From AI to autonomous and connected vehicles advanced driver-assistance systems (ADAS)
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London, UK
ISTE
2021
Hoboken, NJ Wiley |
| Schriftenreihe: | Science, society and new technologies series. Digital sciences set
Volume 2 |
| Online-Zugang: | FHI01 TUM01 URL des Erstveröffentlichers |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV048228609 | ||
| 003 | DE-604 | ||
| 005 | 20240229 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 220517s2021 |||| o||u| ||||||eng d | ||
| 020 | |a 9781119855491 |9 978-1-119-85549-1 | ||
| 020 | |a 9781119855507 |9 9781119855507 | ||
| 020 | |a 9781119855484 |9 9781119855484 | ||
| 035 | |a (ZDB-30-PQE)EBC6712451 | ||
| 035 | |a (ZDB-30-PAD)EBC6712451 | ||
| 035 | |a (ZDB-89-EBL)EBL6712451 | ||
| 035 | |a (OCoLC)1266909081 | ||
| 035 | |a (DE-599)BVBBV048228609 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-91 |a DE-573 | ||
| 082 | 0 | |a 629.2046 | |
| 084 | |a VER 080 |2 stub | ||
| 084 | |a DAT 700 |2 stub | ||
| 245 | 1 | 0 | |a From AI to autonomous and connected vehicles |b advanced driver-assistance systems (ADAS) |c edited by Abdelaziz Bensrhair, Thierry Bapin |
| 264 | 1 | |a London, UK |b ISTE |c 2021 | |
| 264 | 1 | |a Hoboken, NJ |b Wiley | |
| 264 | 4 | |c © 2021 | |
| 300 | |a 1 Online-Ressource (xxiv, 251 Seiten) |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 1 | |a Science, society and new technologies series. Digital sciences set |v Volume 2 | |
| 490 | 0 | |a Mechanical engineering and solid mechanics | |
| 500 | |a Description based on publisher supplied metadata and other sources | ||
| 505 | 8 | |a Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Foreword 1 -- Foreword 2 -- Foreword 3 -- Preface -- 1 Artificial Intelligence for Vehicles -- 1.1. What is AI? -- 1.2. The main methods of AI -- 1.2.1. Deep Learning -- 1.2.2. Machine Learning -- 1.2.3. Clustering -- 1.2.4. Reinforcement learning -- 1.2.5. Case-based reasoning -- 1.2.6. Logical reasoning -- 1.2.7. Multi-agent systems -- 1.2.8. PAC learning -- 1.3. Modern AI challenges for the industry -- 1.3.1. Explainability: XAI (eXplainable Artificial Intelligence) -- 1.3.2. The design of so-called "hybrid" AI systems -- 1.4. What is an "intelligent" vehicle? -- 1.4.1. ADAS -- 1.4.2. The autonomous vehicle -- 1.4.2. The construction of the intelligent vehicle's basic building blocks employing AI methods -- 1.5. References -- 2 Conventional Vision or Not: A Selection of Low-level Algorithms -- 2.1. Introduction -- 2.2. Vision sensors -- 2.2.1. Conventional cameras -- 2.2.2. Emerging sensors -- 2.3. Vision algorithms -- 2.3.1. Choosing the type of information to be retrieved from the images -- 2.3.2. Estimation of ego-movement and localization -- 2.3.3. Detection of the navigable space by a dense approach -- 2.3.4. From the detection of 3D plans to visual odometry -- 2.3.5. Detection of obstacles through the compensation of ego-movement -- 2.3.6. Visual odometry -- 2.4. Conclusion -- 2.5. References -- 3 Automated Driving, a Question of Trajectory Planning -- 3.1. Definition of planning -- 3.2. Trajectory planning: general characteristics -- 3.2.1. Variables -- 3.2.2. Constraints -- 3.2.3. Cost functions -- 3.2.4. Planning methodology -- 3.2.5. Co-pilot respecting legal traffic rules -- 3.2.6. Trajectory prediction for "ghost" objects and vehicles -- 3.2.7. Trajectory evaluation -- 3.2.8. Results on real vehicles and on simulators -- 3.3. Multi-objective trajectory planning | |
