Advanced vehicles and infrastructure systems: computer applications, control and automation
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Chichester [u.a.]
Wiley
1997
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XVIII, 502 S. Ill., graph. Darst. |
| ISBN: | 0471956457 |
Internformat
MARC
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| 245 | 1 | 0 | |a Advanced vehicles and infrastructure systems |b computer applications, control and automation |c Christopher O. Nwagboso [ed.] |
| 264 | 1 | |a Chichester [u.a.] |b Wiley |c 1997 | |
| 300 | |a XVIII, 502 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
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| 700 | 1 | |a Nwagboso, Christopher O. |4 edt | |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-017409476 | ||
Datensatz im Suchindex
| _version_ | 1804138953982345216 |
|---|---|
| adam_text | Contents
Preface xv
List of Contributors xvii
Acknowledgments xjx
PART 1 INTELLIGENT TRANSPORT SYSTEMS 1
1 Introduction to Intelligent Transport Systems 3
C O Nwagboso
1.1 Introduction 3
1.2 Intelligent Transport Systems 4
1.2.1 European Union Initiatives 5
1.2.2 US Initiatives 10
1.2.3 Japanese initiatives 13
1.3 Elements of Intelligent Transport Systems 21
1.3.1 Traffic Management and Control 21
1.3.2 Public Transport and Freight Operation Systems 22
1.3.3 Mobile Telecommunications Systems 23
1.3.4 Debiting and Smart Card Systems 24
1.3.5 User Information Systems 26
1.3.6 Advanced Vehicle Safety Systems 26
1.4 Intelligent Transport Systems User Requirements 28
1.4.1 Public Transport 29
1.4.2 Ereight Operators 29
1.4.3 Fleet/Freight Drivers 30
1.4.4 Private/Individual Users 30
1.4.5 Network Operators 30
1.5 Conclusions 31
vi CONTENTS
2 Microprocessor-based Control Technique for Vehicle
Performance Optimization 33
S R Vishnubhotla
2.1 Introduction 33
2.2 Preliminaries 34
2.2.1 Sensors and Actuators 35
2.2.2 A/D and D/A Converters 36
2.2.3 Multiplexing, Demultiplexing and Buses 36
2.2.4 Multiprocessor Architecture 38
2.3 Vehicle Control and Diagnostics 40
2.3.1 Control Parameters 40
2.3.2 Controls 41
2.3.3 Diagnostics 42
2.4 Small Vehicles 42
2.4.1 Analysis of the Parameters 43
2.4.2 Control of Body Parameters 44
2.4.3 Control of Engine/Dynamic Parameters 45
2.5 Complex Vehicles 46
2.5.1 Description of the System 47
2.5.2 Operation of the System 47
2.6 Future Automobiles 49
2.7 Conclusions 49
3 Automotive Electronic Trends and their Influence on Intelligent
Transport Systems 53
B F Heinrich
3.1 Introduction 53
3.2 Automotive Electronics Trends 54
3.2.1 Historical Trends 55
3.2.2 Present Trends 57
3.2.3 Future Trends 61
3.3 Technology Push Versus Market Pull 66
3.4 Intelligent Vehicle-Highway Systems Deployment 67
3.5 Driver Acceptance 70
3.6 Conclusions 71
PART 2 DYNAMICS OF INTELLIGENT VEHICLES 73
4 Intelligent Vehicle Systems and Control 75
C O Nwagboso
4.1 Introduction 75
4.2 Vehicle Electronics and Control 77
4.2.1 Vehicle Sensors 7g
4.2.2 Basic Control Systems Technology 87
4.2.3 Vehicle Following 94
4.3 Collision Avoidance Systems 97
CONTENTS vii
4.4 Cruise Control System 100
4.4.1 Intelligent Cruise Control System 101
4.5 Navigation and Route Guidance Systems 103
4.5.1 Vehicle Navigation Systems 104
4.5.2 Dynamic Route Guidance Systems 115
4.6 Communication Systems 117
4.7 Driver Vision Enhancement 120
4.8 Conclusions 122
5 Intelligent Automotive Systems: Development in Full-time
Chassis Motion Spheres for Intelligent Vehicles 125
B T Fijalkowski
5.1 Introduction 125
5.2 Proof-of-concept full-time 4WS X 4WA x 4WD x 4WB Intelligent Road 126
Vehicles
5.3 Purpose of Integrated IRV Motion Control Between Individual 4WS, 4WA, 128
4WD and 4WB Controls
5.3.1 Dual-Mode Hybrid 4WS Conversion Sphere 131
5.3.2 Predictive and Adaptive 4WA Suspension Sphere 134
5.3.3 Series Hybrid 4WD Propulsion Sphere 136
5.3.4 Anti-wheel-lock and Anti-wheel-spin 4WB Dispulsion Sphere 140
5.4 Conclusions 141
6 Trends in Traction Control for Improved Vehicle Dynamics 143
S Shiraishi, O Yamanoto, KKin and Y Akuta
6.1 Introduction 143
6.2 History of Traction Control Systems 144
