
AUTOMATION.......................................................................
6
1.2.2 LEVEL 1 - DRIVER ASSISTANCE
................................................................. 7
1.2.3 LEVEL 2 - PARTIAL A U TO M A TIO N
.............................................................. 8
1.2.4 LEVEL 3 - CONDITIONAL A UTOM
ATION........................................................ 9
1.2.5 LEVELS 4 AND 5 - TOWARDS FULLY AUTOMATED D RIV IN G
......................... 15
1.3 PROBLEM OF OBJECT D ETECTION
.............................................................................
21
1.4 CONTRIBUTION AND OUTLINE OF THE T H E S IS
........................................................... 23
2 SENSOR DATA FUSION ARCHITECTURES 27
2.1
OVERVIEW...............................................................................................................
27
2.1.1
LOW-LEVEL................................................................................................
28
2.1.2
HIGH-LEVEL................................................................................................
31
2.1.3 H Y B RID
......................................................................................................
32
2.1.4 C OM
PARISON.............................................................................................
33
2.2 PROPOSED MODULAR SENSOR DATA FUSION A RCHITECTURE
.....................................
38
2.2.1 OBJECT M O D E
L..........................................................................................
39
2.2.2
SENSOR-LEVEL.............................................................................................
41
2.2.3
FUSION-LEVEL.............................................................................................
42
2.2.4 APPLICATION-LEVEL
...................................................................................
43
3 FUSION STRATEGY AND OBJECT ASSOCIATION 46
3.1 DATA A LIGNM
ENT...................................................................................................
46
3.1.1 S P A TIA
L......................................................................................................
46
3.1.2 T E M P O RA
L................................................................................................
47
3.2 FUSION S TRA TE G Y
...................................................................................................
48
3.2.1 SENSOR-TO-SENSOR
...................................................................................
48
3.2.2 SENSOR-TO-GLOBAL
....................................................................................
49
3.3 A SSO C IATIO N
.........................................................................................................
50
3.3.1 A
RCHITECTURE.............................................................................................
51
3.3.2 FEATURE S ELECTIO N
....................................................................................
52
3.3.3 STATE V
ECTOR.............................................................................................
56
3.3.4 G EOM
ETRICAL.............................................................................................
58
3.3.5 ASSOCIATION V ALID ATIO N
..........................................................................
60
3.3.6 MULTI-OBJECT ASSOCIATION
.......................................................................
60
4 STATE AND COVARIANCE 64
4.1 SENSOR-LEVEL PROCESSING WITH TRACKING A LGORITHM S
........................................
64
4.1.1 FEATURE E X TRA C TIO N
.................................................................................
65
4.1.2 DATA A
SSOCIATION....................................................................................
66
4.1.3 F ILTE RIN G
...................................................................................................
66
4.1.4 TRACK M ANAGEM
ENT.................................................................................
68
4.1.5 KINEMATIC
MODELS....................................................................................
68
4.2 CORRELATION AND SEQUENCE OF SENSOR D A T A
........................................................ 69
4.2.1 PROCESS N O IS E
..........................................................................................
70
4.2.2 COMMON INFORMATION H IS TO R Y
.............................................................. 71
4.2.3 OUT-OF-SEQUENCE D A T A
...........................................................................
72
4.3 TRACK-TO-TRACK FUSION WITH THE COMMON S TA TE
............................................... 73
4.3.1 ADAPTED KALMAN F ILTE
R...........................................................................
74
4.3.2 COVARIANCE
INTERSECTION...........................................................................
76
4.3.3 INFORMATION MATRIX F USIO N
....................................................................
77
4.3.4 C OM
PARISON.............................................................................................
79
4.4 GEOMETRICAL FUSION USING THE OBJECT MODEL
.................................................. 86
4.4.1 DIMENSION E S TIM A TIO N
...........................................................................
87
4.4.2 EXTRACTION OF FUSED
COORDINATES...........................................................
90
5 EXISTENCE PROBABILITY 93
5.1 SENSOR-LEVEL PROCESSING
....................................................................................
93
5.1.1 EXISTENCE P RE D IC TIO N
..............................................................................
94
5.1.2 EXISTENCE U P D A TE
....................................................................................