| 505 | 8 | |a 3.3.1. Linear scalarization -- 3.3.2. Nonlinear scalarization -- 3.3.3. Ideal methods -- 3.3.4. Summary of multi-objective planning methods -- 3.3.5. High level information -- 3.4. Conclusion on multi-agent planning for a fleet of vehicles: the future of planning -- 3.5. References -- 4 From Virtual to Real, How to Prototype, Test, Evaluate and Validate ADAS for the Automated and Connected Vehicle? -- 4.1. Context and goals -- 4.2. Generic dynamic and distributed architecture -- 4.2.1. Introduction -- 4.2.2. An interoperable platform -- 4.3. Environment and climatic conditions -- 4.3.1. Introduction -- 4.3.2. Environmental modeling: lights, shadows, materials and textures -- 4.3.3. Degraded, adverse and climatic conditions -- 4.3.4. Visibility layers and ground truths -- 4.4. Modeling of perception sensors -- 4.4.1. Typology of sensor technologies -- 4.4.2. From a functional model to a physical model -- 4.4.3. Optical sensors -- 4.4.4. LIght Detection And Ranging (LIDAR) -- 4.4.5. RAdio Detection And Ranging (RADAR) -- 4.4.6. Global Navigation Satellite System (GNSS) -- 4.5. Connectivity and means of communication -- 4.5.1. State of the art -- 4.5.2. Statistical model of the propagation channel -- 4.5.3. Multi-platform physico-realistic model -- 4.6. Some relevant use cases -- 4.6.1. Graphic resources -- 4.6.2. Communication and overall risk -- 4.6.3. Automated parking maneuver -- 4.6.4. Co-pilot and automated driving -- 4.6.5. Eco-mobility and eco-responsible driving profile -- 4.7. Conclusion and perspectives -- 4.8. References -- 5 Standards for Cooperative Intelligent Transport Systems (C-ITS) -- 5.1. Context and goals -- 5.1.1. Intelligent transport systems (ITS) -- 5.1.2. The connected and cooperative vehicle -- 5.1.3. Silos communication systems -- 5.1.4. Cooperative Intelligent Transport Systems (C-ITS) | |
| 505 | 8 | |a 5.1.5. Diversity of Cooperative ITS services -- 5.1.6. Standardization bodies -- 5.1.7. Genesis of the "Cooperative ITS" standards -- 5.2. "ITS station" architecture -- 5.2.1. General description -- 5.2.2. ITS station communication units -- 5.2.3. Types of ITS stations -- 5.3. Features of the ITS station architecture -- 5.3.1. Combination of communication technologies -- 5.3.2. Centralized communications -- 5.3.3. Localized communications (V2X) -- 5.3.4. Hybrid communications -- 5.3.5. Extensive communications -- 5.3.6. Communications management -- 5.3.7. Messaging -- 5.3.8. Data organization and identification -- 5.3.9. Secure communications and access to data -- 5.3.10. Evolution of standards -- 5.4. Features of the ITS station architecture -- 5.5. Deployment of Cooperative ITS services -- 5.6. References -- 6 The Integration of Pedestrian Orientation for the Benefit of ADAS: A Moroccan Case Study -- 6.1. Introduction -- 6.2. Advanced Driver Assistance System (ADAS) -- 6.3. Proposal for an applicable system to the Moroccan case -- 6.4. General conclusion -- 6.5. References -- 7 Autonomous Vehicle: What Legal Issues? -- 7.1. Introduction -- 7.2. The definition of the so-called "autonomous" vehicle -- 7.3. Legal framework and experiments -- 7.4. The notion of the "driver" -- 7.5. The notion of the "custodian" -- 7.6. What liability regime? -- 7.7. Self-driving vehicle insurance? -- 7.8. Personal data and the autonomous vehicle -- 7.9. The need for uniform regulation -- List of Authors -- Index -- Other titles from iSTE in Mechanical Engineering and Solid Mechanics -- EULA. | |
| 700 | 1 | |a Bensrhair, Abdelaziz |4 edt | |
| 700 | 1 | |a Bapin, Thierry |4 edt | |
| 776 | 0 | 8 | |i Erscheint auch als |a Bensrhair, Abdelaziz |t From AI to Autonomous and Connected Vehicles |d Newark : John Wiley & Sons, Incorporated,c2021 |n Druck-Ausgabe |z 978-1-78630-727-9 |
| 830 | 0 | |a Science, society and new technologies series. Digital sciences set |v Volume 2 |w (DE-604)BV048446103 |9 2 | |
| 856 | 4 | 0 | |u https://ieeexplore.ieee.org/book/9714893 |x Aggregator |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-30-PQE |a ZDB-35-IWT | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-033609328 | ||
| 966 | e | |u https://ieeexplore.ieee.org/book/9714893 |l FHI01 |p ZDB-35-IWT |x Verlag |3 Volltext | |
