Wavelets in intelligent transportation systems:
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Hoboken, NJ
Wiley
2005
|
| Schlagwörter: | |
| Links: | http://www.loc.gov/catdir/toc/ecip0517/2005021397.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014739432&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Includes bibliographical references and index |
| Umfang: | XVIII, 224 S. |
| ISBN: | 9780470867426 0470867426 |
Internformat
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| 245 | 1 | 0 | |a Wavelets in intelligent transportation systems |c Hojjat Adeli, Asim Karim |
| 264 | 1 | |a Hoboken, NJ |b Wiley |c 2005 | |
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| 500 | |a Includes bibliographical references and index | ||
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| 856 | 4 | |u http://www.loc.gov/catdir/toc/ecip0517/2005021397.html |3 Table of contents | |
| 856 | 4 | 2 | |m HBZ Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014739432&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
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Datensatz im Suchindex
| DE-BY-TUM_call_number | 0002 BAU 885f 2006 A 4135 |
|---|---|
| DE-BY-TUM_katkey | 1544541 |
| DE-BY-TUM_location | 00 |
| DE-BY-TUM_media_number | 040006272268 |
| _version_ | 1821933047186980864 |
| adam_text | Titel: Wavelets in intelligent transportation systems
Autor: Adeli, Hojjat
Jahr: 2005
Contents
Preface xiii
Acknowledgments xv
About the Authors xvii
1 Introduction 1
2 Introduction to Wavelet Analysis 3
2.1 Introduction 3
2.2 Basic Concept of Wavelets and Wavelet Analysis 5
2.2.1 What Is a Wavelet? 5
2.2.2 Wavelet Analysis 5
2.2.3 Types of Wavelets and Wavelet Transforms 8
2.3 Mathematical Foundations 9
2.3.1 Sets and Spaces 10
2.3.2 Sequence and Function Spaces 11
2.3.3 Independent and Basis Sets 12
2.3.4 Metric, Normed, and Inner Product Spaces 12
2.3.5 The L2(R) and L2(Z) Spaces 13
2.3.6 Orthogonality 14
2.4 The Discrete Wavelet Transform (DWT) 14
2.5 Multi-resolution Analysis 16
2.6 Wavelet Bases 18
2.6.1 Constructing Wavelet Bases 18
2.6.2 Example Wavelet Systems 20
Contents
2.7 Computing the DWT 23
2.7.1 Pyramid Algorithm 23
2.7.2 Practical Considerations 24
Feature Extraction for Traffic Incident Detection Using the
Wavelet Transform and Linear Discriminant Analysis 27
3.1 Introduction 27
3.2 incident Detection Algorithms 29
3.3 Discrete Wavelet Transform (DWT) of Traffic Signals 31
3.4 Linear Discriminant Analysis (LDA) 34
3.5 Data Acquisition 37
3.6 Results 38
Adaptive Conjugate Gradient Neural Network-Wavelet
Model for Traffic Incident Detection 45
4.1 Introduction 45
4.2 Improving Traffic Incident Detection 46
4.3 Adaptive Conjugate Gradient Neural Network Model 48
4.4 Incident Detection Results Using Various Approaches 52
4.4.1 LDA 52
4.4.2 DWT and LDA 53
4.4.3 ACGNN 53
4.4.4 DWT, LDA, and ACGNN 54
4.5 Effect of Data Filtering Using the DWT 55
4.6 Relative Contribution of DWT and LDA for Feature
Extraction 58
4.7 Effects of Freeway Geometry on Incident Detection 58
4.7.1 Effect of Curvature 58
4.7.2 Effect of the Number of Lanes 60
4.8 Conclusion 65
Enhancing Fuzzy Neural Network Algorithms Using
Wavelets 67
5.1 Introduction 67
5.2 Discrete Wavelet Transform 69
5.3 Architecture 69
5.4 Training of the Network 72
5.5 Filtering of the Traffic Data Using the DWT 73
5.6 Incident Detection Results 73
Contents
Fuzzy-Wavelet Radial Basis Function Neural Network Model
for Freeway Incident Detection 79
6.1 Introduction 79
6.2 A New Traffic Incident Detection Methodology 80
6.3 Selection of Type and Number of Traffic Data 83
6.4 Wavelet-Based De-noising 85
6.5 Fuzzy Data Clustering 86
6.6 Radial Basis Function Neural Network Classifier 89
6.7 Fuzzy-Wavelet RBFNN Model for Incident Detection 91
6.8 Example 93
6.8.1 Training of the Algorithm 93
6.8.2 Testing of the Algorithm Using Simulated Data 94
6.8.3 Testing of the Algorithm Using Real Data 95
6.9 Conclusion 97
Comparison of the Fuzzy-Wavelet RBFNN Freeway Incident
Detection Model with the California Algorithm 99
7.1 Introduction 99
7.2 California Algorithm #8 100
7.3 Evaluation of the Model 101
7.3.1 Introduction 101
7.3.2 Evaluation Criteria 102
7.3.3 Traffic Data 103
7.3.4 Training and Calibration 104
7.3.5 First Simulation Test - Parametric Evaluation 105
7.3.6 Second Simulation Test - Freeway with On- and
Off-Ramps 111
7.3.7 Test Using Real Data 115
7.4 Concluding Remarks 116
Incident Detection Algorithm Using a Wavelet Energy
Representation of Traffic Patterns 119
8.1 Introduction 119
