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1–50 von 82 Ergebnissen
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    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

    Enhancing autonomous vehicle hyperawareness in busy traffic environments: A machine learning approach

    Alozi, Abdul Razak / Hussein, Mohamed | 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

    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

    An integrated data- and theory-driven crash severity model

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

    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

    Factors impacting bike crash severity in urban areas

    Dash, Ishita / Abkowitz, Mark / Philip, Craig | Elsevier | 2022
    Schlagwörter: Machine learning

    Application of explainable machine learning for real-time safety analysis toward a connected vehicle environment

    Yuan, Chen / Li, Ye / Huang, Helai et al. | Elsevier | 2022
    Schlagwörter: Machine learning

    Unveiling the relevance of traffic enforcement cameras on the severity of vehicle–pedestrian collisions in an urban environment with machine learning models

    Pineda-Jaramillo, Juan / Barrera-Jiménez, Humberto / Mesa-Arango, Rodrigo | Elsevier | 2022
    Schlagwörter: Machine learning

    Safety assurance for automated driving systems that can adapt using machine learning: A qualitative interview study

    Ballingall, Stuart / Sarvi, Majid / Sweatman, Peter | Elsevier | 2022
    Schlagwörter: Machine learning

    On the interpretability of machine learning methods in crash frequency modeling and crash modification factor development

    Wen, Xiao / Xie, Yuanchang / Jiang, Liming et al. | Elsevier | 2022
    Schlagwörter: Machine learning

    Integrating machine learning into path analysis for quantifying behavioral pathways in bicycle-motor vehicle crashes

    Lu, Weike / Liu, Jun / Fu, Xing et al. | Elsevier | 2022
    Schlagwörter: Machine learning

    A data-centric weak supervised learning for highway traffic incident detection

    Sun, Yixuan / Mallick, Tanwi / Balaprakash, Prasanna et al. | Elsevier | 2022
    Schlagwörter: Data-centric machine 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

    Predicting collision cases at unsignalized intersections using EEG metrics and driving simulator platform

    Zhang, Xinran / Yan, Xuedong | Elsevier | 2022
    Schlagwörter: Machine learning models

    Analysis of mobile phone use engagement during naturalistic driving through explainable imbalanced machine learning

    Ziakopoulos, Apostolos / Kontaxi, Armira / Yannis, George | Elsevier | 2022
    Schlagwörter: Explainable machine learning

    Heterogeneous ensemble learning for enhanced crash forecasts – A frequentist and machine learning based stacking framework

    Ahmad, Numan / Wali, Behram / Khattak, Asad J. | Elsevier | 2022
    Schlagwörter: Machine learning

    Real-time monitoring of work-at-height safety hazards in construction sites using drones and deep learning

    Shanti, Mohammad Z. / Cho, Chung-Suk / de Soto, Borja Garcia et al. | Elsevier | 2022
    Schlagwörter: Machine learning

    Real-time snowy weather detection based on machine vision and vehicle kinematics: A non-parametric data fusion analysis protocol

    Ali, Elhashemi / Khan, Md Nasim / Ahmed, Mohamed M. | Elsevier | 2022
    Schlagwörter: Unsupervised machine learning

    Quantifying and comparing the effects of key risk factors on various types of roadway segment crashes with LightGBM and SHAP

    Wen, Xiao / Xie, Yuanchang / Wu, Lingtao et al. | Elsevier | 2021
    Schlagwörter: Machine learning

    Speed violation analysis of heavy vehicles on highways using spatial analysis and machine learning algorithms

    Kuşkapan, Emre / Çodur, M. Yasin / Atalay, Ahmet | Elsevier | 2021
    Schlagwörter: Machine learning

    Workers’ compensation claim counts and rates by injury event/exposure among state-insured private employers in Ohio, 2007–2017

    Wurzelbacher, Steven J. / Meyers, Alysha R. / Lampl, Michael P. et al. | Elsevier | 2021
    Schlagwörter: Machine learning

    A comparative study of machine learning classifiers for injury severity prediction of crashes involving three-wheeled motorized rickshaw

    Ijaz, Muhammad / lan, Liu / Zahid, Muhammad et al. | Elsevier | 2021
    Schlagwörter: Machine learning (ML)

    A literature review of machine learning algorithms for crash injury severity prediction

    Santos, Kenny / Dias, João P. / Amado, Conceição | Elsevier | 2021
    Schlagwörter: Machine learning

    A hybrid machine learning model for predicting Real-Time secondary crash likelihood

    Li, Pei / Abdel-Aty, Mohamed | Elsevier | 2021
    Schlagwörter: Machine learning

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

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

    Physiological signal-based drowsiness detection using machine learning: Singular and hybrid signal approaches

    Hasan, Md Mahmudul / Watling, Christopher N. / Larue, Grégoire S. | Elsevier | 2021
    Schlagwörter: Machine learning

    A data-driven, kinematic feature-based, near real-time algorithm for injury severity prediction of vehicle occupants

    Wang, Qingfan / Gan, Shun / Chen, Wentao et al. | Elsevier | 2021
    Schlagwörter: Machine-learning algorithms

    Railroad accident analysis using extreme gradient boosting

    Bridgelall, Raj / Tolliver, Denver D. | Elsevier | 2021
    Schlagwörter: Machine learning

    Applying machine learning, text mining, and spatial analysis techniques to develop a highway-railroad grade crossing consolidation model

    Soleimani, Samira / Leitner, Michael / Codjoe, Julius | Elsevier | 2021
    Schlagwörter: Machine learning

    Deriving a joint risk estimate from dynamic data collected at motorcycle rides

    Hula, Andreas / Fürnsinn, Florian / Schwieger, Klemens et al. | Elsevier | 2021
    Schlagwörter: Machine learning

    Vulnerable road users’ crash hotspot identification on multi-lane arterial roads using estimated exposure and considering context classification

    Mahmoud, Nada / Abdel-Aty, Mohamed / Cai, Qing et al. | Elsevier | 2021
    Schlagwörter: Machine learning

    Effectiveness of resampling methods in coping with imbalanced crash data: Crash type analysis and predictive modeling

    Morris, Clint / Yang, Jidong J. | Elsevier | 2021
    Schlagwörter: Machine learning