Human Factors in Intelligent Vehicles:
Human Factors in Intelligent Vehiclesaddresses issues related to theanalysis of human factors in the design and evaluation of intelligent vehiclesfor a wide spectrum of applications and over different dimensions. Thecontributors cover autonomous vehicles as well as the frameworks for analyzingautoma...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Aalborg
River Publishers
2020
|
| Schriftenreihe: | River Publishers Series in Transport Technology Ser
|
| Schlagworte: | |
| Online-Zugang: | HWR01 |
| Zusammenfassung: | Human Factors in Intelligent Vehiclesaddresses issues related to theanalysis of human factors in the design and evaluation of intelligent vehiclesfor a wide spectrum of applications and over different dimensions. Thecontributors cover autonomous vehicles as well as the frameworks for analyzingautomation, modelling and methods for road users' interaction such asintelligent user interfaces, including brain-computer interfaces and simulationand analysis tools related to human factors |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (176 Seiten) |
| ISBN: | 9788770222037 |
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| 505 | 8 | |a Front Cover -- Human Factors in Intelligent Vehicles -- Contents -- Preface -- List of Contributors -- List of Figures -- List of Tables -- List of Abbreviations -- 01 Continuous Game Theory Pedestrian Modelling Method for Autonomous Vehicles -- 1.1 Introduction -- 1.2 Related Work -- 1.2.1 Pedestrian Crossing Behaviour -- 1.2.2 Game Theory -- 1.2.3 Pedestrian Tracking -- 1.3 Methods -- 1.3.1 Human Experiment -- 1.3.2 Pedestrian Detection and Tracking -- 1.3.3 Sequential Chicken Model -- 1.3.4 Gaussian Process Parameter Posterior Analysis -- 1.4 Results -- 1.5 Discussion -- Acknowlegdment -- References -- 02 The Interface Challenge for Partially Automated Vehicles: How Driver Characteristics Affect Information Usage Over Time -- 2.1 Introduction -- 2.2 Method -- 2.2.1 Study Design -- 2.2.2 Participants -- 2.2.3 Interface Design -- 2.2.4 Driving Scenario -- 2.2.5 Procedure -- 2.2.6 Data Analysis -- 2.2.6.1 Trust (Parts 1 and 2) -- 2.2.6.2 DBQ (Part 1 only) -- 2.2.6.3 DALI (Part 2 only) -- 2.3 Results -- 2.3.1 Trust Results (Parts 1 and 2) -- 2.3.2 DBQ Results (Part 1 only) -- 2.3.3 DALI Results (Part 2 only) -- 2.3.4 Fixations -- 2.3.4.1 Fixations and Trust (Parts 1 and 2) -- 2.3.4.2 Fixations and DBQ (Part 1 only) -- 2.3.4.3 Fixations and DALI (Part 2 only) -- 2.3.5 Between trust, DBQ and DALI -- 2.3.5.1 Trust and DBQ (Part 1 only) -- 2.3.5.2 Trust and DALI (Part 2 only) -- 2.4 Discussion -- 2.4.1 Fixations -- 2.4.1.1 Fixations and Trust (Parts 1 and 2) -- 2.4.1.2 Fixations and DBQ (Part 1 only) -- 2.4.2 Fixations and DALI (Part 2 only) -- 2.4.3 Between Trust, DBQ and DALI -- 2.4.3.1 Trust and DBQ (Part 1 only) -- 2.4.3.2 Trust and DALI (Part 2 only) -- 2.5 Conclusion -- References -- 03 A CNN Approach for Bidirectional Brainwave Controller for Intelligent Vehicles -- 3.1 Introduction -- 3.1.1 Human Brain -- 3.1.2 Brainwaves Features | |
