臺灣博碩士論文加值系統

現行的駕駛輔助系統是由獨立功能性的感測器所組合而成，用以觀測車子周圍的環境。這些駕駛輔助系統對於有些感測器有著逐漸增加的輔助需求，這些需求是有互補性的以及重疊性的。藉由融合這些感測器的資料，得到一個較大視野的探測環境，在一個適當的範圍內，量測的明確性及精確性是增加的。在不同的行車條件下，選取所需要的物體探測感測器是一個很重要的議題。在這篇論文中， 基於現行的駕駛輔助系統，我們提出了一個新型未來的駕駛輔助系統，藉由在不同的行車條件下的感測器種類及應用，在一個多群組感測器融合的架構下實行出來。在新型未來的駕駛輔助系統上裝設了在現行的駕駛輔助系統上通用的感測器。
在這篇論文中，發展了一個用於駕駛輔助系統的多群組感測器選取的演算法以及透過Borland C++ Builder軟體建立了一個模擬行車的介面。透過整數線性規劃及最佳化理論來描述用於新型未來的駕駛輔助系統的多群組感測器選取的問題。有兩個類型的議題用來考慮系統的實行成果：靜態（離線的感測器選取問題）；動態（線上的行車條件轉換問題）。我們提出了一個目標用來決定離線及線上的最佳化的感測器選取，需要考慮感測器的涵蓋區域、能量、頻寬及可靠度。基於多群組網路、不同的行車條件、行車安全性的轉換以及駕駛的需求，我們發展了一個用來探測行車環境及給予駕駛及時的警示的多群組感測器選取方法。而透過不同的模擬可以說明所提出策略的實行成果。

Fixed Driver Assistance Systems consist of functionally isolated sensors to observe the environment around vehicle. These driver assistance systems have increasing demands for several sensors, which are complementary but also redundant. By fusing these sensors data, a large field of view is obtained and the certainty and precision of the estimates in the relevant regions is increased. It is an important issue to choose necessary object-detecting sensors in different driving conditions. In this thesis, we present a new active Driver Assistance System which is based on fixed Driver Assistance Systems including sensor types and the applications for different driving conditions implements a multi-sensor fusion architecture. Commonly used sensors of fixed Driver Assistance Systems are deployed on the new active Driver Assistance System.
In this thesis, a multi-sensor selection algorithm for Driver Assistance Systems is developed and a driving simulation interface is built up by Borland C++ Builder software. The multi-sensor selection problems for the new active Driver Assistance System is formulated by Integer Linear Programs (ILPs) and optimization theory. To consider system performances, there are two types of issues: static (off-line multi-sensor selection problem); dynamic (on-line driving condition transformation problem). We propose an objective to determine optimal selection of sensors off-line and on-line for guaranteed coverage, energy, bandwidth and reliability of sensors. Based on the multi-sensors network, different driving conditions, driving security transformation and driver commands, a multi-sensors selection approach for detecting the environment around the vehicle and warning the driver in time is developed. The performance of the proposed strategies is illustrated through extensive simulations.

摘要 I
ABSTRACT III
CONTENTS V
LIST OF FIGURES VII
LIST OF TABLES XI
CHAPTER 1 1
INTRODUCTION 1
1.1 MOTIVATION 1
1.2 CONTRIBUTION 6
1.3 ORGANIZATION OF THE THESIS 7
CHAPTER 2 9
BACKGROUND AND LITERATURE SURVEY 9
2.1 LITERATURE SURVEY OF RELATED RESEARCHES 9
2.2 FIXED DRIVER ASSISTANCE SYSTEMS 13
2.3 ACTIVE DRIVER ASSISTANCE SYSTEMS 19
2.4 MATHEMATICAL PRELIMINARY 22
2.4.1 Optimization Problem 22
2.4.2 Linear Programming 24
2.4.3 Integer Linear Programs 25
CHAPTER 3 35
PROBLEM FORMATION 35
3.1 PROBLEM DESCRIPTION 35
3.1.1 Multiple Object-Detecting Sensors 36
3.1.2 Different Driving Conditions 45
3.2 MULTI-SENSOR SELECTION NETWORK 47
CHAPTER 4 51
ANALYSIS AND DESIGN OF MULTI-SENSOR SELECTION SYSTEM 51
4.1 MULTI-SENSOR SELECTION SYSTEM ARCHITECTURE 51
4.1.1 Multi-Sensor Selection Problem Definition 52
4.1.2 Multi-Sensor Selection System Architecture 59
4.2 MULTI-SENSOR SELECTION SYSTEM PERFORMANCE 62
4.2.1 Off-Line Multi-Sensor Selection Problem 63
4.2.2 On-Line Driving Condition Transformation Problem 75
4.2.3 Multi-Sensor Selection Algorithm 83
CHAPTER 5 91
SIMULATION STUDY 91
5.1 SIMULATION SETUP 91
5.1.1 Simulator and Development Environment 92
5.1.2 Simulation Scenarios 96
5.2 CASE STUDY: SIMULATION OF STRAIGHT DRIVING 100
5.2.1 Description of Straight Driving Simulation 100
