臺灣博碩士論文加值系統

近來嵌入式系統的蓬勃發展，車用型電腦漸漸成為主流，並配備從GPS衛星導航系統到影音播放系統，目前都是車上的標準配備，因此我們實作了一個包含通訊、多媒體、個人化等的多功能數位車用控制台。
一個性能優良的駕駛者與車輛之介面(driver-vehicle interface)下需要具備兩項功能，首先如何有效地預防行車碰撞的發生，其次精確地記錄行車資訊以利事故發生後的調查。而根據統計結果，在車禍事故發生的原因之中，前後車未保持安全的行車間距，佔了大部份的比例，約25%。因此，碰撞預警系統(collision warning system)也是未來汽車上一項必備的功能，因為在行車可能發生碰撞的情況下，它可即時提醒駕駛者並督促駕駛者做適當處置，以減少與前(後)車發生碰撞的機會。再者車上配備一台行車事件記錄器(motor vehicle event data recorder)，可紀錄下汽車行駛中的所有數據資料，假設不幸發生車禍事故，相關的行車紀錄能協助釐清肇事原因。
在本篇論文中，除了建置此多功能控制台外，主要探討的是如何實現一個具有即時性及高成效的碰撞預警系統，並將此系統建立在控制台上，如此提供了行車時預防碰撞的機制。在設計上採用智慧化的計算及推測方法，因此使用適應性神經模糊推論系統(adaptive network-based fuzzy inference system)來實現碰撞預警系統，其運算方式是根據下列因素 - (1)後車速度、(2)兩車相對速度、(3)兩車夾角、(4)兩車垂直間距、(5)兩車水平間距、(6)後車之經度緯度 - 做為預警系統輸入變數來推測危險警告的程度，並以適當不同程度的聲響做為輸出，通知駕駛人及車內其他乘客。
最後我們利用MATLAB的ANFIS Toolbox來模擬及實現我們所提出的碰撞預警系統，期望能夠在行車安全方面，提供一個較精準且更具效能的車用預警系統。

With the arrival of embedded systematic era, the car PC products of all kinds push the market lastingly. All of equipments from GPS satellite navigation system to audio-video amusement become the standard facility in an automobile. Thus, we have implemented a multi-function digital automobile console (MFDAC), including communication, multimedia and individualization etc.
Clearly, a good driver-vehicle interface needs two functions. First, how to effectively prevent traffic crash is taken into account. Next, how to record event data precisely is necessary to facilitate the traffic crash investigation after accident. According to the statistics, the highest ratio of causing traffic crash, say 25%, is related to the problem of tail gating. Therefore, a collision warning system (CWS) is necessary to be one of automobile equipments in the near future. This is because it get driver alert if any possibility of the frontal or rear-end impact collision could be mad and urge the driver promptly responding to this warning by taking appropriate precaution measure against traffic crash so that accident could be avoided. Moreover, equipping with motor vehicle event data record (MVEDR) in automobile is also required so that it is used to collect the necessary data in transit. It can assist the traffic crash investigation to tell what was happened in case of car accident.
Besides, the main objective of this study is to explore how to realize real-time high-performance collision warning system in MFDAC such that it provides the mechanism of precaution against traffic crash in transit. An intelligent computation for system’s inference is considered and hence adaptive network-based fuzzy inference system (ANFIS) is employed to realize collision warning system. In this proposed CWS, the computational inference is based on the following factors (input variables) - (1) host vehicle velocity、(2) relative velocity between two vehicles、(3) angle between two vehicles、(4) vertical distance between two vehicles、(5) horizontal distance between two vehicles、(6) longitude and latitude from GPS - and the buzzer will output warning message by different level inferred from CES so as to alert the driver and passengers inside an automobile.
Finally we utilize ANFIS toolbox of MATLAB to simulate and verify the proposed warning system, and expect to achieve better accuracy and more effectiveness of CWS in vehicle safety.