| 505 | 8 | |a 3.1.3 BCI Research -- 3.2 Setup Overview -- 3.2.1 Brainwave Sensor -- 3.2.2 Vehicle Platform -- 3.3 Methodology -- 3.3.1 Data Reading -- 3.3.2 Data Filtering -- 3.3.3 Input Processing -- 3.3.4 NN Classifier -- 3.3.5 CNN Classifier -- 3.3.5.1 MindNet_1 -- 3.3.5.2 MindNet_2 -- 3.4 Experimental Works and Results -- 3.4.1 General Classifier -- 3.4.2 Individual Classifier -- 3.4.3 Computational Time -- 3.5 Conclusion and Future Work -- References -- 04 A-RCRAFT Framework for Analysing Automation: Application to SAE J3016 Levels of Driving Automation -- 4.1 Introduction -- 4.2 A Framework for Automation Analysis: A-RCRAFT -- 4.2.1 Allocation of Functions and Tasks -- 4.2.2 Allocation of Resources -- 4.2.3 Allocation of Control Transitions -- 4.2.4 Allocation of Responsibility -- 4.2.5 Allocation of Authority -- 4.3 Qualitative Analysis of SAE J3016 Levels of Driving Automation with A-RCRAFT -- 4.3.1 Scope of the SAE J3016 for the Human Tasks and System Functions -- 4.3.2 Decomposition of Levels of Driving Automation Accordingto A-RCRAFT -- 4.3.3 Results of the Analysis and Benefits from Using A-RCRAFT -- 4.4 Conclusion -- References -- 05 Autonomous Vehicles: Vulnerable Road User Response to Visual Information Using an Analysis Framework for Shared Spaces -- 5.1 Introduction -- 5.2 Field Test Description -- 5.3 Analyzing Algorithm -- 5.3.1 Pedestrian Detection and Pose Estimation -- 5.3.2 Distance Estimation via Stereo Cameras -- 5.3.3 Pedestrian tracking with DeepSort -- 5.3.4 Face Detection -- 5.3.5 Velocity -- 5.3.6 Classification -- 5.3.7 Behavior Segmentation -- 5.4 Data Analysis -- 5.5 Results -- 5.5.1 Algorithm Result -- 5.5.2 Field Tests Results -- 5.6 Conclusion, Discussion, and Future Work -- Acknowledgment -- References -- 06 Intelligent Vehicles and Older Drivers -- 6.1 Introduction -- 6.2 Age-related Limitations in Driving | |
| 505 | 8 | |a 6.2.1 Vision and Audition -- 6.2.2 Cognitive Function -- 6.2.3 Physical Function -- 6.3 How Can Intelligent Vehicles Help Older Drivers? -- 6.4 Intelligent Vehicles and Older Driver -- 6.4.1 Research Methods -- 6.4.2 Age Differences in the Acceptance of Assistive Technologies -- 6.4.3 Age Differences in Effectiveness of FCW -- 6.4.4 Age Differences in Effectiveness of LDW -- 6.5 HMI Design for Older Drivers -- 6.5.1 Visual HMI Design -- 6.5.2 Audible HMI Design -- 6.5.3 Multiple-task Design -- 6.6 Conclusions -- References -- 07 Integration Model of Multi-Agent Architectures for Data Fusion-Based Active Driving System -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Deployment Architecture -- 7.4 Materials and Methods -- 7.4.1 Materials -- 7.4.2 Deployment Details -- 7.4.3 Driving Trail Designing -- 7.5 Results -- 7.6 Discussion -- Acknowledgment -- References -- Index -- About the Editors -- Back Cover | |
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| contents | Front Cover -- Human Factors in Intelligent Vehicles -- Contents -- Preface -- List of Contributors -- List of Figures -- List of Tables -- List of Abbreviations -- 01 Continuous Game Theory Pedestrian Modelling Method for Autonomous Vehicles -- 1.1 Introduction -- 1.2 Related Work -- 1.2.1 Pedestrian Crossing Behaviour -- 1.2.2 Game Theory -- 1.2.3 Pedestrian Tracking -- 1.3 Methods -- 1.3.1 Human Experiment -- 1.3.2 Pedestrian Detection and Tracking -- 1.3.3 Sequential Chicken Model -- 1.3.4 Gaussian Process Parameter Posterior Analysis -- 1.4 Results -- 1.5 Discussion -- Acknowlegdment -- References -- 02 The Interface Challenge for Partially Automated Vehicles: How Driver Characteristics Affect Information Usage Over Time -- 2.1 Introduction -- 2.2 Method -- 2.2.1 Study Design -- 2.2.2 Participants -- 2.2.3 Interface Design -- 2.2.4 Driving Scenario -- 2.2.5 Procedure -- 2.2.6 Data Analysis -- 2.2.6.1 Trust (Parts 1 and 2) -- 2.2.6.2 DBQ (Part 1 only) -- 2.2.6.3 DALI (Part 2 only) -- 2.3 Results -- 2.3.1 Trust Results (Parts 1 and 2) -- 2.3.2 DBQ Results (Part 1 only) -- 2.3.3 DALI Results (Part 2 only) -- 2.3.4 Fixations -- 2.3.4.1 Fixations and Trust (Parts 1 and 2) -- 2.3.4.2 Fixations and DBQ (Part 1 only) -- 2.3.4.3 Fixations and DALI (Part 2 only) -- 2.3.5 Between trust, DBQ and DALI -- 2.3.5.1 Trust and DBQ (Part 1 only) -- 2.3.5.2 Trust and DALI (Part 2 only) -- 2.4 Discussion -- 2.4.1 Fixations -- 2.4.1.1 Fixations and Trust (Parts 1 and 2) -- 2.4.1.2 Fixations and DBQ (Part 1 only) -- 2.4.2 Fixations and DALI (Part 2 only) -- 2.4.3 Between Trust, DBQ and DALI -- 2.4.3.1 Trust and DBQ (Part 1 only) -- 2.4.3.2 Trust and DALI (Part 2 only) -- 2.5 Conclusion -- References -- 03 A CNN Approach for Bidirectional Brainwave Controller for Intelligent Vehicles -- 3.1 Introduction -- 3.1.1 Human Brain -- 3.1.2 Brainwaves Features 3.1.3 BCI Research -- 3.2 Setup Overview -- 3.2.1 Brainwave Sensor -- 3.2.2 Vehicle Platform -- 3.3 Methodology -- 3.3.1 Data Reading -- 3.3.2 Data Filtering -- 3.3.3 Input Processing -- 3.3.4 NN Classifier -- 3.3.5 CNN Classifier -- 3.3.5.1 MindNet_1 -- 3.3.5.2 MindNet_2 -- 3.4 Experimental Works and Results -- 3.4.1 General Classifier -- 3.4.2 Individual Classifier -- 3.4.3 Computational Time -- 3.5 Conclusion and Future Work -- References -- 04 A-RCRAFT Framework for Analysing Automation: Application to SAE J3016 Levels of Driving Automation -- 4.1 Introduction -- 4.2 A Framework for Automation Analysis: A-RCRAFT -- 4.2.1 Allocation of Functions and Tasks -- 4.2.2 Allocation of Resources -- 4.2.3 Allocation of Control Transitions -- 4.2.4 Allocation of Responsibility -- 4.2.5 Allocation of Authority -- 4.3 Qualitative Analysis of SAE J3016 Levels of Driving Automation with A-RCRAFT -- 4.3.1 Scope of the SAE J3016 for the Human Tasks and System Functions -- 4.3.2 Decomposition of Levels of Driving Automation Accordingto A-RCRAFT -- 4.3.3 Results of the Analysis and Benefits from Using A-RCRAFT -- 4.4 Conclusion -- References -- 05 Autonomous Vehicles: Vulnerable Road User Response to Visual Information Using an Analysis Framework for Shared Spaces -- 5.1 Introduction -- 5.2 Field Test Description -- 5.3 Analyzing Algorithm -- 5.3.1 Pedestrian Detection and Pose Estimation -- 5.3.2 Distance Estimation via Stereo Cameras -- 5.3.3 Pedestrian tracking with DeepSort -- 5.3.4 Face Detection -- 5.3.5 Velocity -- 5.3.6 Classification -- 5.3.7 Behavior Segmentation -- 5.4 Data Analysis -- 5.5 Results -- 5.5.1 Algorithm Result -- 5.5.2 Field Tests Results -- 5.6 Conclusion, Discussion, and Future Work -- Acknowledgment -- References -- 06 Intelligent Vehicles and Older Drivers -- 6.1 Introduction -- 6.2 Age-related Limitations in Driving 6.2.1 Vision and Audition -- 6.2.2 Cognitive Function -- 6.2.3 Physical