| 966 | e | |u https://ebookcentral.proquest.com/lib/munchentech/detail.action?docID=6712451 |l TUM01 |p ZDB-30-PQE |q TUM_PDA_PQE_Kauf |x Aggregator |3 Volltext | |
Datensatz im Suchindex
| DE-BY-TUM_katkey | 2647909 |
|---|---|
| DE-BY-TUM_local_url | Verlag https://ieeexplore.ieee.org/book/9714893 https://ebookcentral.proquest.com/lib/munchentech/detail.action?docID=6712451 Aggregator |
| _version_ | 1816714804301135872 |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author2 | Bensrhair, Abdelaziz Bapin, Thierry |
| author2_role | edt edt |
| author2_variant | a b ab t b tb |
| author_facet | Bensrhair, Abdelaziz Bapin, Thierry |
| building | Verbundindex |
| bvnumber | BV048228609 |
| classification_tum | VER 080 DAT 700 |
| collection | ZDB-30-PQE ZDB-35-IWT |
| contents | Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Foreword 1 -- Foreword 2 -- Foreword 3 -- Preface -- 1 Artificial Intelligence for Vehicles -- 1.1. What is AI? -- 1.2. The main methods of AI -- 1.2.1. Deep Learning -- 1.2.2. Machine Learning -- 1.2.3. Clustering -- 1.2.4. Reinforcement learning -- 1.2.5. Case-based reasoning -- 1.2.6. Logical reasoning -- 1.2.7. Multi-agent systems -- 1.2.8. PAC learning -- 1.3. Modern AI challenges for the industry -- 1.3.1. Explainability: XAI (eXplainable Artificial Intelligence) -- 1.3.2. The design of so-called "hybrid" AI systems -- 1.4. What is an "intelligent" vehicle? -- 1.4.1. ADAS -- 1.4.2. The autonomous vehicle -- 1.4.2. The construction of the intelligent vehicle's basic building blocks employing AI methods -- 1.5. References -- 2 Conventional Vision or Not: A Selection of Low-level Algorithms -- 2.1. Introduction -- 2.2. Vision sensors -- 2.2.1. Conventional cameras -- 2.2.2. Emerging sensors -- 2.3. Vision algorithms -- 2.3.1. Choosing the type of information to be retrieved from the images -- 2.3.2. Estimation of ego-movement and localization -- 2.3.3. Detection of the navigable space by a dense approach -- 2.3.4. From the detection of 3D plans to visual odometry -- 2.3.5. Detection of obstacles through the compensation of ego-movement -- 2.3.6. Visual odometry -- 2.4. Conclusion -- 2.5. References -- 3 Automated Driving, a Question of Trajectory Planning -- 3.1. Definition of planning -- 3.2. Trajectory planning: general characteristics -- 3.2.1. Variables -- 3.2.2. Constraints -- 3.2.3. Cost functions -- 3.2.4. Planning methodology -- 3.2.5. Co-pilot respecting legal traffic rules -- 3.2.6. Trajectory prediction for "ghost" objects and vehicles -- 3.2.7. Trajectory evaluation -- 3.2.8. Results on real vehicles and on simulators -- 3.3. Multi-objective trajectory planning 3.3.1. Linear scalarization -- 3.3.2. Nonlinear scalarization -- 3.3.3. Ideal methods -- 3.3.4. Summary of multi-objective planning methods -- 3.3.5. High level information -- 3.4. Conclusion on multi-agent planning for a fleet of vehicles: the future of planning -- 3.5. References -- 4 From Virtual to Real, How to Prototype, Test, Evaluate and Validate ADAS for the Automated and Connected Vehicle? -- 4.1. Context and goals -- 4.2. Generic dynamic and distributed architecture -- 4.2.1. Introduction -- 4.2.2. An interoperable platform -- 4.3. Environment and climatic conditions -- 4.3.1. Introduction -- 4.3.2. Environmental modeling: lights, shadows, materials and textures -- 4.3.3. Degraded, adverse and climatic conditions -- 4.3.4. Visibility layers and ground truths -- 4.4. Modeling of perception sensors -- 4.4.1. Typology of sensor technologies -- 4.4.2. From a functional model to a physical model -- 4.4.3. Optical sensors -- 4.4.4. LIght Detection And Ranging (LIDAR) -- 4.4.5. RAdio Detection And Ranging (RADAR) -- 4.4.6. Global Navigation Satellite System (GNSS) -- 4.5. Connectivity and means of communication -- 4.5.1. State of the art -- 4.5.2. Statistical model of the propagation channel -- 4.5.3. Multi-platform physico-realistic model -- 4.6. Some relevant use cases -- 4.6.1. Graphic resources -- 4.6.2. Communication and overall risk -- 4.6.3. Automated parking maneuver -- 4.6.4. Co-pilot and automated driving -- 4.6.5. Eco-mobility and eco-responsible driving profile -- 4.7. Conclusion and perspectives -- 4.8. References -- 5 Standards for Cooperative Intelligent Transport Systems (C-ITS) -- 5.1. Context and goals -- 5.1.1. Intelligent transport systems (ITS) -- 5.1.2. The connected and cooperative vehicle -- 5.1.3. Silos communication systems -- 5.1.4. Cooperative Intelligent Transport Systems (C-ITS) 5.1.5. Diversity of Cooperative ITS services -- 5.1.6. Standardization bodies -- 5.1.7. Genesis of the "Cooperative ITS" standards -- 5.2. "ITS station" architecture -- 5.2.1. General description -- 5.2.2. ITS station communication units -- 5.2.3. Types of ITS stations -- 5.3. Features of the ITS station architecture -- 5.3.1. Combination of communication technologies -- 5.3.2. Centralized communications -- 5.3.3. Localized communications (V2X) -- 5.3.4. Hybrid communications -- 5.3.5. Extensive communications -- 5.3.6. Communications management -- 5.3.7. Messaging -- 5.3.8. Data organization and identification -- 5.3.9. Secure communications and access to data -- 5.3.10. Evolution of standards -- 5.4. Features of the ITS station architecture -- 5.5. Deployment of Cooperative ITS services -- 5.6. References -- 6 The Integration of Pedestrian Orientation for the Benefit of ADAS: A Moroccan Case Study -- 6.1. Introduction -- 6.2. Advanced Driver Assistance System (ADAS) -- 6.3. Proposal for an applicable system to the Moroccan case -- 6.4. General conclusion -- 6.5. References -- 7 Autonomous Vehicle: What Legal Issues? -- 7.1. Introduction -- 7.2. The definition of the so-called "autonomous" vehicle -- 7.3. Legal framework and experiments -- 7.4. The notion of the "driver" -- 7.5. The notion of the "custodian" -- 7.6. What liability regime? -- 7.7. Self-driving vehicle insurance? -- 7.8. Personal data and the autonomous vehicle -- 7.9. The need for uniform regulation -- List of Authors -- Index -- Other titles from iSTE in Mechanical Engineering and Solid Mechanics -- EULA. |
| ctrlnum | (ZDB-30-PQE)EBC6712451 (ZDB-30-PAD)EBC6712451 (ZDB-89-EBL)EBL6712451 (OCoLC)1266909081 (DE-599)BVBBV048228609 |
| dewey-full | 629.2046 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
| dewey-raw | 629.2046 |
| dewey-search | 629.2046 |
| dewey-sort | 3629.2046 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Informatik Verkehrstechnik Verkehr / Transport |
| discipline_str_mv | Informatik Verkehrstechnik Verkehr / Transport |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>07529nmm a2200529zcb4500</leader><controlfield tag="001">BV048228609</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20240229 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">220517s2021 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119855491</subfield><subfield code="9">978-1-119-85549-1</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119855507</subfield><subfield code="9">9781119855507</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781119855484</subfield><subfield code="9">9781119855484</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PQE)EBC6712451</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-30-PAD)EBC6712451</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-89-EBL)EBL6712451</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1266909081</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV048228609</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-91</subfield><subfield code="a">DE-573</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">629.2046</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">VER 080</subfield><subfield code="2">stub</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">DAT 