5.2.2 Simulation of Straight Driving 102
5.3 CASE STUDY: SIMULATION OF CHANGE LANE DRIVING 111
5.3.1 Description of Change Lane Driving Simulation 111
5.3.2 Simulation of Change Lane Driving 115
5.4 COMPARISON OF MULTI-SENSOR SELECTION RESULTS 125
CHAPTER 6 131
CONCLUSION 131
APPENDIX A 135
THREE TYPES OF ILPS 135
APPENDIX B 139
SENSOR NETWORK 139
B.1 Sensor Network Definition 139
B.2 Sensor Network Application 144
REFERENCES 149
PAPERS: 149
WEBSITES: 153
BOOKS: 153

Papers:
[1: Leohold and Schmidt 2004]
Leohold, J. and Schmidt, C., “Communication requirements of future driver assistance systems in automobiles,” in proceeding of IEEE International Workshop on Factory Communication System, pp. 167-174, vol. 22-24, Sep., 2004.
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Rabel, M., Schmeiser, A., and Grossmann, H.P., “Communication architecture for sensorfusion systems,” in proceedings of IEEE Intelligent Vehicles Symposium, pp. 363-368, vol. 14-17, June, 2004.
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Tanaka, J., Ishida, S., Kawagoe, H. and Kondo, S., “Workload of using a driver assistance system,” in proceedings of IEEE Intelligent Transportation Systems, pp. 382-386, vol. 1-3, Oct., 2000.
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Kaempchen, N. and Dietmayer, K., "Data synchronization strategies for multi-sensor fusion,“ in proceedings of ITS 2003, 10th World Congress on Intelligent Transportation Systems, Madrid, Spain, Issued No.2250, November 2003.
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Becker, J.C. and Simon, A., "Sensor and navigation data fusion for an autonomous vehicle," in proceeding of IEEE Intelligent Vehicle Symposium, pp. 156-161, vol. 3-5, Oct., 2000.
[6: Becker 1999]
Becker, J., "Fusion of data from the object-detecting sensors of an autonomous vehicle," in proceedings of IEEE International Conference on Intelligent Transportation Systems, pp. 362-367, vol. 5-8, Oct., 1999.
[7: Torkkola et al. 2004]
Torkkola, K., Venkatesan, S. and Huan Liu, "Sensor selection for maneuver classification," in proceedings of IEEE Intelligent Transportation Systems, pp. 636-641, vol. 3-6, Oct., 2004.
[8: Isler and Bajcsy 2005]
Isler, V. and Bajcsy, R., "The sensor selection problem for bounded uncertainty sensing models," in proceedings of IEEE 4th International Symposium on Information Processing in Sensor Networks, pp. 151-158, vol. 15, April, 2005.
[9: Patel et al. 2005]
Patel, M., Chandrasekaran, R. and Venkatesan, S., "Energy efficient sensor, relay and base station placements for coverage, connectivity and routing," in proceedings of IEEE 24th International Performance, Computing, and Communications Conference, pp. 581-586, vol. 7-9, April, 2005.
[10: Brooks et al. 2004]
Brooks, A., Williams, S. and Makarenko, A., “Automatic online localization of nodes in an active sensor network,” in proceedings of IEEE International Conference on Robotics and Automation, pp. 4821-4826, vol. 5, 26 April-1 May, 2004.
[11: Poduri and Sukhatme 2004]
Poduri, S. and Sukhatme, G.S., “Constrained coverage for mobile sensor networks,” in proceedings of IEEE International Conference on Robotics and Automation, pp. 165-171, vol. 1, 26 April-1 May, 2004.
[12: Batalin and Sukhatme 2004]
Batalin, M.A. and Sukhatme, G.S., “Using a sensor network for distributed multi-robot task allocation,” in proceedings of IEEE International Conference on Robotics and Automation, pp. 158-164, vol. 1, 26 April-1 May, 2004.
[13: Popa et al. 2004]
Popa, D.O., Stephanou, H.E., Helm, C. and Sanderson, A.C., “Robotic deployment of sensor networks using potential fields,” in proceedings of IEEE International Conference on Robotics and Automation, pp. 642-647, vol. 1, 26 April-1 May, 2004.
[14: Batalin et al. 2004]
Batalin, M.A., Sukhatme, G.S. and Hattig, M., “Mobile robot navigation using a sensor network,” in proceedings of IEEE International Conference on Robotics and Automation, pp. 636-641, vol. 1, 26 April-1 May, 2004.
[15: Peterson and Rus 2004]
Peterson, R. and Rus, D., “Interacting with sensor networks,” in proceedings of IEEE International Conference on Robotics and Automation, pp. 180-186, vol. 1, 26 April-1 May, 2004.
[16: Makarenko et al. 2004]
Makarenko, A., Brooks, A., Williams, S., Durrant-Whyte, H. and Grocholsky, B., “A decentralized architecture for Active Sensor Networks,” in proceedings of IEEE International Conference on Robotics and Automation, pp. 1097-1102, vol. 2, 26 April-1 May, 2004.
[17: Kian Hsiang Low et al. 2004]
Kian Hsiang Low, Wee Kheng Leow Ang, and M.H., Jr., “Reactive, distributed layered architecture for resource-bounded multi-robot cooperation: application to mobile sensor network coverage” in proceedings of IEEE International Conference on Robotics and Automation, pp. 3747-3752, vol. 4, 26 April-1 May, 2004.
[18: Jindong Tan et al. 2004]
Jindong Tan, Ning Xi, Weihua Sheng and Jizhong Xiao, “Modeling multiple robot systems for area coverage and cooperation,” in proceedings of IEEE International Conference on Robotics and Automation, pp. 2568-2573, vol. 3, 26 April-1 May, 2004.
[19: Corke et al. 2004]
Corke, P., Hrabar, S., Peterson, R., Rus, D., Saripalli, S. and Sukhatme, G., “Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle” in proceedings of IEEE International Conference on Robotics and Automation, pp. 3602-3608, vol. 4, 26 April-1 May, 2004.
[20: Jones et al. 2003]
Jones, E.D., Roberts, R.S. and Hsia, T.C.S., “STOMP: a software architecture for the design and simulation of UAV-based sensor networks” in proceedings of IEEE International Conference on Robotics and Automation, pp. 3321-3326, vol. 3, 14-19 Sept, 2003.
[21: Rahimi et al. 2003]
Rahimi, M., Shah, H., Sukhatme, G.S., Heideman, J. and Estrin, D., “Studying the feasibility of energy harvesting in a mobile sensor network” in proceedings of IEEE International Conference on Robotics and Automation, pp. 19-24, vol. 1, 14-19 Sept, 2003.
[22: Akyildiz et al. 2002]
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y. and Cayirci, E., “A survey on sensor networks,” IEEE Communications Magazine, pp. 102-114, August, 2002
[23: Sohrabi et al. 2000]
Sohrabi, K., Gao, J., Ailawadhi, V. and Pottie, G.J., “Protocol for Self-Organization of a wireless sensor network,” IEEE Personal Communication, pp. 16-27, Oct., 2000.
Websites:
[24: Hella]
http://www.hella.de
Germany Automotive Industry
[25: PReVENT]
http://www.prevent-ip.org/en
PReVENT is a European automotive industry activity co-funded by the European Commission to Contribute to road safety.
[26: Continetal TEMIC]
http://www.conti-online.com
Germany Automotive Systems Company
[27: Invent]
http://www.invent-online.de/index.html
Germany Intelligent Traffic and User Friendly Technology
Books:
[28: Pedregal 2004]
Pedregal, P., Introduction to Optimization, First Edition, Springer, 2004.
[29: Winston 2004]
Winston, W.L., Operations Research: Applications and Algorithms, Fourth Edition, Thomson Brooks/Cole, 2004.
[30: Nemhauser et al. 1989]
Nemhauser, G.L., Rinnooy Kan, A.H.G. and Todd, M.J., Handbooks in Operations Research and Management Science Volume 1: Optimization, First Edition, North-Holland, 1989.
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Williams, H.P., Model Building in Mathematical Programming, Forth Edition, WILEY, 1999.
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Nauss, R.M., Parametric Integer Programming, First Edition, Columbia, 1979.
[33: Plane and McMillan 1971]
Plane, D.R. and McMillan, C., Discrete Optimization: Integer Programming and Network Analysis for Management Decisions, First Edition, Prentice-Hall, 1971.
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Greenberg, H., Integer Programming, First Edition, Academic Press, 1971.
[35: Siegwart and Nourbakhsh 2004]
Siegwart, R. and Nourbakhsh, I.R., Introduction to Autonomous Mobile Robots, First Edition, MIT Press, 2004.