Chuyên Đề Intelligent Vehicle Technologies (Công nghệ xe thông minh)

Intelligent Vehicle Technologies
Part One: Introduction 1
1 The car of the future – Michel Parent 3
1.1 Such a wonderful product . 3
1.2 Difficulties now and ahead 4
1.3 Emerging technologies 13
Part Two: Intelligent vehicle sensor technologies 19
2 The CAN bus – Nan Liang and Dobrivoje Popovic 21
2.1 Introduction 21
2.1.1 What is CAN? 22
2.1.2 How does it work? 23
2.1.3 Main features of the CAN bus 24
2.1.4 Advantages of CAN 25
2.1.5 Application fields 25
2.2 Functional concepts 26
2.2.1 Data exchange concept 26
2.2.2 Message and frame formats 27
2.2.3 Error detection and error handling 30
2.3 Hierarchical organization 31
2.3.1 Layering concept 35
2.3.2 Physical layer 37
2.3.3 Data link layer 41
2.3.4 Application layer 48
2.3.5 CANopen communication profile 49
2.4 Implementations 52
2.4.1 General layout 53
2.4.2 CAN controller 53
2.4.3 CAN products 55
2.4.4 HECAN 55
2.5 CAN applications 55
2.5.1 General overview 55
2.5.2 Applications in vehicles 56
2.5.3 Other CAN applications 58
2.6 CAN-related standards 60
2.6.1 ISO 11519: Low speed CAN 60
2.6.2 ISO 11898: High speed CAN 61
2.6.3 Vehicle-related components standards 62
2.7 The future of CAN 62
References 64
3 Microcontrollers and micro-electronic technology – Kurshid Alam
and Ljubo Vlacic 65
3.1 Introduction 65
3.2 Microcontrollers – an embedded microcomputer 65
3.2.1 Address bus, data bus and control bus 66
3.2.2 Central processing unit 66
3.2.3 Memory 68
3.2.4 Input/output (I/O) interface 68
3.3 Microprocessor or microcontroller? 69
3.4 Product design using a microcontroller 70
3.5 Microtechnology 71
3.5.1 Introduction – brief outline of circuit integration 71
3.5.2 The transistor – the active element of integrated circuits 78
3.5.3 Technologies for monolithic chip integration of circuits 82
3.6 Conclusion 85
References 85
4 Vehicle optical sensor – Yuichi Shinmoto 87
4.1 Introduction 87
4.2 Laser radar 87
4.2.1 The basic principles 88
4.2.2 Example of laser radar 89
4.3 Non-contact ground velocity detecting sensor 90
4.3.1 Comparison of respective methods 90
4.3.2 The principles of the spatial filter method 93
4.3.3 Ground velocity sensors for vehicles 95
4.4 Road surface recognition sensor 96
4.4.1 Measuring reflexibility 97
4.4.2 Surface recognition by the spatial filter method 98
4.4.3 GVS (ground view sensor) 99
4.5 Vehicle sensors for ETC systems 103
4.5.1 Compact vehicle sensor 104
4.5.2 Optical axle-counting sensor 108
4.6 Conclusion 111
References 111
5 Towards intelligent automotive vision systems – Christoph Stiller 113
5.1 Introduction and motivation 113
5.2 Applications of vision in driver assistance systems 116
5.3 Operating principles 118
5.3.1 Components of a vision sensor system 118
5.3.2 Sensor raw data analysis 118
5.4 Applications and results 122
5.4.1 Autonomous driving 123
5.4.2 Heavy truck coupling 125
5.5 Conclusions 127
Acknowledgements 128
References 128
6 From door to door – principles and applications of computer vision
for driver assistant systems – Uwe Franke, Dariu Gavrila, Axel Gern,
Steffen G¨ orzig, Reinhard Janssen, Frank Paetzold and
Christian W¨ ohler 131
6.1 Introduction 131
6.1.1 Vision in cars: why? 132
6.1.2 One decade of research at DaimlerChrysler 132
6.1.3 A comprehensive driver assistance approach 133
6.1.4 Outline of the chapter 134
6.2 Driver assistance on highways 134