Function -- 6.3 How Can Intelligent Vehicles Help Older Drivers? -- 6.4 Intelligent Vehicles and Older Driver -- 6.4.1 Research Methods -- 6.4.2 Age Differences in the Acceptance of Assistive Technologies -- 6.4.3 Age Differences in Effectiveness of FCW -- 6.4.4 Age Differences in Effectiveness of LDW -- 6.5 HMI Design for Older Drivers -- 6.5.1 Visual HMI Design -- 6.5.2 Audible HMI Design -- 6.5.3 Multiple-task Design -- 6.6 Conclusions -- References -- 07 Integration Model of Multi-Agent Architectures for Data Fusion-Based Active Driving System -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Deployment Architecture -- 7.4 Materials and Methods -- 7.4.1 Materials -- 7.4.2 Deployment Details -- 7.4.3 Driving Trail Designing -- 7.5 Results -- 7.6 Discussion -- Acknowledgment -- References -- Index -- About the Editors -- Back Cover |
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| id | DE-604.BV048220706 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T19:50:31Z |
| indexdate | 2024-07-10T09:32:24Z |
| institution | BVB |
| isbn | 9788770222037 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033601450 |
| oclc_num | 1319631986 |
| open_access_boolean | |
| owner | DE-2070s |
| owner_facet | DE-2070s |
| physical | 1 Online-Ressource (176 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE HWR_PDA_PQE |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | River Publishers |
| record_format | marc |
| series2 | River Publishers Series in Transport Technology Ser |
| spelling | Olaverri-Monreal, Cristina Verfasser aut Human Factors in Intelligent Vehicles Aalborg River Publishers 2020 ©2020 1 Online-Ressource (176 Seiten) txt rdacontent c rdamedia cr rdacarrier River Publishers Series in Transport Technology Ser Description based on publisher supplied metadata and other sources Front Cover -- Human Factors in Intelligent Vehicles -- Contents -- Preface -- List of Contributors -- List of Figures -- List of Tables -- List of Abbreviations -- 01 Continuous Game Theory Pedestrian Modelling Method for Autonomous Vehicles -- 1.1 Introduction -- 1.2 Related Work -- 1.2.1 Pedestrian Crossing Behaviour -- 1.2.2 Game Theory -- 1.2.3 Pedestrian Tracking -- 1.3 Methods -- 1.3.1 Human Experiment -- 1.3.2 Pedestrian Detection and Tracking -- 1.3.3 Sequential Chicken Model -- 1.3.4 Gaussian Process Parameter Posterior Analysis -- 1.4 Results -- 1.5 Discussion -- Acknowlegdment -- References -- 02 The Interface Challenge for Partially Automated Vehicles: How Driver Characteristics Affect Information Usage Over Time -- 2.1 Introduction -- 2.2 Method -- 2.2.1 Study Design -- 2.2.2 Participants -- 2.2.3 Interface Design -- 2.2.4 Driving Scenario -- 2.2.5 Procedure -- 2.2.6 Data Analysis -- 2.2.6.1 Trust (Parts 1 and 2) -- 2.2.6.2 DBQ (Part 1 only) -- 2.2.6.3 DALI (Part 2 only) -- 2.3 Results -- 2.3.1 Trust Results (Parts 1 and 2) -- 2.3.2 DBQ Results (Part 1 only) -- 2.3.3 DALI Results (Part 2 only) -- 2.3.4 Fixations -- 2.3.4.1 Fixations and Trust (Parts 1 and 2) -- 2.3.4.2 Fixations and DBQ (Part 1 only) -- 2.3.4.3 Fixations and DALI (Part 2 only) -- 2.3.5 Between trust, DBQ and DALI -- 2.3.5.1 Trust and DBQ (Part 1 only) -- 2.3.5.2 Trust and DALI (Part 2 only) -- 2.4 Discussion -- 2.4.1 