8.2 Freeway Incident Detection and Patterns in Traffic Flow 120
8.2.1 Single-Station Versus Two-Station Incident
Detection Approaches 121
8.2.2 Upstream and Downstream Flow Patterns 125
8.3 Discrete Wavelet Transform and Signal Energy 129
8.4 Traffic Pattern Feature Enhancement and De-noising 131
x Contents
8.5 Pattern Classification Using Radial Basis Function
Neural Networks 136
8.6 Wavelet Energy Freeway Incident Detection Algorithm 137
8.7 Model Testing 140
8.7.1 Introduction 140
8.7.2 Training 141
8.7.3 First Test Using Simulated Data: Two-Lane
Freeway 141
8.7.4 Second Test Using Simulated Data: Three-Lane
Freeway 142
8.7.5 Third Test Using Simulated Data: Compression
Waves 143
8.7.6 Fourth Test Using Real Data: FSP Project s
1-880 Database 144
8.7.7 Result Summary and Comparison 145
8.8 Conclusion 145
9 Parametric Evaluation of the Wavelet Energy Freeway
Incident Detection Algorithm 147
9.1 Introduction 147
9.2 Factors to Consider in Rural Freeway Incident Detection 148
9.3 Evaluation and Parametric Investigation 150
9.3.1 Goals 150
9.3.2 Data 150
9.3.3 Training and Calibration 151
9.4 Parametric Evaluation Using Simulated Data on Typical
Urban Freeways 152
9.5 False Alarm Performance in the Vicinity of On- and
Off-Ramps 156
9.6 Evaluation on Rural Freeways 157
9.7 Evaluation Using Real Data 163
9.8 Performance Summary and Conclusion 164
10 Case-Based Reasoning Model for Work Zone Traffic
Management 167
10.1 Introduction 167
10.2 Work Zones and Traffic Management 169
10.3 Case-Based Reasoning 170
10.4 Objectives 173
Contents xi
10.5 Scope and Categorization of Parameters 174
10.5.1 Work Zone Type 174
10.5.2 Work Zone Layout 174
10.5.3 Work Characteristics 175
10.5.4 Traffic Flow Characteristics 175
10.5.5 Phases of Work 175
10.5.6 Traffic Control Measures 176
10.5.7 Road User Cost 176
10.6 A Four-Set Case Model for the Work Zone Traffic
Management Domain 176
10.7 Hierarchical Object-Oriented Case Model 179
10.8 Case Representation 181
10.9 Similarity Measures 185
10.10 Case Retrieval 185
10.11 Creation of the Case Base 186
10.12 Creation of Work Zone Traffic Control Plans Using
the CBR System 187
10.13 Illustrative Examples 189
10.13.1 Example 1 191
10.13.2 Example 2 194
10.13.3 Example 3 195
10.14 Conclusion 195
11 Mesoscopic-Wavelet Freeway Work Zone Flow and
Congestion Model 197
11.1 Introduction 197
11.2 Macroscopic Models 200
11.3 Microscopic Models 201
11.4 A Mesoscopic Flow Model for a Freeway Work Zone 203
11.5 Traffic Feature Enhancement Using Discrete Wavelet
Transform 211
11.6 Concluding Remarks 213
References 215
Index 223
|
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| isbn | 9780470867426 0470867426 |
| language | English |
| lccn | 2005021397 |
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| publishDate | 2005 |
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| spellingShingle | Adeli, Hojjat 1950- Wavelets in intelligent transportation systems Intelligent Vehicle Highway Systems Wavelets (Mathematics) Verkehrsleittechnik (DE-588)4133709-8 gnd Transport (DE-588)4060680-6 gnd Analyse (DE-588)4122795-5 gnd Soft Computing (DE-588)4455833-8 gnd |
| subject_GND | (DE-588)4133709-8 (DE-588)4060680-6 (DE-588)4122795-5 (DE-588)4455833-8 |
| title | Wavelets in intelligent transportation systems |
| title_auth | Wavelets in intelligent transportation systems |
| title_exact_search | Wavelets in intelligent transportation systems |
| title_full | Wavelets in intelligent transportation systems Hojjat Adeli, Asim Karim |
| title_fullStr | Wavelets in intelligent transportation systems Hojjat Adeli, Asim Karim |
| title_full_unstemmed | Wavelets in intelligent transportation systems Hojjat Adeli, Asim Karim |
| title_short | Wavelets in intelligent transportation systems |
| title_sort | wavelets in intelligent transportation systems |
| topic | Intelligent Vehicle Highway Systems Wavelets (Mathematics) Verkehrsleittechnik (DE-588)4133709-8 gnd Transport (DE-588)4060680-6 gnd Analyse (DE-588)4122795-5 gnd Soft Computing (DE-588)4455833-8 gnd |
| topic_facet | Intelligent Vehicle Highway Systems Wavelets (Mathematics) Verkehrsleittechnik Transport Analyse Soft Computing |
| url | http://www.loc.gov/catdir/toc/ecip0517/2005021397.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014739432&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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Teilbibliothek Stammgelände
| Signatur: |
0002 BAU 885f 2006 A 4135
Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |