Advances in Automated Driving Systems
Electrification, automation of vehicle control, digitalization and new mobility are the mega-trends in automotive engineering, and they are strongly connected. While many demonstrations for highly automated vehicles have been made worldwide, many challenges remain in bringing automated vehicles to t...
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| Aineistotyyppi: | Online |
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| Kieli: | englanti |
| Julkaistu: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Aiheet: | |
| Linkit: | ONIX_20220706_9783036545035_124 |
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| _version_ | 1869517739753734144 |
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| collection | Directory of Open Access Books |
| description | Electrification, automation of vehicle control, digitalization and new mobility are the mega-trends in automotive engineering, and they are strongly connected. While many demonstrations for highly automated vehicles have been made worldwide, many challenges remain in bringing automated vehicles to the market for private and commercial use. The main challenges are as follows: reliable machine perception; accepted standards for vehicle-type approval and homologation; verification and validation of the functional safety, especially at SAE level 3+ systems; legal and ethical implications; acceptance of vehicle automation by occupants and society; interaction between automated and human-controlled vehicles in mixed traffic; human–machine interaction and usability; manipulation, misuse and cyber-security; the system costs of hard- and software and development efforts. This Special Issue was prepared in the years 2021 and 2022 and includes 15 papers with original research related to recent advances in the aforementioned challenges. The topics of this Special Issue cover: Machine perception for SAE L3+ driving automation; Trajectory planning and decision-making in complex traffic situations; X-by-Wire system components; Verification and validation of SAE L3+ systems; Misuse, manipulation and cybersecurity; Human–machine interactions, driver monitoring and driver-intention recognition; Road infrastructure measures for the introduction of SAE L3+ systems; Solutions for interactions between human- and machine-controlled vehicles in mixed traffic. |
| format | Online |
| id | doab-20.500.12854ir-87529 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-875292024-04-09T23:16:00Z Advances in Automated Driving Systems Eichberger, Arno Szalay, Zsolt Fellendorf, Martin Liu, Henry automated driving scenario-based testing software framework traffic signs ADAS traffic sign recognition system cooperative perception ITS digital twin sensor fusion edge cloud autonomous drifting model predictive control (MPC) successive linearization adaptive control vehicle motion control varying road surfaces vehicle dynamics Mask R-CNN transfer learning inverse gamma correction illumination instance segmentation pedestrian custom dataset deep learning wheel loaders throttle prediction state prediction automation safety validation automated driving systems decomposition modular safety approval modular testing fault tree analysis adaptive cruise control informed machine learning physics-guided reinforcement learning safety autonomous vehicles autonomous conflict management UTM UAV UGV U-Space framework development lane detection simulation and modelling multi-layer perceptron convolutional neural network driver drowsiness ECG signal heart rate variability wavelet scalogram automated driving (AD) driving simulator expression of trust acceptance simulator case study NASA TLX advanced driver assistant systems (ADAS) system usability scale driving school virtual validation ground truth reference measurement calibration method simulation traffic evaluation simulation and modeling connected and automated vehicle driver assistance system virtual test and validation radar sensor physical perception model virtual sensor model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Electrification, automation of vehicle control, digitalization and new mobility are the mega-trends in automotive engineering, and they are strongly connected. While many demonstrations for highly automated vehicles have been made worldwide, many challenges remain in bringing automated vehicles to the market for private and commercial use. The main challenges are as follows: reliable machine perception; accepted standards for vehicle-type approval and homologation; verification and validation of the functional safety, especially at SAE level 3+ systems; legal and ethical implications; acceptance of vehicle automation by occupants and society; interaction between automated and human-controlled vehicles in mixed traffic; human–machine interaction and usability; manipulation, misuse and cyber-security; the system costs of hard- and software and development efforts. This Special Issue was prepared in the years 2021 and 2022 and includes 15 papers with original research related to recent advances in the aforementioned challenges. The topics of this Special Issue cover: Machine perception for SAE L3+ driving automation; Trajectory planning and decision-making in complex traffic situations; X-by-Wire system components; Verification and validation of SAE L3+ systems; Misuse, manipulation and cybersecurity; Human–machine interactions, driver monitoring and driver-intention recognition; Road infrastructure measures for the introduction of SAE L3+ systems; Solutions for interactions between human- and machine-controlled vehicles in mixed traffic. 2022-07-06T11:54:38Z 2022-07-06T11:54:38Z 2022 book ONIX_20220706_9783036545035_124 9783036545035 9783036545042 https://directory.doabooks.org/handle/20.500.12854/87529 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/5727 https://mdpi.com/books/pdfview/book/5727 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-4504-2 10.3390/books978-3-0365-4504-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036545035 9783036545042 294 Basel open access |