Fixations -- 2.4.1.1 Fixations and Trust (Parts 1 and 2) -- 2.4.1.2 Fixations and DBQ (Part 1 only) -- 2.4.2 Fixations and DALI (Part 2 only) -- 2.4.3 Between Trust, DBQ and DALI -- 2.4.3.1 Trust and DBQ (Part 1 only) -- 2.4.3.2 Trust and DALI (Part 2 only) -- 2.5 Conclusion -- References -- 03 A CNN Approach for Bidirectional Brainwave Controller for Intelligent Vehicles -- 3.1 Introduction -- 3.1.1 Human Brain -- 3.1.2 Brainwaves Features 3.1.3 BCI Research -- 3.2 Setup Overview -- 3.2.1 Brainwave Sensor -- 3.2.2 Vehicle Platform -- 3.3 Methodology -- 3.3.1 Data Reading -- 3.3.2 Data Filtering -- 3.3.3 Input Processing -- 3.3.4 NN Classifier -- 3.3.5 CNN Classifier -- 3.3.5.1 MindNet_1 -- 3.3.5.2 MindNet_2 -- 3.4 Experimental Works and Results -- 3.4.1 General Classifier -- 3.4.2 Individual Classifier -- 3.4.3 Computational Time -- 3.5 Conclusion and Future Work -- References -- 04 A-RCRAFT Framework for Analysing Automation: Application to SAE J3016 Levels of Driving Automation -- 4.1 Introduction -- 4.2 A Framework for Automation Analysis: A-RCRAFT -- 4.2.1 Allocation of Functions and Tasks -- 4.2.2 Allocation of Resources -- 4.2.3 Allocation of Control Transitions -- 4.2.4 Allocation of Responsibility -- 4.2.5 Allocation of Authority -- 4.3 Qualitative Analysis of SAE J3016 Levels of Driving Automation with A-RCRAFT -- 4.3.1 Scope of the SAE J3016 for the Human Tasks and System Functions -- 4.3.2 Decomposition of Levels of Driving Automation Accordingto A-RCRAFT -- 4.3.3 Results of the Analysis and Benefits from Using A-RCRAFT -- 4.4 Conclusion -- References -- 05 Autonomous Vehicles: Vulnerable Road User Response to Visual Information Using an Analysis Framework for Shared Spaces -- 5.1 Introduction -- 5.2 Field Test Description -- 5.3 Analyzing Algorithm -- 5.3.1 Pedestrian Detection and Pose Estimation -- 5.3.2 Distance Estimation via Stereo Cameras -- 5.3.3 Pedestrian tracking with DeepSort -- 5.3.4 Face Detection -- 5.3.5 Velocity -- 5.3.6 Classification -- 5.3.7 Behavior Segmentation -- 5.4 Data Analysis -- 5.5 Results -- 5.5.1 Algorithm Result -- 5.5.2 Field Tests Results -- 5.6 Conclusion, Discussion, and Future Work -- Acknowledgment -- References -- 06 Intelligent Vehicles and Older Drivers -- 6.1 Introduction -- 6.2 Age-related Limitations in Driving 6.2.1 Vision and Audition -- 6.2.2 Cognitive Function -- 6.2.3 Physical Function -- 6.3 How Can Intelligent Vehicles Help Older Drivers? -- 6.4 Intelligent Vehicles and Older Driver -- 6.4.1 Research Methods -- 6.4.2 Age Differences in the Acceptance of Assistive Technologies -- 6.4.3 Age Differences in Effectiveness of FCW -- 6.4.4 Age Differences in Effectiveness of LDW -- 6.5 HMI Design for Older Drivers -- 6.5.1 Visual HMI Design -- 6.5.2 Audible HMI Design -- 6.5.3 Multiple-task Design -- 6.6 Conclusions -- References -- 07 Integration Model of Multi-Agent Architectures for Data Fusion-Based Active Driving System -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Deployment Architecture -- 7.4 Materials and Methods -- 7.4.1 Materials -- 7.4.2 Deployment Details -- 7.4.3 Driving Trail Designing -- 7.5 Results -- 7.6 Discussion -- Acknowledgment -- References -- Index -- About the Editors -- Back Cover Human Factors in Intelligent