700</subfield><subfield code="2">stub</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">From AI to autonomous and connected vehicles</subfield><subfield code="b">advanced driver-assistance systems (ADAS)</subfield><subfield code="c">edited by Abdelaziz Bensrhair, Thierry Bapin</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">London, UK</subfield><subfield code="b">ISTE</subfield><subfield code="c">2021</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hoboken, NJ</subfield><subfield code="b">Wiley</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xxiv, 251 Seiten)</subfield><subfield code="b">Illustrationen, Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Science, society and new technologies series. Digital sciences set</subfield><subfield code="v">Volume 2</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Mechanical engineering and solid mechanics</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Foreword 1 -- Foreword 2 -- Foreword 3 -- Preface -- 1 Artificial Intelligence for Vehicles -- 1.1. What is AI? -- 1.2. The main methods of AI -- 1.2.1. Deep Learning -- 1.2.2. Machine Learning -- 1.2.3. Clustering -- 1.2.4. Reinforcement learning -- 1.2.5. Case-based reasoning -- 1.2.6. Logical reasoning -- 1.2.7. Multi-agent systems -- 1.2.8. PAC learning -- 1.3. Modern AI challenges for the industry -- 1.3.1. Explainability: XAI (eXplainable Artificial Intelligence) -- 1.3.2. The design of so-called "hybrid" AI systems -- 1.4. What is an "intelligent" vehicle? -- 1.4.1. ADAS -- 1.4.2. The autonomous vehicle -- 1.4.2. The construction of the intelligent vehicle's basic building blocks employing AI methods -- 1.5. References -- 2 Conventional Vision or Not: A Selection of Low-level Algorithms -- 2.1. Introduction -- 2.2. Vision sensors -- 2.2.1. Conventional cameras -- 2.2.2. Emerging sensors -- 2.3. Vision algorithms -- 2.3.1. Choosing the type of information to be retrieved from the images -- 2.3.2. Estimation of ego-movement and localization -- 2.3.3. Detection of the navigable space by a dense approach -- 2.3.4. From the detection of 3D plans to visual odometry -- 2.3.5. Detection of obstacles through the compensation of ego-movement -- 2.3.6. Visual odometry -- 2.4. Conclusion -- 2.5. References -- 3 Automated Driving, a Question of Trajectory Planning -- 3.1. Definition of planning -- 3.2. Trajectory planning: general characteristics -- 3.2.1. Variables -- 3.2.2. Constraints -- 3.2.3. Cost functions -- 3.2.4. Planning methodology -- 3.2.5. Co-pilot respecting legal traffic rules -- 3.2.6. Trajectory prediction for "ghost" objects and vehicles -- 3.2.7. Trajectory evaluation -- 3.2.8. Results on real vehicles and on simulators -- 3.3. Multi-objective trajectory planning</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">3.3.1. Linear scalarization -- 3.3.2. Nonlinear scalarization -- 3.3.3. Ideal methods -- 3.3.4. Summary of multi-objective planning methods -- 3.3.5. High level information -- 3.4. Conclusion on multi-agent planning for a fleet of vehicles: the future of planning -- 3.5. References -- 4 From Virtual to Real, How to Prototype, Test, Evaluate and Validate ADAS for the Automated and Connected Vehicle? -- 4.1. Context and goals -- 4.2. Generic dynamic and distributed architecture -- 4.2.1. Introduction -- 4.2.2. An interoperable platform -- 4.3. Environment and climatic conditions -- 4.3.1. Introduction -- 4.3.2. Environmental modeling: lights, shadows, materials and textures -- 4.3.3. Degraded, adverse and climatic conditions -- 4.3.4. Visibility layers and ground truths -- 4.4. Modeling of perception sensors -- 4.4.1. Typology of sensor technologies -- 4.4.2. From a functional model to a physical model -- 4.4.3. Optical sensors -- 4.4.4. LIght Detection And Ranging (LIDAR) -- 4.4.5. RAdio Detection And Ranging (RADAR) -- 4.4.6. Global Navigation Satellite System (GNSS) -- 