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Synonyme wurden verwendet für: Machine learning
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    Enhancing autonomous vehicle hyperawareness in busy traffic environments: A machine learning approach

    Alozi, Abdul Razak / Hussein, Mohamed | Elsevier | 2024
    Schlagwörter: Machine learning

    Geographically weighted machine learning for modeling spatial heterogeneity in traffic crash frequency and determinants in US

    Wang, Shuli / Gao, Kun / Zhang, Lanfang et al. | Elsevier | 2024
    Schlagwörter: Spatial machine learning

    Revisiting the hybrid approach of anomaly detection and extreme value theory for estimating pedestrian crashes using traffic conflicts obtained from artificial intelligence-based video analytics

    Hussain, Fizza / Ali, Yasir / Li, Yuefeng et al. | Elsevier | 2024
    Schlagwörter: Machine learning

    Integrating visual factors in crash rate analysis at Intersections: An AutoML and SHAP approach towards cycling safety

    Xue, Huiyuan / Guo, Peizhuo / Li, Yiyan et al. | Elsevier | 2024
    Schlagwörter: Automated machine learning

    The usefulness of artificial intelligence for safety assessment of different transport modes

    Tselentis, Dimitrios I. / Papadimitriou, Eleonora / van Gelder, Pieter | Elsevier | 2023
    Schlagwörter: Machine Learning

    Towards safer streets: A framework for unveiling pedestrians’ perceived road safety using street view imagery

    Hamim, Omar Faruqe / Ukkusuri, Satish V. | Elsevier | 2023
    Schlagwörter: Machine learning

    Exploring nighttime pedestrian crash patterns at intersection and segments: Findings from the machine learning algorithm

    Hossain, Ahmed / Sun, Xiaoduan / Shahrier, Mahir et al. | Elsevier | 2023
    Schlagwörter: Machine learning

    Analyzing the injury severity in single-bicycle crashes: An application of the ordered forest with some practical guidance

    Zhang, Yingheng / Li, Haojie / Ren, Gang | Elsevier | 2023
    Schlagwörter: Machine learning

    Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review

    Ali, Yasir / Hussain, Fizza / Haque, Md Mazharul | Elsevier | 2023
    Schlagwörter: Machine learning

    Injury severity prediction of cyclist crashes using random forests and random parameters logit models

    Scarano, Antonella / Rella Riccardi, Maria / Mauriello, Filomena et al. | Elsevier | 2023
    Schlagwörter: Machine learning

    An interpretable clustering approach to safety climate analysis: Examining driver group distinctions

    Sun, Kailai / Lan, Tianxiang / Goh, Yang Miang et al. | Elsevier | 2023
    Schlagwörter: Interpretable machine learning

    An integrated data- and theory-driven crash severity model

    Liu, Dongjie / Li, Dawei / Sze, N.N. et al. | Elsevier | 2023
    Schlagwörter: Interpretable machine learning

    Road safety evaluation with multiple treatments: A comparison of methods based on simulations

    Zhang, Yingheng / Li, Haojie / Ren, Gang | Elsevier | 2023
    Schlagwörter: Machine learning

    An integrated approach of machine learning and Bayesian spatial Poisson model for large-scale real-time traffic conflict prediction

    Li, Dongya / Fu, Chuanyun / Sayed, Tarek et al. | Elsevier | 2023
    Schlagwörter: Machine learning

    Explore traffic conflict risks considering motion constraint degree in the diverging area of toll plazas

    Xing, Lu / Yu, Le / Zheng, Ou et al. | Elsevier | 2023
    Schlagwörter: Machine learning

    Toward safer highway work zones: An empirical analysis of crash risks using improved safety potential field and machine learning techniques

    Wang, Bo / Chen, Tianyi / Zhang, Chi et al. | Elsevier | 2023
    Schlagwörter: Machine learning

    Traffic conflict assessment using macroscopic traffic flow variables: A novel framework for real-time applications

    Gore, Ninad / Chauhan, Ritvik / Easa, Said et al. | Elsevier | 2023
    Schlagwörter: Machine learning models

    A systematic approach to macro-level safety assessment and contributing factors analysis considering traffic crashes and violations

    Wang, Xuesong / Zhang, Xueyu / Pei, Yingying | Elsevier | 2023
    Schlagwörter: Interpretable machine learning framework

    An interpretable prediction model of illegal running into the opposite lane on curve sections of two-lane rural roads from drivers’ visual perceptions

    He, Li / Yu, Bo / Chen, Yuren et al. | Elsevier | 2023
    Schlagwörter: Interpretable machine learning

    Using contextual data to predict risky driving events: A novel methodology from explainable artificial intelligence

    Masello, Leandro / Castignani, German / Sheehan, Barry et al. | Elsevier | 2023
    Schlagwörter: Machine learning

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