6.3 Recent Trends in Traction Control 146
6.3.1 Nissan ETS System 147
6.3.2 Porcshe Tiptronic System 148
6.3.3 Mitsubishi TCL System 148
6.3.4 Honda TCS System 151
6.4 Fundamental Form of Traction Control 151
6.5 Classification of Types of Traction Control 153
6.6 Hierarchical Relationships in Traction Control Systems 155
6.7 Harmonizing Traction Control with Other Systems 158
6.8 Conclusions 165
PART 3 AUTONOMOUS VEHICLES SYSTEMS 167
7 A Closed-loop Four-wheel-steering Control System: Toward
an Autonomous Vehicle 169
E C Yeh, RHWu and] C Hsu
7.1 Introduction 169
7.2 4WS Control System 170
7.2.1 An Overview of the 4WS Control System 170
7.2.2 A Multi-input 4WS System 172
viii CONTENTS
7.3 The Closed-loop 4WS Control System Towards an Autonomous Vehicle 181
7.3.1 Intelligent Control Centre 183
7.3.2 Closed-loop 4WS Vehicle System 185
7.3.3 Environment Sensing System 185
7.3.4 On-board Monitoring and Emergency Handling 186
7.4 Future Prospects for the Steering Control System 186
7.5 Conclusions 187
8 Collision-free Manoeuvring and Control for an Autonomous
Vehicle 189
KI Trovato
8.1 Introduction 189
8.2 Framework 189
8.3 Algorithm Analysis and Accuracy 193
8.4 The Fire Exit Problem 194
8.5 The Robot Path Planning Problem 195
8.6 The Vehicle Manoeuvring Problem 196
8.7 A Forward-only Constraint 201
8.8 Use of the System for Complex Manoeuvres and Larger Areas 201
8.9 A Radio-controlled Example 203
8.10 High-speed Vehicle Manoeuvring 205
8.11 Invitation 206
8.12 Conclusions 206
9 Optically-based Underground Mine Vehicle Guidance 209
R Hurteau, Y Laperriere and M St Amant
9.1 Introduction 209
9.1.1 Mine Context 210
9.1.2 Automation of Ore Transportation 211
9.2 Description of the System 213
9.2.1 Demonstration Prototype 216
9.3 Optical Detector 217
9.3.1 Guideline and Milestones 217
9.3.2 Guideline Detector 219
9.3.3 Image Analysis 219
9.3.4 Geometrical Model of the Optical Detector 221
9.3.5 Navigation Errors 223
9.3.6 Performance 224
9.3.7 Simulation of the Optical Detector 225
9.4 Motion Control of the Vehicle 227
9.4.1 Model of the Vehicle 227
9.4.2 Design Model and Motion Controller 229
9.4.3 Speed Controller 231
9.4.4 Position Orientation Controller 231
9.5 Simulation and Experimental Results 233
9.5.1 Gain Adaptation with the Speed 233
9.5.2 Tracking Properties 235
CONTENTS ix
9.6 Test on a Load Haul Dump Vehicle 239
9.7 Conclusions 241
10 Application of Neural Networks to Guidance of Autonomous
Vehicles 243
A S Pandya and P G Luebbers
10.1 Introduction 243
10.2 Autonomous Land Vehicle Application 245
10.3 Design Rationale 246
10.3.1 Determination of Road from Non-road Portions of Image Data 247
10.3.2 Determination of Guidance Controller 247
10.3.3 A General Framework for an Autonomous Land Vehicle Control System 248
10.4 Description of Neural Network/Fuzzy Logic Controller for HMMWV 249
10.4.1 Edge Extraction and Edge Modelling 250
10.4.2 Feature Extraction 250
10.4.3 Feature Extraction Results 252
10.4.4 Neural Network Feature Approximation Results 252
10.4.5 Neural Network/Fuzzy Logic Controller 252
10.5 Conclusion 256
PART 4 VEHICLE NAVIGATION AND GUIDANCE 259
11 Camera Telemeter Multisensory System for Obstacle Avoidance 261
/ Trassoudaine, J Gallice and F Collange
11.1 Introduction 261
11.2 The Multisensor 262
11.2.1 Description and Performances of the Multisensor 262
11.2.2 The Multisensor Calibration 267
11.2.3 A Smart Sensor 272
11.3 Obstacle Detection and Tracking by a Multisensorial Approach 277
11.3.1 Obstacle Detection 277
11.3.2 Obstacle Tracking 279
11.3.3 Results 283
11.4 Conclusion 284
12 Trends in Vehicle Navigation and Guidance Systems for
Intelligent Motoring 289
A M Parkes
12.1 Introduction 289
12.2 Route Planning 291
12.3 Route Navigation 291
12.4 Route Guidance 291
12.5 Conclusions 300
x CONTENTS
13 Simulation Modelling of Route Guidance Control Strategies 303
N B Hounsell and A Stevens
13.1 Introduction 3^3
13.1.1 Development of Dynamic Route Guidance 303
13.1.2 Control Strategies 304
13.1.3 The Need for Simulation Modelling 305
13.2 Simulation 305
13.2.1 Simulation Requirements 305