4.5. Connectivity and means of communication -- 4.5.1. State of the art -- 4.5.2. Statistical model of the propagation channel -- 4.5.3. Multi-platform physico-realistic model -- 4.6. Some relevant use cases -- 4.6.1. Graphic resources -- 4.6.2. Communication and overall risk -- 4.6.3. Automated parking maneuver -- 4.6.4. Co-pilot and automated driving -- 4.6.5. Eco-mobility and eco-responsible driving profile -- 4.7. Conclusion and perspectives -- 4.8. References -- 5 Standards for Cooperative Intelligent Transport Systems (C-ITS) -- 5.1. Context and goals -- 5.1.1. Intelligent transport systems (ITS) -- 5.1.2. The connected and cooperative vehicle -- 5.1.3. Silos communication systems -- 5.1.4. Cooperative Intelligent Transport Systems (C-ITS)</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">5.1.5. Diversity of Cooperative ITS services -- 5.1.6. Standardization bodies -- 5.1.7. Genesis of the "Cooperative ITS" standards -- 5.2. "ITS station" architecture -- 5.2.1. General description -- 5.2.2. ITS station communication units -- 5.2.3. Types of ITS stations -- 5.3. Features of the ITS station architecture -- 5.3.1. Combination of communication technologies -- 5.3.2. Centralized communications -- 5.3.3. Localized communications (V2X) -- 5.3.4. Hybrid communications -- 5.3.5. Extensive communications -- 5.3.6. Communications management -- 5.3.7. Messaging -- 5.3.8. Data organization and identification -- 5.3.9. Secure communications and access to data -- 5.3.10. Evolution of standards -- 5.4. Features of the ITS station architecture -- 5.5. Deployment of Cooperative ITS services -- 5.6. References -- 6 The Integration of Pedestrian Orientation for the Benefit of ADAS: A Moroccan Case Study -- 6.1. Introduction -- 6.2. Advanced Driver Assistance System (ADAS) -- 6.3. Proposal for an applicable system to the Moroccan case -- 6.4. General conclusion -- 6.5. References -- 7 Autonomous Vehicle: What Legal Issues? -- 7.1. Introduction -- 7.2. The definition of the so-called "autonomous" vehicle -- 7.3. Legal framework and experiments -- 7.4. The notion of the "driver" -- 7.5. The notion of the "custodian" -- 7.6. What liability regime? -- 7.7. Self-driving vehicle insurance? -- 7.8. Personal data and the autonomous vehicle -- 7.9. The need for uniform regulation -- List of Authors -- Index -- Other titles from iSTE in Mechanical Engineering and Solid Mechanics -- EULA.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bensrhair, Abdelaziz</subfield><subfield code="4">edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bapin, Thierry</subfield><subfield code="4">edt</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="a">Bensrhair, Abdelaziz</subfield><subfield code="t">From AI to Autonomous and Connected Vehicles</subfield><subfield code="d">Newark : John Wiley & Sons, Incorporated,c2021</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-1-78630-727-9</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Science, society and new technologies series. Digital sciences set</subfield><subfield code="v">Volume 2</subfield><subfield code="w">(DE-604)BV048446103</subfield><subfield code="9">2</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://ieeexplore.ieee.org/book/9714893</subfield><subfield code="x">Aggregator</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-30-PQE</subfield><subfield code="a">ZDB-35-IWT</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033609328</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ieeexplore.ieee.org/book/9714893</subfield><subfield code="l">FHI01</subfield><subfield code="p">ZDB-35-IWT</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://ebookcentral.proquest.com/lib/munchentech/detail.action?docID=6712451</subfield><subfield code="l">TUM01</subfield><subfield code="p">ZDB-30-PQE</subfield><subfield code="q">TUM_PDA_PQE_Kauf</subfield><subfield code="x">Aggregator</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV048228609 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T19:50:52Z |