Vehiclesaddresses issues related to theanalysis of human factors in the design and evaluation of intelligent vehiclesfor a wide spectrum of applications and over different dimensions. Thecontributors cover autonomous vehicles as well as the frameworks for analyzingautomation, modelling and methods for road users' interaction such asintelligent user interfaces, including brain-computer interfaces and simulationand analysis tools related to human factors Autonomes Fahrzeug (DE-588)7714938-5 gnd rswk-swf Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd rswk-swf Autonomes Fahrzeug (DE-588)7714938-5 s Mensch-Maschine-Kommunikation (DE-588)4125909-9 s DE-604 García-Fernández, Fernando Sonstige oth Rossetti, Rosaldo J. F. Sonstige oth Erscheint auch als Druck-Ausgabe Olaverri-Monreal, Cristina Human Factors in Intelligent Vehicles Aalborg : River Publishers,c2020 9788770222044 |
| spellingShingle | Olaverri-Monreal, Cristina Human Factors in Intelligent Vehicles Front Cover -- Human Factors in Intelligent Vehicles -- Contents -- Preface -- List of Contributors -- List of Figures -- List of Tables -- List of Abbreviations -- 01 Continuous Game Theory Pedestrian Modelling Method for Autonomous Vehicles -- 1.1 Introduction -- 1.2 Related Work -- 1.2.1 Pedestrian Crossing Behaviour -- 1.2.2 Game Theory -- 1.2.3 Pedestrian Tracking -- 1.3 Methods -- 1.3.1 Human Experiment -- 1.3.2 Pedestrian Detection and Tracking -- 1.3.3 Sequential Chicken Model -- 1.3.4 Gaussian Process Parameter Posterior Analysis -- 1.4 Results -- 1.5 Discussion -- Acknowlegdment -- References -- 02 The Interface Challenge for Partially Automated Vehicles: How Driver Characteristics Affect Information Usage Over Time -- 2.1 Introduction -- 2.2 Method -- 2.2.1 Study Design -- 2.2.2 Participants -- 2.2.3 Interface Design -- 2.2.4 Driving Scenario -- 2.2.5 Procedure -- 2.2.6 Data Analysis -- 2.2.6.1 Trust (Parts 1 and 2) -- 2.2.6.2 DBQ (Part 1 only) -- 2.2.6.3 DALI (Part 2 only) -- 2.3 Results -- 2.3.1 Trust Results (Parts 1 and 2) -- 2.3.2 DBQ Results (Part 1 only) -- 2.3.3 DALI Results (Part 2 only) -- 2.3.4 Fixations -- 2.3.4.1 Fixations and Trust (Parts 1 and 2) -- 2.3.4.2 Fixations and DBQ (Part 1 only) -- 2.3.4.3 Fixations and DALI (Part 2 only) -- 2.3.5 Between trust, DBQ and DALI -- 2.3.5.1 Trust and DBQ (Part 1 only) -- 2.3.5.2 Trust and DALI (Part 2 only) -- 2.4 Discussion -- 2.4.1 Fixations -- 2.4.1.1 Fixations and Trust (Parts 1 and 2) -- 2.4.1.2 Fixations and DBQ (Part 1 only) -- 2.4.2 Fixations and DALI (Part 2 only) -- 2.4.3 Between Trust, DBQ and DALI -- 2.4.3.1 Trust and DBQ (Part 1 only) -- 2.4.3.2 Trust and DALI (Part 2 only) -- 2.5 Conclusion -- References -- 03 A CNN Approach for Bidirectional Brainwave Controller for Intelligent Vehicles -- 3.1 Introduction -- 3.1.1 Human Brain -- 3.1.2 Brainwaves Features 3.1.3 BCI Research -- 3.2 Setup Overview -- 3.2.1 Brainwave Sensor -- 3.2.2 Vehicle Platform -- 3.3 Methodology -- 3.3.1 Data Reading -- 3.3.2 Data Filtering -- 3.3.3 Input Processing -- 3.3.4 NN Classifier -- 3.3.5 CNN Classifier -- 3.3.5.1 MindNet_1 -- 3.3.5.2 MindNet_2 -- 3.4 Experimental Works and Results -- 3.4.1 General Classifier -- 3.4.2 Individual Classifier -- 3.4.3 Computational Time -- 3.5 Conclusion and