第5章小型整体径向传输线的实验研究 5.1小型整体径向传输线的实验装置设计 5.1.1单路高电压纳秒矩形波脉冲发生器 5.1.2电阻分压器 5.1.321路分路器 5.1.4整体径向传输线及其负载 5.2实验结果与讨论 5.2.1正常情形 5.2.2不同数目输入端口情形 5.2.3故障情形 5.3本章小结第6章结论参考文献在学期间发表的学术论文致谢Contents用于拍瓦级脉冲驱动源的整体径向传输线的研究 Contents Chapter 1Introduction 1.1Background 1.2Review of Evaluation Methods of Intelligent Driving Systems 1.2.1Brief Introduction of Relevant Evaluation Methods 1.2.2Classification Analysis and Comparison 1.3Research Status of Intelligent Driving System Identification
1.3.1Key Parameters Estimation 1.3.2Control Logic Identification 1.4Research Status of Evaluation Index 1.4.1Evaluation Index about Intelligence 1.4.2Evaluation Index about Safety Benefit 1.5Research Topics in This Book
Chapter 2Research Framework of Safety Benefit Evaluation Methodology 2.1Design of Safety Benefit Evaluation Process 2.1.1Basic Data Source 2.1.2Monte Carlo Simulation 2.1.3Safety Benefit Calculation 2.2Involved Key Techniques
Chapter 3Intelligent Driving System Identification Method Based on Vehicle Operation Data 3.1The Goal of Intelligent Driving System Identification 3.2Key Parameters Estimation Based on Frequency Response Characteristics 3.2.1Tire Stiffness Estimation Based on Frequency Response of the Steering System 3.2.2Time Delay Coefficient Estimation Based on Frequency Response of the Driving System 3.2.3Vehicle Mass Estimation Based on Vehicle Longitudinal Frequency Response Characteristics 3.2.4Summary of This Section 3.3Control Logic Identification Based on Machine Learning 3.3.1Intrinsic Nature of Control Logic Identification 3.3.2Control Logic Identification Based on Neural Network 3.4Summary of This Chapter
Chapter 4Occupant Injury Risk Estimation Based on Accident Data 4.1Research Scheme of Occupant Injury Risk Estimation 4.2Feasibility Verification of Vehicle Deformation Depth as Occupant Injury Evaluation Index 4.2.1Verification Based on GIDAS Data 4.2.2Verification Based on NASSCDS Data 4.3Occupant Injury Risk Estimation Based on Vehicle Deformation Depth 4.3.1Injury Risk Model Based on Vehicle Deformation Depth 4.3.2Vehicle Deformation Depth Estimation Based on Crash Energy 4.3.3Occupant Injury Risk Calculation Using Crash Simulation Software 4.4Summary of This Chapter
Chapter 5Safety Benefit Evaluation Methodology of Intelligent Driving Systems Based on Multisource Data Mining 5.1Overall Requirements for Safety Benefit Evaluation Methods 5.2Framework of Safety Benefit Evaluation Method Based on MultiSource Data Mining 5.3Key Techniques of Building Traffic Model 5.3.1Random Leading Vehicle Model 5.3.2Random Following Vehicle Model 5.3.3Subject Vehicle Model 5.4Key Techniques of Simulation Process 5.4.1CarSimSimulink Simulation Module 5.4.2PC CrashRateEFFECT Simulation Module 5.5Key Techniques of Injury Risk Estimation Process 5.5.1Calculation Method of Average Occupant Risk Per Mileage 5.5.2Deformation Length Estimation Based on Vehicle Collision Position Coordinates 5.6Summary of This Chapter
Chapter 6Verification and Application of the Proposed Methods 6.1Verification of Intelligent Driving System Identification Methods 6.1.1Verification of Key Parameters Estimation Methods
6.1.2Verification of the Control Logic Identification Method 6.2Verification of the Occupant Injury Risk Estimation Method
6.2.1Regression Relation Between Injury Risk and ΔV
6.2.2Comparison of the Occupant Injury Risk Estimation Methods with Deformation Depth and ΔV 6.3Application of the Proposed Safety Benefit Evaluation Methodology 6.3.1Safety Benefit Evaluation Using Accident Reconstruction Database 6.3.2Safety Benefit Evaluation Based on Random Traffic Scenarios 6.4Summary of This Chapter
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