| indexdate | 2024-11-25T18:02:39Z |
| institution | BVB |
| isbn | 9781119855491 9781119855507 9781119855484 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033609328 |
| oclc_num | 1266909081 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM DE-573 |
| owner_facet | DE-91 DE-BY-TUM DE-573 |
| physical | 1 Online-Ressource (xxiv, 251 Seiten) Illustrationen, Diagramme |
| psigel | ZDB-30-PQE ZDB-35-IWT ZDB-30-PQE TUM_PDA_PQE_Kauf |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | ISTE Wiley |
| record_format | marc |
| series | Science, society and new technologies series. Digital sciences set |
| series2 | Science, society and new technologies series. Digital sciences set Mechanical engineering and solid mechanics |
| spellingShingle | From AI to autonomous and connected vehicles advanced driver-assistance systems (ADAS) Science, society and new technologies series. Digital sciences set Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Foreword 1 -- Foreword 2 -- Foreword 3 -- Preface -- 1 Artificial Intelligence for Vehicles -- 1.1. What is AI? -- 1.2. The main methods of AI -- 1.2.1. Deep Learning -- 1.2.2. Machine Learning -- 1.2.3. Clustering -- 1.2.4. Reinforcement learning -- 1.2.5. Case-based reasoning -- 1.2.6. Logical reasoning -- 1.2.7. Multi-agent systems -- 1.2.8. PAC learning -- 1.3. Modern AI challenges for the industry -- 1.3.1. Explainability: XAI (eXplainable Artificial Intelligence) -- 1.3.2. The design of so-called "hybrid" AI systems -- 1.4. What is an "intelligent" vehicle? -- 1.4.1. ADAS -- 1.4.2. The autonomous vehicle -- 1.4.2. The construction of the intelligent vehicle's basic building blocks employing AI methods -- 1.5. References -- 2 Conventional Vision or Not: A Selection of Low-level Algorithms -- 2.1. Introduction -- 2.2. Vision sensors -- 2.2.1. Conventional cameras -- 2.2.2. Emerging sensors -- 2.3. Vision algorithms -- 2.3.1. Choosing the type of information to be retrieved from the images -- 2.3.2. Estimation of ego-movement and localization -- 2.3.3. Detection of the navigable space by a dense approach -- 2.3.4. From the detection of 3D plans to visual odometry -- 2.3.5. Detection of obstacles through the compensation of ego-movement -- 2.3.6. Visual odometry -- 2.4. Conclusion -- 2.5. References -- 3 Automated Driving, a Question of Trajectory Planning -- 3.1. Definition of planning -- 3.2. Trajectory planning: general characteristics -- 3.2.1. Variables -- 3.2.2. Constraints -- 3.2.3. Cost functions -- 3.2.4. Planning methodology -- 3.2.5. Co-pilot respecting legal traffic rules -- 3.2.6. Trajectory prediction for "ghost" objects and vehicles -- 3.2.7. Trajectory evaluation -- 3.2.8. Results on real vehicles and on simulators -- 3.3. Multi-objective trajectory planning 3.3.1. Linear scalarization -- 3.3.2. Nonlinear scalarization -- 3.3.3. Ideal methods -- 3.3.4. Summary of multi-objective planning methods -- 3.3.5. High level information -- 3.4. Conclusion on multi-agent planning for a fleet of vehicles: the future of planning -- 3.5. References -- 4 From Virtual to Real, How to Prototype, Test, Evaluate and Validate ADAS for the Automated and Connected Vehicle? -- 4.1. Context and goals -- 4.2. Generic dynamic and distributed architecture -- 4.2.1. Introduction -- 4.2.2. An interoperable platform -- 4.3. Environment and climatic conditions -- 4.3.1. Introduction -- 4.3.2. Environmental modeling: lights, shadows, materials and textures -- 4.3.3. Degraded, adverse and climatic conditions -- 4.3.4. Visibility layers and ground truths -- 4.4. Modeling of perception sensors -- 4.4.1. Typology of sensor technologies -- 4.4.2. From a functional model to a physical model -- 4.4.3. Optical sensors -- 4.4.4. LIght Detection And