6.2.1 Lane recognition 135
6.2.2 Traffic sign recognition (TSR) 141
6.3 Driver assistance in urban traffic 147
6.3.1 Stereo vision 147
6.3.2 Shape-based analysis 152
6.3.3 Road recognition 157
6.4 Object recognition as a classification problem 161
6.4.1 General aspects 161
6.4.2 Traffic lights and signs 166
6.4.3 Pedestrian recognition 169
6.4.4 Further examples 175
6.5 Building intelligent systems 177
6.5.1 ANTS: a multi-agent system 178
6.5.2 UTA II on the road 182
6.6 Summary 185
References 186
7 Radio communication technologies for vehicle information
systems – Shingo Ohmori, Tetsuo Horimatsu, Masayuki Fujise
and Kiyohito Tokuda 189
7.1 Introduction 189
7.1.1 Overview 189
7.1.2 Vision for ITS communications 190
7.1.3 International activities for standardization 194
7.2 ITS communication systems 196
7.2.1 Overview 196
7.2.2 Multimedia communication in a car 196
7.2.3 Current ITS communication systems and services 201
7.2.4 The prospect of growing technology 204
7.3 Vehicle–vehicle and road–vehicle communication systems 206
7.3.1 Overview 206
7.3.2 Road–vehicle communication system 206
7.3.3 Inter-vehicle communication system 213
7.4 Device technologies 219
7.4.1 Overview 219
7.4.2 Optical devices 220
7.4.3 Millimetre-wave devices 224
References 227
8 Global positioning technology in the intelligent transportation
space – Patrick Herron, Chuck Powers and Michael Solomon 229
8.1 History of GPS 229
8.2 The NAVSTAR GPS system 230
8.2.1 GPS system characteristics 231
8.2.2 The navigation message 232
8.3 Fundamentals of satellite-based positioning 234
8.3.1 The basic science of global positioning 234
8.3.2 Positioning techniques 236
8.4 GPS receiver technology 242
8.4.1 GPS receiver components 242
8.4.2 GPS receiver solutions 244
8.4.3 Performance considerations 247
8.5 Applications for GPS technology 249
8.5.1 Basic positioning applications 249
8.5.2 Location-based services 252
8.6 Conclusion 254
Further reading 254
Part Three: Intelligent vehicle decision and control technologies 257
9 Adaptive control system techniques – Muhidin Lelic and Zoran Gajic 259
9.1 Automatic control of highway traffic and moving vehicles 259
9.2 Adaptive control of highway traffic and moving vehicles 261
9.3 Conventional control schemes 262
9.4 Adaptive control – an overview 264
9.4.1 Gain scheduling 265
9.4.2 Model reference adaptive control (direct
adaptive control) 266
9.4.3 Self-tuning control (indirect adaptive control) 266
9.5 System models for adaptive control 267
9.5.1 System identification basics 268
9.5.2 Recursive parameter estimation 268
9.5.3 Estimator initialization 270
9.6 Design of self-tuning controllers 271
9.6.1 Generalized minimum variance (GMV) control 271
9.6.2 Pole placement control 276
9.6.3 Model predictive control 278
9.6.4 Generalized predictive control 279
9.6.5 Generalized pole placement control 281
9.7 Concluding remarks 284
References 284
10 Fuzzy control – Mark Hitchings, Ljubo Vlacic and Vojislav Kecman 289
10.1 Introduction 289
10.1.1 Intelligent control techniques 289
10.1.2 Distance and tracking control – problem definition 293
10.2 Fuzzy control systems – theoretical background 294
10.2.1 Overview 294
10.2.2 Additive fuzzy systems – the standard additive model 297
10.2.3 Fuzzification methods 299
10.2.4 Fuzzy inference methods 301
10.2.5 Defuzzification methods 304
10.3 Fuzzy control systems – design steps 307