13.2.2 Simulation Options 306
13.2.3 Developments of Contram 307
13.2.4 Model Features and Applications 309
13.3 Conclusions 316
PART 5 INFORMATICS SYSTEMS 319
14 Development of Safe Road Transport Informatic Systems 321
H Trier and G Heuser
14.1 Introduction 321
14.2 Notes on Terminology 322
14.2.1 Choice of Jargon 322
14.2.2 Fault, Error, Failure 323
14.2.3 Verification and Validation 323
14.3 The Safety Task Force 324
14.4 Systems Consideration 325
14.4.1 Definition of Systems 325
14.4.2 Systems Configuration 325
14.4.3 Systems Safety Considerations 326
14.5 Process of Integrity Level Assignment 330
14.5.1 Hazard Identification and Specification 330
14.5.2 Assignment of Controllability Category and its Integrity Level 331
14.6 Approach to Attain Safety 332
14.7 Safety Requirements 333
14.8 Consideration of Failure 333
14.9 Measures Against Failure 334
14.9.1 Measures to Avoid Failures 336
14.9.2 Measures to Control Faults 337
14.9.3 Fault Detection Measures 338
14.9.4 Effectiveness of Measures 341
14.10 Assignment of Measures to Integrity Levels 341
14.11 Conclusion 341
15 Information Systems for Public Transport Management 343
B De Saint-Laurent
15.1 Introduction 343
15.1.1 Scope and Contributions 343
15.1.2 Some Definitions 343
CONTENTS xi
15.2 What is an Advanced Public Transport System? 344
15.2.1 The APTS Rationale: Where Supply Meets Demand 344
15.2.2 The APTS Response 345
15.2.3 Achievements of APTS so far 349
15.2.4 Evaluation of APTS Impact 349
15.2.5 Limits of Existing Systems 350
15.2.6 New Issues 358
15.3 Computer-based Advanced Solutions 358
15.3.1 The Cassiope/EuroBus/Transmodel Framework in Drive 358
15.3.2 Implementation Aspects 359
15.3.3 Other Needs for Standardization 366
15.4 A Vital Issue for Public Transport 366
16 Analysis of Road Database Management Structure 371
Y Loyaerts
16.1 Introduction 371
16.2 Road Database Information 372
16.2.1 Data Levels 372
16.2.2 Data Domains of a Road Database 373
16.2.3 Network Definition 375
16.3 Data Collection 376
16.4 Data Quality 377
16.4.1 Quality of Information Collection 377
16.4.2 Quality of Database Updating 378
16.4.3 Quality During Exchange of Information 379
16.5 Distribution of Road Data 379
16.5.1 Road Databases Interested Parties 380
16.5.2 Road Reference System 381
16.5.3 Neighbouring Data 382
16.6 Data Exchange 382
16.6.1 Liaison with Other Bodies 383
16.6.2 Data Exchange 384
16.7 The Way Forward 385
16.7.1 Future Actions 385
16.8 Conclusions 387
PART 6 AUTOMATED TRAFFIC CONTROL SYSTEMS 391
17 Video Image Understanding for Automatic Traffic
Monitoring and Control 393
A Rourke and M G H Bell
17.1 Introduction 393
17.2 Practicalities of Image Processing for Traffic Monitoring 394
17.3 Loop Emulation 397
17.3.1 The TULIP System 398
17.3.2 Results of TULIP Processing 399
17.4 Queue and Congestion Monitoring Using Image Processing 400
17.4.1 The Fast_Q System 401
17.4.2 Experimental Results 404
xii CONTENTS
17.5 Vehicle Classification 405
17.5.1 Model Creation 406
17.5.2 Three-dimensional Modelling 407
17.5.3 Camera Calibration 408
17.5.4 Vehicle Modelling 410
17.5.5 Model Construction 410
17.5.6 Image Segmentation 411
17.5.7 Model-image Matching for Vehicle Classification 412
17.6 Conclusions 414
18 Automatic Vehicle Model Classification 417
M Varga and] Radford
18.1 Introduction 417
18.2 Region Cueing Algorithm 417
18.2.1 Edge Extraction 418
18.2.2 Line Type Fractal Discriminant 418
18.2.3 Circle/Arc Finding Hough Transform 419
18.2.4 Wheel-base Detection 419
18.2.5 Pre-processing 420
18.3 Model Classification 420
18.3.1 Data Representation 420
18.3.2 Dynamic Programming 420
18.3.3 Edge Based Classification 421
18.3.4 Modification of the Edge-based Classification 423
18.4 Experimental Set-up 425
18.5 Conclusions 425
19 Model Based Collaboration Architectures for Traffic Control 433
M Irgens, C Krogh and H Traettebers
19.1 Introduction 433
19.2 Methodological Preliminaries 434
19.3 The Problem: a Brief Analysis 434
19.4 Solution Elements: the Models 436
19.4.1 Abstraction and Granularity 436
19.4.2 Imperative and Declarative Elements 436
19.4.3 Imperative Elements 437