Ranging (LIDAR) -- 4.4.5. RAdio Detection And Ranging (RADAR) -- 4.4.6. Global Navigation Satellite System (GNSS) -- 4.5. Connectivity and means of communication -- 4.5.1. State of the art -- 4.5.2. Statistical model of the propagation channel -- 4.5.3. Multi-platform physico-realistic model -- 4.6. Some relevant use cases -- 4.6.1. Graphic resources -- 4.6.2. Communication and overall risk -- 4.6.3. Automated parking maneuver -- 4.6.4. Co-pilot and automated driving -- 4.6.5. Eco-mobility and eco-responsible driving profile -- 4.7. Conclusion and perspectives -- 4.8. References -- 5 Standards for Cooperative Intelligent Transport Systems (C-ITS) -- 5.1. Context and goals -- 5.1.1. Intelligent transport systems (ITS) -- 5.1.2. The connected and cooperative vehicle -- 5.1.3. Silos communication systems -- 5.1.4. Cooperative Intelligent Transport Systems (C-ITS) 5.1.5. Diversity of Cooperative ITS services -- 5.1.6. Standardization bodies -- 5.1.7. Genesis of the "Cooperative ITS" standards -- 5.2. "ITS station" architecture -- 5.2.1. General description -- 5.2.2. ITS station communication units -- 5.2.3. Types of ITS stations -- 5.3. Features of the ITS station architecture -- 5.3.1. Combination of communication technologies -- 5.3.2. Centralized communications -- 5.3.3. Localized communications (V2X) -- 5.3.4. Hybrid communications -- 5.3.5. Extensive communications -- 5.3.6. Communications management -- 5.3.7. Messaging -- 5.3.8. Data organization and identification -- 5.3.9. Secure communications and access to data -- 5.3.10. Evolution of standards -- 5.4. Features of the ITS station architecture -- 5.5. Deployment of Cooperative ITS services -- 5.6. References -- 6 The Integration of Pedestrian Orientation for the Benefit of ADAS: A Moroccan Case Study -- 6.1. Introduction -- 6.2. Advanced Driver Assistance System (ADAS) -- 6.3. Proposal for an applicable system to the Moroccan case -- 6.4. General conclusion -- 6.5. References -- 7 Autonomous Vehicle: What Legal Issues? -- 7.1. Introduction -- 7.2. The definition of the so-called "autonomous" vehicle -- 7.3. Legal framework and experiments -- 7.4. The notion of the "driver" -- 7.5. The notion of the "custodian" -- 7.6. What liability regime? -- 7.7. Self-driving vehicle insurance? -- 7.8. Personal data and the autonomous vehicle -- 7.9. The need for uniform regulation -- List of Authors -- Index -- Other titles from iSTE in Mechanical Engineering and Solid Mechanics -- EULA. |
| title | From AI to autonomous and connected vehicles advanced driver-assistance systems (ADAS) |
| title_auth | From AI to autonomous and connected vehicles advanced driver-assistance systems (ADAS) |
| title_exact_search | From AI to autonomous and connected vehicles advanced driver-assistance systems (ADAS) |
| title_exact_search_txtP | From AI to autonomous and connected vehicles advanced driver-assistance systems (ADAS) |
| title_full | From AI to autonomous and connected vehicles advanced driver-assistance systems (ADAS) edited by Abdelaziz Bensrhair, Thierry Bapin |
| title_fullStr | From AI to autonomous and connected vehicles advanced driver-assistance systems (ADAS) edited by Abdelaziz Bensrhair, Thierry Bapin |
| title_full_unstemmed | From AI to autonomous and connected vehicles advanced driver-assistance systems (ADAS) edited by Abdelaziz Bensrhair, Thierry Bapin |
| title_short | From AI to autonomous and connected vehicles |
| title_sort | from ai to autonomous and connected vehicles advanced driver assistance systems adas |
| title_sub | advanced driver-assistance systems (ADAS) |
| url | https://ieeexplore.ieee.org/book/9714893 |
| volume_link | (DE-604)BV048446103 |
| work_keys_str_mv | AT bensrhairabdelaziz fromaitoautonomousandconnectedvehiclesadvanceddriverassistancesystemsadas AT bapinthierry fromaitoautonomousandconnectedvehiclesadvanceddriverassistancesystemsadas |