CHAPTER 1 INTRODUCTION 1
1.1 MOTIVATION 1
1.2 OVERVIEW 2
1.3 ORGANIZATION OF THIS THESIS 4
CHAPTER 2 RELATED WORKS 8
2.1 AUTOMOBILE MULTIMEDIA 8
2.1.1 BENQ – AZTECA 516 8
2.1.2 LIFEVIEW - CAR PC 9
2.1.3 YULON - TOBE 10
2.2 VEHICLE SAFETY 11
2.2.1 COLLISION WARNING SYSTEM (CWS) 11
2.2.1.1 VISION BASED SENSORS 11
2.2.1.2 RADAR SENSORS 12
2.2.1.3 LASER SENSORS 13
2.2.1.4 OTHER SENSORS 14
2.2.2 INTEGRATING SYSTEM 14
2.2.3 THREAT ASSESSMENT ALGORITHMS 14
2.3 MOTOR VEHICLE EVENT DATA RECORDER (MVEDR) 15
2.4 CHAPTER SUMMARY 16
CHAPTER 3 TECHNICAL KNOWLEDGE 18
3.1 IEEE 1616 STANDARD FOR MOTOR VEHICLE EVENT DATA RECORDER 18
3.1.1 DATA ATTRIBUTES AND OUTPUT 19
3.1.2 DATA DICTIONARY 22
3.2 ISO 11898 CONTROLLER AREA NETWORK (CAN) 23
3.2.1 ISO/OSI REFERENCE MODEL 24
3.2.2 PRINCIPLES OF DATA EXCHANGE 26
3.2.3 MESSAGE FRAME FORMAT 27
3.3 FUZZY THEOREM 29
3.3.1 FUZZY SET 30
3.3.2 FUZZY INFERENCE 32
3.3.3 FUZZY SYSTEM 34
3.4 FUZZY NEURAL NETWORK 35
3.4.1 ARTIFICIAL NEURAL NETWORK 36
3.4.1.1 PROCESSING ELEMENT 37
3.4.1.2 LAYER 38
3.4.1.3 NETWORK 39
3.4.2 BACK-PROPAGATION ALGORITHM 40
3.4.3 ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM (ANFIS) 45
CHAPTER 4 HARDWARE ARCHITECTURE 48
4.1 OVERVIEW OF TARGET PLATFORM 48
4.2 FUNCTION BLOCKS AND HARDWARE DEVICES 49
CHAPTER 5 SOFTWARE ORGANIZATION 55
5.1 OVERVIEW OF WINDOWS CE .NET 55
5.2 SOFTWARE FUNCTIONS 56
CHAPTER 6 IMPLEMENTATION 59
6.1 THE IMPLEMENTATION OF AUTOMOBILE DIGITAL CONSOLE 59
6.1.1 THE BUILD-IN SOFTWARE 59
6.1.2 GRAPHIC USER INTERFACE 59
6.1.3 FTP PROGRAM 60
6.1.4 GPS PROGRAM 60
6.1.5 GSM PROGRAM 60
6.1.6 PICTURE VIEWER 61
6.1.7 DICTIONARY 61
6.1.8 TO-DO-LIST 61
6.1.9 DATA EXCHANGER 61
6.1.10 FILE VIEWER 61
6.1.11 DVD PLAYER 65
6.1.11.1 HARDWARE ACCELERATION 65
6.1.11.2 DVD VIDEO PLAYER 66
6.2 THE IMPLEMENTATION OF MVEDR 67
6.2.1 CAN BUS 67
6.2.2 CAN MANAGER 68
6.2.3 MOTOR VEHICLE EVENT DATA RECORDER (MVEDR) 68
6.3 COLLISION WARNING SYSTEMS (CWS) 69
6.3.1 SENSOR STAGE 71
6.3.2 CAN STAGE 72
6.3.3 SCANNING STAGE 72
6.3.4 PREDICT STAGE 74
6.3.5 WARNING STAGE 75
CHAPTER 7 EVALUATION AND RESULT 77
7.1 EVALUATION 77
7.2 RESULTS 82
7.3 SUMMARY 83
CHAPTER 8 CONCLUSIONS AND FUTURE WORKS 91
8.1 CONCLUSIONS 91
8.2 FUTURE WORKS 91

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