19.4.4 Declarative Elements 440
19.5 Model-based Collaboration: Architectures 444
19.5.1 Requirements 444
19.5.2 A Model-based Architecture 445
19.5.3 A Generic Tasks Architecture 446
19.5.4 A Blackboard-based Architecture 448
19.5.5 Cooperating Supervised Agents 449
19.6 Solution Elements Instantiated: IUTCS and KITS 451
19.7 Conclusion 452
CONTENTS xiii
20 Application of Artificial Intelligence and Expert Systems
to Traffic Control 455
G Ambrosino, M Bielli and M Boero
20.1 Introduction 455
20.2 Knowledge-based and Expert Systems Approach to Traffic Control 456
20.2.1 Current Problems with Conventional UTC Technology 456
20.2.2 Roles 458
for Knowledge-based Techniques in Urban Traffic Control Systems
20.3 A Knowledge-based Architecture for Traffic Control 459
20.3.1 The Blackboard Approach 460
20.3.2 The IUTCS Architecture 461
20.3.3 The knowledge sources 462
20.3.4 Knowledge Representation 466
20.4 Testing the IUTCS Prototype 467
20.4.1 Testing Traffic Data Inference Agent 468
20.4.2 Testing the Traffic Control Agent 469
20.5 Conclusions 471
21 Application of a Neural Network with Computer
Vision for a Vehicle Identification and Detection System 475
K Kanayame and T Naito
21.1 Introduction 475
21.2 Image Processing for Traffic Applications 476
21.3 Vehicle Identification System 477
21.3.1 Extraction of Plate Character String and Cut-out of Character 477
21.3.2 Normalization and Image Transfer 477
21.3.3 Character Recognition by the Neural Network 478
21.4 Vehicle Detection System 480
21.4.1 Pre-processing for a Vehicle Detection System 480
21.4.2 Image Analysis by the Neural Network for a Car Detection System 481
21.5 Conclusions 487
Subject Index 489
|
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| indexdate | 2024-07-09T21:36:23Z |
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| isbn | 0471956457 |
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| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017409476 |
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| spelling | Advanced vehicles and infrastructure systems computer applications, control and automation Christopher O. Nwagboso [ed.] Chichester [u.a.] Wiley 1997 XVIII, 502 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Verkehrsleittechnik (DE-588)4133709-8 gnd rswk-swf Satellitennavigation (DE-588)4202846-2 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Verkehrsleittechnik (DE-588)4133709-8 s Satellitennavigation (DE-588)4202846-2 s DE-604 Nwagboso, Christopher O. edt HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017409476&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Advanced vehicles and infrastructure systems computer applications, control and automation Verkehrsleittechnik (DE-588)4133709-8 gnd Satellitennavigation (DE-588)4202846-2 gnd |
| subject_GND | (DE-588)4133709-8 (DE-588)4202846-2 (DE-588)4143413-4 |
| title | Advanced vehicles and infrastructure systems computer applications, control and automation |
| title_auth | Advanced vehicles and infrastructure systems computer applications, control and automation |
| title_exact_search | Advanced vehicles and infrastructure systems computer applications, control and automation |
| title_full | Advanced vehicles and infrastructure systems computer applications, control and automation Christopher O. Nwagboso [ed.] |
| title_fullStr | Advanced vehicles and infrastructure systems computer applications, control and automation Christopher O. Nwagboso [ed.] |
| title_full_unstemmed | Advanced vehicles and infrastructure systems computer applications, control and automation Christopher O. Nwagboso [ed.] |
| title_short | Advanced vehicles and infrastructure systems |
| title_sort | advanced vehicles and infrastructure systems computer applications control and automation |
| title_sub | computer applications, control and automation |
| topic | Verkehrsleittechnik (DE-588)4133709-8 gnd Satellitennavigation (DE-588)4202846-2 gnd |
| topic_facet | Verkehrsleittechnik Satellitennavigation Aufsatzsammlung |
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