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    Multi-Objective reinforcement learning approach for improving safety at intersections with adaptive traffic signal control

    Gong, Yaobang / Abdel-Aty, Mohamed / Yuan, Jinghui et al. | Elsevier | 2020
    Schlagwörter: Multi-objective reinforcement learning , Deep learning

    Characterizing accident narratives with word embeddings: Improving accuracy, richness, and generalizability

    Goldberg, David M. | Elsevier | 2021
    Schlagwörter: Machine learning , Transfer learning

    A deep learning based traffic crash severity prediction framework

    Rahim, Md Adilur / Hassan, Hany M. | Elsevier | 2021
    Schlagwörter: Deep learning , Transfer learning

    A feature learning approach based on XGBoost for driving assessment and risk prediction

    Shi, Xiupeng / Wong, Yiik Diew / Li, Michael Zhi-Feng et al. | Elsevier | 2019
    Schlagwörter: Feature learning

    Highway crash detection and risk estimation using deep learning

    Huang, Tingting / Wang, Shuo / Sharma, Anuj | Elsevier | 2019
    Schlagwörter: Deep learning

    Developing and testing a hazard prediction task for novice drivers: A novel application of naturalistic driving videos

    Ehsani, Johnathon P. / Seymour, Karen E. / Chirles, Theresa et al. | Elsevier | 2020
    Schlagwörter: Learning

    Some implications of an event-based definition of exposure to the risk of road accident

    Elvik, Rune | Elsevier | 2014
    Schlagwörter: Learning

    Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis

    Parsa, Amir Bahador / Movahedi, Ali / Taghipour, Homa et al. | Elsevier | 2019
    Schlagwörter: Machine learning

    Advancing urban traffic accident forecasting through sparse spatio-temporal dynamic learning

    Cui, Pengfei / Yang, Xiaobao / Abdel-Aty, Mohamed et al. | Elsevier | 2024
    Schlagwörter: Hypergraph Learning , Self-Supervised Learning

    A Bayesian deep learning method for freeway incident detection with uncertainty quantification

    Liu, Genwang / Jin, Haolin / Li, Jiaze et al. | Elsevier | 2022
    Schlagwörter: Bayesian deep learning , Machine learning

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