Future Work -- References -- 04 A-RCRAFT Framework for Analysing Automation: Application to SAE J3016 Levels of Driving Automation -- 4.1 Introduction -- 4.2 A Framework for Automation Analysis: A-RCRAFT -- 4.2.1 Allocation of Functions and Tasks -- 4.2.2 Allocation of Resources -- 4.2.3 Allocation of Control Transitions -- 4.2.4 Allocation of Responsibility -- 4.2.5 Allocation of Authority -- 4.3 Qualitative Analysis of SAE J3016 Levels of Driving Automation with A-RCRAFT -- 4.3.1 Scope of the SAE J3016 for the Human Tasks and System Functions -- 4.3.2 Decomposition of Levels of Driving Automation Accordingto A-RCRAFT -- 4.3.3 Results of the Analysis and Benefits from Using A-RCRAFT -- 4.4 Conclusion -- References -- 05 Autonomous Vehicles: Vulnerable Road User Response to Visual Information Using an Analysis Framework for Shared Spaces -- 5.1 Introduction -- 5.2 Field Test Description -- 5.3 Analyzing Algorithm -- 5.3.1 Pedestrian Detection and Pose Estimation -- 5.3.2 Distance Estimation via Stereo Cameras -- 5.3.3 Pedestrian tracking with DeepSort -- 5.3.4 Face Detection -- 5.3.5 Velocity -- 5.3.6 Classification -- 5.3.7 Behavior Segmentation -- 5.4 Data Analysis -- 5.5 Results -- 5.5.1 Algorithm Result -- 5.5.2 Field Tests Results -- 5.6 Conclusion, Discussion, and Future Work -- Acknowledgment -- References -- 06 Intelligent Vehicles and Older Drivers -- 6.1 Introduction -- 6.2 Age-related Limitations in Driving 6.2.1 Vision and Audition -- 6.2.2 Cognitive Function -- 6.2.3 Physical Function -- 6.3 How Can Intelligent Vehicles Help Older Drivers? -- 6.4 Intelligent Vehicles and Older Driver -- 6.4.1 Research Methods -- 6.4.2 Age Differences in the Acceptance of Assistive Technologies -- 6.4.3 Age Differences in Effectiveness of FCW -- 6.4.4 Age Differences in Effectiveness of LDW -- 6.5 HMI Design for Older Drivers -- 6.5.1 Visual HMI Design -- 6.5.2 Audible HMI Design -- 6.5.3 Multiple-task Design -- 6.6 Conclusions -- References -- 07 Integration Model of Multi-Agent Architectures for Data Fusion-Based Active Driving System -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Deployment Architecture -- 7.4 Materials and Methods -- 7.4.1 Materials -- 7.4.2 Deployment Details -- 7.4.3 Driving Trail Designing -- 7.5 Results -- 7.6 Discussion -- Acknowledgment -- References -- Index -- About the Editors -- Back Cover Autonomes Fahrzeug (DE-588)7714938-5 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd |
| subject_GND | (DE-588)7714938-5 (DE-588)4125909-9 |
| title | Human Factors in Intelligent Vehicles |
| title_auth | Human Factors in Intelligent Vehicles |
| title_exact_search | Human Factors in Intelligent Vehicles |
| title_exact_search_txtP | Human Factors in Intelligent Vehicles |
| title_full | Human Factors in Intelligent Vehicles |
| title_fullStr | Human Factors in Intelligent Vehicles |
| title_full_unstemmed | Human Factors in Intelligent Vehicles |
| title_short | Human Factors in Intelligent Vehicles |
| title_sort | human factors in intelligent vehicles |
| topic | Autonomes Fahrzeug (DE-588)7714938-5 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd |
| topic_facet | Autonomes Fahrzeug Mensch-Maschine-Kommunikation |
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