95
5.1.3 GENERALIZED BAYES EXTENSION
.................................................................
97
5.1.4 MODELING THE PARAM
ETERS........................................................................
98
5.1.5 OBJECT M A N AG E M EN
T..............................................................................
104
5.2 F U S IO N
.......................................................................................................................
105
5.2.1 A
RCHITECTURE.................................................................................................
105
5.2.2 MODELING WITH DEMPSTER-SHAFER EVIDENCE T H E O R Y
................................
105
5.2.3 EXTENSION FOR OCCLUSION M
ODELING............................................................ 110
5.2.4 MODELING THE TRUST P RO B A B ILITY
............................................................... 114
6 CLASSIFICATION 116
6.1 SENSOR-LEVEL PROCESSING
........................................................................................
117
6.1.1 MEASUREMENT CLASSIFICATION
.....................................................................
117
6.1.2 TEMPORAL F ILTE RIN G
.....................................................................................124
6.2 F U S IO N
.......................................................................................................................
124
6.2.1 MODELING WITH THE DEMPSTER-SHAFER EVIDENCE T H E O RY
..........................125
6.2.2 MODELING THE TRUST P RO B A B ILITY
............................................................... 130
7 EVALUATION 133
7.1 TEST VEHICLE AND SENSOR CONFIGURATION
........................................................... 133
7.2 OVERTAKING MANEUVER WITH GROUND TRUTH
.........................................................135
7.2.1 GROUND TRUTH C
ALCULATION........................................................................
136
7.2.2 STATE E S TIM A TIO N
....................................................................................
136
7.2.3 E X IS TE N C E
....................................................................................................140
7.2.4 C
LASSIFICATION..............................................................................................140
7.3 PERFORMANCE IN REAL TRAFFIC
SCENARIOS..................................................................141
7.3.1 DETECTION R A T E
...........................................................................................144
7.3.2 CLASSIFICATION PERFORM
ANCE........................................................................
146
7.3.3 INTEGRATION IN AUTOMATED DRIVING AND ADAS P R O JE C T S
.......................149
8 CONCLUSION AND DISCUSSION 152
A SYNCHRONOUS TRACK-TO-TRACK FUSION ALGORITHMS 155
A.L SIMPLE WEIGHTED F U S IO N
......................................................................................
155
A.2 USE OF CROSS-COVARIANCE
......................................................................................
157
A 3 COVARIANCE
INTERSECTION..........................................................................................158
A.4 C OM
PARISON............................................................................................................
159
B INFORMATION MATRIX FUSION DERIVATION 162
C DETERMINING THE TRUST PROBABILITY 164
C.L EXISTENCE
...............................................................................................................
164
C. 2
CLASSIFICATION.........................................................................................................
165
D EVALUATION SCENARIO DESCRIPTIONS 167
D. L TRAINING D A T A
.........................................................................................................
167
D.2 EVALUATION D A TA
..................................................................................................
167
D.2.1 TEST T RA CK
...................................................................................................
167
D.2.2 REAL T RA FFIC
............................................................................................