10.4 Fuzzy control of distance and tracking 307
10.4.1 Considerations 308
10.4.2 Design strategy 309
10.4.3 System requirements and functions 311
10.4.4 Definitions of linguistic variables 313
10.4.5 System structure 314
10.4.6 Fuzzification method 316
10.4.7 Fuzzy inference rules 321
10.4.8 Defuzzification method 322
10.5 Conclusion 325
10.6 Abbreviations 326
References 327
11 Decisional architectures for motion autonomy –
Christian Laugier and Thierry Fraichard 333
11.1 Introduction 333
11.2 Robot control architectures and motion autonomy 334
11.2.1 Definitions and taxonomy 334
11.2.2 Deliberative architectures 335
11.2.3 Reactive architectures 336
11.2.4 Hybrid architectures 339
11.2.5 Conclusion 348
11.3 Sharp control and decisional architecture for autonomous vehicles 348
11.3.1 Overview of the Sharp architecture 348
11.3.2 Models of the vehicles 350
11.3.3 Concept of sensor-based manoeuvre 351
11.3.4 Reactive trajectory following 352
11.3.5 Parallel parking 355
11.3.6 Platooning 358
11.4 Experimental results 360
11.4.1 Experimental vehicles 360
11.4.2 Experimental run of the trajectory following manoeuvre 361
11.4.3 Experimental run of the parallel parking manoeuvre 362
11.4.4 Experimental run of the platooning manoeuvre 363
11.5 Motion planning for car-like vehicles 364
11.5.1 Introduction 364
11.5.2 Main approaches to trajectory planning 365
11.5.3 Trajectory planning and state-time space 366
11.5.4 Case study 366
11.5.5 Solution algorithm 372
11.5.6 Nonholonomic path planning 378
References 386
12 Brake modelling and control – Dragos B. Maciuca 393
12.1 Brake modelling 393
12.1.2 Brake pedal 394
12.1.3 Vacuum booster 395
12.1.4 Brake hydraulics 400
12.1.5 Disc and drum brakes 405
12.1.6 Simplified model 409
12.1.7 Vehicle model 410
12.2 Brake control 412
12.2.1 Background 412
12.2.2 Vacuum booster control 417
12.2.3 Master cylinder control 419
12.3 Conclusions 421
References 422
13 ACC systems – overview and examples – David Maurel and
St´ ephane Donikian 423
13.1 ACC overview 423
13.1.1 Longitudinal control research 425
13.1.2 Sensor issues 426
13.1.3 ACC products 427
13.2 Systems based on ACC 428
13.2.1 Stop&Go 428
13.2.2 Anti-collision systems 430
13.3 Impact of ACC on traffic and drivers 433
13.3.1 Traffic flow 433
13.3.2 Simulations 435
13.3.3 String stability 437
13.3.4 Impact on traffic flow in a merging situation 438
13.3.5 User acceptance 439
13.3.6 Conclusion 440
References 440
Part Four: Case study 443
14 ARGO prototype vehicle – Alberto Broggi, Massimo Bertozzi,
Gianni Conte and Alessandra Fascioli 445
14.1 Introduction: the ARGO project 445
14.2 The GOLD system 446
14.2.1 The inverse perspective mapping 446
14.2.2 Lane detection 446
14.2.3 Obstacle detection 453
14.2.4 Vehicle detection 457
14.2.5 Pedestrian detection 463
14.2.6 The software system’s architecture 464
14.2.7 Computational performance 467
14.3 The ARGO prototype vehicle 468
14.3.1 Functionalities 468
14.3.2 The data acquisition system 469
14.3.3 The processing system 471
14.3.4 The output system 471
14.3.5 The control system 475
14.3.6 Other vehicle equipments and emergency features 476
14.4 The MilleMiglia in Automatico test 477
14.4.1 Description 477
14.4.2 System performance 481
14.4.3 Statistical analysis of the tour 486
14.4.4 Detailed analysis of one hour of automatic driving 487
14.4.5 Discussion and current enhancements 488
References 493
Index 495