Sökning: "Naturalistic driving data"

Visar resultat 1 - 5 av 6 uppsatser innehållade orden Naturalistic driving data.

  1. 1. Parameter Estimation and Simulation of Driving Datasets

    Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Författare :Bojian Qu; [2023]
    Nyckelord :autonomous vehicles; safety assessment; trajectory generation; safety-critical scenarios; density estimation; approximate inference; självkörande fordon; säkerhetsbedömning; bana generering; säkerhetskritiska scenarier; densitetsuppskattning; ungefärlig slutledning;

    Sammanfattning : The development of autonomous driving in recent years has been in full swing and one of the aspects that Autonomous Vehicles (AVs) should always focus on is safety. Although the corresponding technology has gradually matured, and AVs have performed well in a large number of tests, people are still uncertain whether AVs can cope with all possible situations. LÄS MER

  3. 2. Identification of driver baselines

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Alexander Malmgren; Fabian Daneshmand-Mehr; [2022-06-27]
    Nyckelord :computer; science; computer science; Time series clustering; clustering; ADAS; driver profile; statistics;

    Sammanfattning : This thesis aims to answer whether it is possible to produce one or more baselines based on naturalistic driving data collected over a period of 8 months. The baseline is based on variables extracted from the drivers action, such as acceleration and gaze vectors, along with variables extracted from the nature of the trip, such as time of day or road type. LÄS MER

  4. 3. Driver Behavior Classification in Electric Vehicles

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :FEDERICA COMUNI; CHRISTOPHER MÉSZÁROS; [2021-07-06]
    Nyckelord :Aggressive driver behavior; Driver behavior classification; Self-attention; Recurrence plots; active learning; Active deep dropout; Gradual pseudo labeling;

    Sammanfattning : Studies have shown that driving style affects the energy consumption of electric vehicles, with aggressive driving consuming up to 30% more energy than moderate driving. Therefore, modeling of aggressive driving can provide a more precise estimation of the energy consumption and the remaining range of a vehicle. LÄS MER

  5. 4. Towards Vision Zero using Virtual Reality

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Vivek Vivian; [2021]
    Nyckelord :;

    Sammanfattning : The number of individuals killed in road accidents around the world is rising. The problem of road safety is a big societal concern. Drivers have a challenge while overtaking vulnerable road users since it necessitates a well-timed, safe interaction between the vehicle, the road user, and approaching traffic. LÄS MER

  7. 5. Dynamic Speed Adaptation for Curves using Machine Learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Kirilll Narmack; [2018]
    Nyckelord :Machine; Learning; Artificial; Intelligence; MachineLearning; Machine-Learning; AI; ML; MLP; Neural; Networks; Multilayer-Perceptron; RFB; RBF-Network; Vehicle; Automation; AutonomousVehicles; Autonomous; SelfDriving; Self-Driving; Self; Driving; Curve; Speed; Adaptation; Adaption; CSA; ACC; Adaptive; Cruise; Control; Driving; Style; Driver; Behavior; Behaviour; Sample; Samples; Distance; Derivative; Speed; Velocity; Curvature; Road; Inclination; Lane; Width; Type; Acceleration; Longitudinal; Lateral; Data; Training; Test; Validation; Results; Discussion; Sustainability; Ethics; Ethical; Sustainable; Future; Today; Tomorrow; Yesterday; Robot; Robotics; System; Systems; Class; Classes; Bin; Bins; Tree; One; A; Dynamic; Using; Time; Delay; Volvo; Car; Cars; Corporation; Zenuity; School; Computer; Science; Master; Degree; Project; Thesis; Paper; Object; GPS; Map; Length; Research; Advanced; Машинное; Обучение; Искусственный; Интеллект; AI; ML; MLP; RBF; Автомобиль; Машына; Сеть; Робот; Водитель; Заворот; Дорога; Сам; Сама; Едет; Ехать; Учить; Учит; Учится; Автоматизация; Адаптация; Результат; Один; Одна; Одно; Вчера; Сегодня; Завтра; Дерево; Карта; ГПС; Информатика; Компьютер; Наука; Научная; Работа; Школа; Вольво; Завод; Транспорт; Maskininlärning; Artificiell; Intelligens; Inlärning; Maskin; AI; ML; MLP; RBF; Neural; Neurala; Nätverk; Artificiella; Automation; Själv; Självkörande; Körande; Bil; Fordon; Robot; Robotik; Körstil; Stil; Beteende; Adaption; Kurva; Lutning; Väg; CSA; ACC; Farthållare; Hastighet; Fart; Hållare; Inclination; Körfält; Fält; Spår; Bredd; Typ; Acceleration; Longitudinell; Lateral; Data; Traingin; Test; Validation; Resultat; Diskussion; Längd; Hållbarhet; Etik; Etiskt; Framtid; Dåtid; Idag; Imorgon; System; Class; Klass; Classer; Klasser; Träd; En; Ett; Fler; Flera; Dynamisk; Använda; Tid; Fördröjning; Tids; Volvo; Car; Corporation; Object; Zenuity; Skola; Dator; Vetenskap; Forkning; Avancerad; Projekt; Exjobb; Examensarbete; Betyg; GPS; Karta;

    Sammanfattning : The vehicles of tomorrow will be more sophisticated, intelligent and safe than the vehicles of today. The future is leaning towards fully autonomous vehicles. LÄS MER