| spellingShingle | automated driving scenario-based testing software framework traffic signs ADAS traffic sign recognition system cooperative perception ITS digital twin sensor fusion edge cloud autonomous drifting model predictive control (MPC) successive linearization adaptive control vehicle motion control varying road surfaces vehicle dynamics Mask R-CNN transfer learning inverse gamma correction illumination instance segmentation pedestrian custom dataset deep learning wheel loaders throttle prediction state prediction automation safety validation automated driving systems decomposition modular safety approval modular testing fault tree analysis adaptive cruise control informed machine learning physics-guided reinforcement learning safety autonomous vehicles autonomous conflict management UTM UAV UGV U-Space framework development lane detection simulation and modelling multi-layer perceptron convolutional neural network driver drowsiness ECG signal heart rate variability wavelet scalogram automated driving (AD) driving simulator expression of trust acceptance simulator case study NASA TLX advanced driver assistant systems (ADAS) system usability scale driving school virtual validation ground truth reference measurement calibration method simulation traffic evaluation simulation and modeling connected and automated vehicle driver assistance system virtual test and validation radar sensor physical perception model virtual sensor model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Advances in Automated Driving Systems |
| title | Advances in Automated Driving Systems |
| title_full | Advances in Automated Driving Systems |
| title_fullStr | Advances in Automated Driving Systems |
| title_full_unstemmed | Advances in Automated Driving Systems |
| title_short | Advances in Automated Driving Systems |
| title_sort | advances in automated driving systems |
| topic | automated driving scenario-based testing software framework traffic signs ADAS traffic sign recognition system cooperative perception ITS digital twin sensor fusion edge cloud autonomous drifting model predictive control (MPC) successive linearization adaptive control vehicle motion control varying road surfaces vehicle dynamics Mask R-CNN transfer learning inverse gamma correction illumination instance segmentation pedestrian custom dataset deep learning wheel loaders throttle prediction state prediction automation safety validation automated driving systems decomposition modular safety approval modular testing fault tree analysis adaptive cruise control informed machine learning physics-guided reinforcement learning safety autonomous vehicles autonomous conflict management UTM UAV UGV U-Space framework development lane detection simulation and modelling multi-layer perceptron convolutional neural network driver drowsiness ECG signal heart rate variability wavelet scalogram automated driving (AD) driving simulator expression of trust acceptance simulator case study NASA TLX advanced driver assistant systems (ADAS) system usability scale driving school virtual validation ground truth reference measurement calibration method simulation traffic evaluation simulation and modeling connected and automated vehicle driver assistance system virtual test and validation radar sensor physical perception model virtual sensor model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | automated driving scenario-based testing software framework traffic signs ADAS traffic sign recognition system cooperative perception ITS digital twin sensor fusion edge cloud autonomous drifting model predictive control (MPC) successive linearization adaptive control vehicle motion control varying road surfaces vehicle dynamics Mask R-CNN transfer learning inverse gamma correction illumination instance segmentation pedestrian custom dataset deep learning wheel loaders throttle prediction state prediction automation safety validation automated driving systems decomposition modular safety approval modular testing fault tree analysis adaptive cruise control informed machine learning physics-guided reinforcement learning safety autonomous vehicles autonomous conflict management UTM UAV UGV U-Space framework development lane detection simulation and modelling multi-layer perceptron convolutional neural network driver drowsiness ECG signal heart rate variability wavelet scalogram automated driving (AD) driving simulator expression of trust acceptance simulator case study NASA TLX advanced driver assistant systems (ADAS) system usability scale driving school virtual validation ground truth reference measurement calibration method simulation traffic evaluation simulation and modeling connected and automated vehicle driver assistance system virtual test and validation radar sensor physical perception model virtual sensor model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20220706_9783036545035_124 |