Advances in Automated Driving Systems

• Autore: Eichberger Arno
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 online resource (294 p.)
• Soggetto topico: History of engineering & technology; Technology: general issues
• Soggetto non controllato: acceptance; adaptive control; adaptive cruise control; ADAS; advanced driver assistant systems (ADAS); automated driving; automated driving (AD); automated driving systems; automation; autonomous conflict management; autonomous drifting; autonomous vehicles; calibration method; connected and automated vehicle; convolutional neural network; cooperative perception; decomposition; deep learning; digital twin; driver assistance system; driver drowsiness; driving school; driving simulator; ECG signal; edge cloud; expression of trust; fault tree analysis; framework development; ground truth; heart rate variability; illumination; informed machine learning; instance segmentation; inverse gamma correction; ITS; lane detection; Mask R-CNN; model predictive control (MPC); modular safety approval; modular testing; multi-layer perceptron; n/a; NASA TLX; pedestrian custom dataset; physical perception model; physics-guided reinforcement learning; radar sensor; reference measurement; safety; safety validation; scenario-based testing; sensor fusion; simulation; simulation and modeling; simulation and modelling; simulator case study; software framework; state prediction; successive linearization; system usability scale; throttle prediction; traffic evaluation; traffic sign recognition system; traffic signs; transfer learning; U-Space; UAV; UGV; UTM; varying road surfaces; vehicle dynamics; vehicle motion control; virtual sensor model; virtual test and validation; virtual validation; wavelet scalogram; wheel loaders
• Persona (resp. second.): SzalayZsolt; FellendorfMartin; LiuHenry; EichbergerArno
• Sommario/riassunto: 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.
• Titolo autorizzato: Advances in Automated Driving Systems
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910580214003321
• Lo trovi qui: Univ. Federico II