05609nam 2201357z- 450 991058021400332120220706(CKB)5690000000011948(oapen)https://directory.doabooks.org/handle/20.500.12854/87529(oapen)doab87529(EXLCZ)99569000000001194820202207d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAdvances in Automated Driving SystemsBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (294 p.)3-0365-4503-4 3-0365-4504-2 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.History of engineering & technologybicsscTechnology: general issuesbicsscacceptanceadaptive controladaptive cruise controlADASadvanced driver assistant systems (ADAS)automated drivingautomated driving (AD)automated driving systemsautomationautonomous conflict managementautonomous driftingautonomous vehiclescalibration methodconnected and automated vehicleconvolutional neural networkcooperative perceptiondecompositiondeep learningdigital twindriver assistance systemdriver drowsinessdriving schooldriving simulatorECG signaledge cloudexpression of trustfault tree analysisframework developmentground truthheart rate variabilityilluminationinformed machine learninginstance segmentationinverse gamma correctionITSlane detectionMask R-CNNmodel predictive control (MPC)modular safety approvalmodular testingmulti-layer perceptronn/aNASA TLXpedestrian custom datasetphysical perception modelphysics-guided reinforcement learningradar sensorreference measurementsafetysafety validationscenario-based testingsensor fusionsimulationsimulation and modelingsimulation and modellingsimulator case studysoftware frameworkstate predictionsuccessive linearizationsystem usability scalethrottle predictiontraffic evaluationtraffic sign recognition systemtraffic signstransfer learningU-SpaceUAVUGVUTMvarying road surfacesvehicle dynamicsvehicle motion controlvirtual sensor modelvirtual test and validationvirtual validationwavelet scalogramwheel loadersHistory of engineering & technologyTechnology: general issuesEichberger Arnoedt1328211Szalay ZsoltedtFellendorf MartinedtLiu HenryedtEichberger ArnoothSzalay ZsoltothFellendorf MartinothLiu HenryothBOOK9910580214003321Advances in Automated Driving Systems3038431UNINA