Narrow your search

Library

KU Leuven (2)

LUCA School of Arts (2)

Odisee (2)

Thomas More Kempen (2)

Thomas More Mechelen (2)

UCLL (2)

VIVES (2)

FARO (1)

ULiège (1)

Vlaams Parlement (1)

More...

Resource type

book (3)


Language

English (2)

German (1)


Year
From To Submit

2022 (2)

2019 (1)

Listing 1 - 3 of 3
Sort by

Book
Heilsame Architektur
Authors: ---
ISBN: 3839445035 9783839445037 Year: 2019 Publisher: Bielefeld

Loading...
Export citation

Choose an application

Bookmark

Abstract

»Healing Design«, »Architecture for Health«, »Urban Health« - immer lauter wird der Ruf nach Bauten, die nicht nur funktional gestaltet sind, sondern so, dass Menschen sich in ihnen wohlfühlen und besser gesund werden: nach Architekturen also, welche die Gesetzmäßigkeiten des leiblich-räumlichen Wahrnehmens und Spürens berücksichtigen. Katharina Brichetti und Franz Mechsner stellen Projekte heilsamer Architektur vor und verbinden dies mit Einsichten aus Psychologie, Neurobiologie und Phänomenologie, um zu zeigen, was menschenfreundliche Raumgestaltung ausmacht. Im Mittelpunkt steht dabei die Wirkung gebauter Umwelt auf das Erleben im Sinne einer »Rehumanisierung von Architektur« (Gernot Böhme). »Damit das, was Brichetti und Mechsner in ihrem Buch an Wissens- und Lösungsansätzen so hilfreich zusammengetragen haben, sich zukünftig vermehrt in Praxis umzusetzen lässt, bedarf es der Zusammenarbeit von Bürgerbeteiligungen und interdisziplinären Expertengruppen. Dementsprechend empfehle ich ihr Buch sehr für alle ExpertInnen und Initiativen aus Stadtplanungs- und Krankenbereichen, aber auch aus Politik und Ökonomie.« Helmut Milz, www.flaneurin.at, 18.10.2020 »Die beiden Autoren lassen nicht außer Acht, dass der Zugang zu architektonisch heilsamen Umgebungen immer stärker zu einer Frage der sozialen Gerechtigkeit wird. So ist ein Buch entstanden, das Architektur in einen ganzheitlichen Zusammenhang stellt.« Stadt+Grün, 8 (2019) Besprochen in: www.kultur-punkt.ch, 7 (2019), Franz Mechsner Stadt und Raum, 4 (2019) Konturen, 06.09.2019 www.swiss-architects.com, 19.09.2019, Inge Beckel TEC21, 45 (2019) DAB Regional, 12 (2019), Loni Siegmund jot.wd, 12 (2019), Ralf Nachtmann Stadt+Grün, 8 (2019)


Book
Advances in Automated Driving Systems
Authors: --- --- ---
Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

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.

Keywords

Technology: general issues --- History of engineering & technology --- 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 --- 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


Book
Advances in Automated Driving Systems
Authors: --- --- ---
Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

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.

Keywords

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

Listing 1 - 3 of 3
Sort by