||Research on Integrated Positioning and Active Safety of Intelligent Vehicles
||Department of Electrical Engineering
Safety driving system
Addressed on the studies of intelligent vehicle safety driving system (IVSDS), several advanced driver assistance systems (ADAS) have been recently developed for better convenience and safety. These ADASs can be normally separated into active and passive safety systems. The former includes blind spot detection, lane departure warning, forward collision warning, adaptive cruise control, and adaptive headlights, and the latter contains seat belts, car airbags, and vehicle body structures. Advanced driver assisted vehicles employ highly accurate/reliable positioning and stable/real-time vehicle communication system to assist the drivers to control the vehicle traveling at specific driving situations to guarantee safety. GPS has become one of the most crucial navigation systems. However, GPS cannot provide an uninterrupted positioning solution when the vehicle drives in areas such as urban canyons or tunnels, because the system suffers from signal blockage and multipath efforts. In order to deal with these problems, GPS/Inertial Navigation System (INS) integrated navigation technique has become the main direction to facilitate a continuous positioning solution. Moreover, stable and real-time vehicular dedicated short-range communication (DSRC) is an important index for IVSDS. The improvement of the stability and reliability will prompt the development of intelligent vehicles further based on the real-time information exchanged by vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I).
The contributions of this dissertation address on vehicular DSRC, satellite navigation, and inertial sensing to explore the research of integrated positioning and active collision avoidance system (CAS). Firstly, this dissertation performs the analysis and study of the current specifications for the DSRC system. According to the discussion on a vehicular control system, the results are planned for the basis of the DSRC applications. Furthermore, the safety driving system needs accurate and reliable speed and heading angle data for vehicle controls. However, the heading angles derived based on GPS position information are sometimes misleading, especially when the vehicle speed is low. This dissertation proposes the use of the sensor fusion approach to address the issue. An adaptive two-stage filter is proposed to provide the benefits of simple implementation, cost-effectiveness, ease-of-tuning, and performance assurance. Based on the integrated positioning system and the DSRC system, the study further investigates active CAS. For active safety requirements of the automatic driving, this dissertation develops a hierarchical structure to facilitate the integration of different types, characteristics, accuracy of sensing data in combination with the vehicle dynamics and environment model. This research uses collision avoidance control and overtaking control of automatic driving as examples for detailed design, simulation and performance assessment.
List of Figures viii
List of Tables x
List of Abbreviation xi
Chapter 1 Introduction 1
1.1 Background 2
1.2 Motivation 4
1.3 Contributions 9
1.4 Organization 10
Chapter 2 DSRC-Based Vehicular Control System 11
2.1 DSRC 12
2.1.1 System Implementation 14
2.1.2 Operating Principle 16
2.2 High Dynamic GPS Receiver 19
2.2.1 Hardware Implementation 19
2.2.2 Software Design 21
2.2.3 Performance Analysis for High Dynamic GPS Receiver 22
2.3 Summary 26
Chapter 3 Sensor-Fusion for High Accuracy in Vehicular Speed and Heading Angle Estimation 27
3.1 Determination of Speed and Heading Angle 29
3.1.1 Difference-Based Approach 29
3.1.2 Filter-Based Approach 35
3.1.3 Sensor-Fusion Approach 39
3.2 Simulation Results 45
3.2.1 Constant Speed and Heading Angle Case 45
3.2.2 Changing Speed/Heading Angle Case 49
3.3 Experimental Results 53
3.4 Summary 57
Chapter 4 Active Collision Avoidance System of Intelligent Vehicles 58
4.1 Control System 60
4.2 Safety System 67
4.3 Simulation Results 70
4.3.1 Active CAS 71
4.3.2 Effect of 74
4.3.3 Effect of 75
4.4 Experimental Results 76
4.5 Summary 78
Chapter 5 Conclusions 79
5.1 Conclusions 79
5.2 Future Research 81
Appendix A Determination of the Error Covariance of the Riccati Equation and Covariance of the Lyapunov Equation 87
Publication List 91
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