168
REFERENCES 172
|
| any_adam_object | 1 |
| author | Aeberhard, Michael 1983- |
| author_GND | (DE-588)1136141693 |
| author_facet | Aeberhard, Michael 1983- |
| author_role | aut |
| author_sort | Aeberhard, Michael 1983- |
| author_variant | m a ma |
| building | Verbundindex |
| bvnumber | BV044562780 |
| classification_rvk | ZO 4650 |
| ctrlnum | (OCoLC)1010492500 (DE-599)HBZHT019476919 |
| discipline | Verkehr / Transport |
| edition | Als Manuskript gedruckt |
| format | Thesis Book |
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| genre_facet | Hochschulschrift |
| id | DE-604.BV044562780 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T07:55:59Z |
| institution | BVB |
| isbn | 9783183804122 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029961354 |
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| physical | XV, 199 Seiten Illustrationen, Diagramme |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | VDI Verlag GmbH |
| record_format | marc |
| series | Fortschritt-Berichte VDI. Reihe 12, Verkehrstechnik/Fahrzeugtechnik |
| series2 | Fortschritt-Berichte VDI. Reihe 12, Verkehrstechnik/Fahrzeugtechnik |
| spelling | Aeberhard, Michael 1983- Verfasser (DE-588)1136141693 aut Object-level fusion for surround environment perception in automated driving applications Michael Aeberhard, M.Sc., München Object level fusion for surround environment perception in automated driving applications Object level fusion in automated driving Als Manuskript gedruckt Düsseldorf VDI Verlag GmbH [2017] © 2017 XV, 199 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Fortschritt-Berichte VDI. Reihe 12, Verkehrstechnik/Fahrzeugtechnik Nr. 804 Dissertation Technische Universität Dortmund 2017 Multisensor (DE-588)4257775-5 gnd rswk-swf Sensorsystem (DE-588)4307964-7 gnd rswk-swf Personenkraftwagen (DE-588)4076001-7 gnd rswk-swf Objekterkennung (DE-588)4314334-9 gnd rswk-swf Fahrerassistenzsystem (DE-588)4622983-8 gnd rswk-swf Umweltmodell Informatik (DE-588)4250471-5 gnd rswk-swf Datenfusion (DE-588)4582612-2 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Personenkraftwagen (DE-588)4076001-7 s Fahrerassistenzsystem (DE-588)4622983-8 s Objekterkennung (DE-588)4314334-9 s Sensorsystem (DE-588)4307964-7 s Multisensor (DE-588)4257775-5 s Datenfusion (DE-588)4582612-2 s Umweltmodell Informatik (DE-588)4250471-5 s DE-604 Fortschritt-Berichte VDI. Reihe 12, Verkehrstechnik/Fahrzeugtechnik Nr. 804 (DE-604)BV000761054 804 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029961354&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Aeberhard, Michael 1983- Object-level fusion for surround environment perception in automated driving applications Fortschritt-Berichte VDI. Reihe 12, Verkehrstechnik/Fahrzeugtechnik Multisensor (DE-588)4257775-5 gnd Sensorsystem (DE-588)4307964-7 gnd Personenkraftwagen (DE-588)4076001-7 gnd Objekterkennung (DE-588)4314334-9 gnd Fahrerassistenzsystem (DE-588)4622983-8 gnd Umweltmodell Informatik (DE-588)4250471-5 gnd Datenfusion (DE-588)4582612-2 gnd |
| subject_GND | (DE-588)4257775-5 (DE-588)4307964-7 (DE-588)4076001-7 (DE-588)4314334-9 (DE-588)4622983-8 (DE-588)4250471-5 (DE-588)4582612-2 (DE-588)4113937-9 |
| title | Object-level fusion for surround environment perception in automated driving applications |
| title_alt | Object level fusion for surround environment perception in automated driving applications Object level fusion in automated driving |
| title_auth | Object-level fusion for surround environment perception in automated driving applications |
| title_exact_search | Object-level fusion for surround environment perception in automated driving applications |
| title_full | Object-level fusion for surround environment perception in automated driving applications Michael Aeberhard, M.Sc., München |
| title_fullStr | Object-level fusion for surround environment perception in automated driving applications Michael Aeberhard, M.Sc., München |
| title_full_unstemmed | Object-level fusion for surround environment perception in automated driving applications Michael Aeberhard, M.Sc., München |
| title_short | Object-level fusion for surround environment perception in automated driving applications |
| title_sort | object level fusion for surround environment perception in automated driving applications |
| topic | Multisensor (DE-588)4257775-5 gnd Sensorsystem (DE-588)4307964-7 gnd Personenkraftwagen (DE-588)4076001-7 gnd Objekterkennung (DE-588)4314334-9 gnd Fahrerassistenzsystem (DE-588)4622983-8 gnd Umweltmodell Informatik (DE-588)4250471-5 gnd Datenfusion (DE-588)4582612-2 gnd |
| topic_facet | Multisensor Sensorsystem Personenkraftwagen Objekterkennung Fahrerassistenzsystem Umweltmodell Informatik Datenfusion Hochschulschrift |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029961354&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV000761054 |
| work_keys_str_mv | AT aeberhardmichael objectlevelfusionforsurroundenvironmentperceptioninautomateddrivingapplications AT aeberhardmichael objectlevelfusioninautomateddriving |