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1–20 von 314 Ergebnissen
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    Large-Scale Freeway Traffic Flow Estimation Using Crowdsourced Data: A Case Study in Arizona

    Cottam, Adrian / Li, Xiaofeng / Ma, Xiaobo et al. | ASCE | 2024
    Schlagwörter: Machine learning

    Predicting passenger satisfaction in public transportation using machine learning models

    Ruiz, Elkin / Yushimito, Wilfredo F. / Aburto, Luis et al. | Elsevier | 2024
    Schlagwörter: Machine learning

    SHapley Additive exPlanations for Explaining Artificial Neural Network Based Mode Choice Models

    Koushik, Anil / Manoj, M. / Nezamuddin, N. | Springer Verlag | 2024
    Schlagwörter: Deep learning , Machine learning

    Exploring the contributions of Ebike ownership, transit access, and the built environment to car ownership in a developing city

    Sun, Shan / Guo, Liang / Yang, Shuo et al. | Elsevier | 2024
    Schlagwörter: Machine learning

    In-store shopping trip predictions and impact factors during COVID-19 emergencies

    Imran, Md Ashraful / Hyun, Kate | Taylor & Francis Verlag | 2024
    Schlagwörter: machine learning

    Analyzing multi-factor effects on travel well-being, including non-linear relationship and interaction

    Yu, Hongmei / Ye, Xiaofei / Liu, Lining et al. | Taylor & Francis Verlag | 2024
    Schlagwörter: machine learning

    Applying a Bayesian network for modelling the shift from motorcycle to public transport use in Vietnam

    Nguyen, Son-Tung / Moeinaddini, Mehdi / Saadi, Ismaïl et al. | Elsevier | 2024
    Schlagwörter: Network-learning

    Travel behavior and system dynamics in a simple gamified automated multimodal network

    Collins, Mor / Etzioni, Shelly / Ben-Elia, Eran | Elsevier | 2024
    Schlagwörter: Reinforced Learning

    Expressway Traffic Incident Detection Using a Deep Learning Approach Based on Spatiotemporal Features with Multilevel Fusion

    Qu, Qikai / Shen, Yongjun / Yang, Miaomiao et al. | ASCE | 2024
    Schlagwörter: Deep learning

    Detecting anomalous commuting patterns: Mismatch between urban land attractiveness and commuting activities

    Tong, Zhaomin / Zhang, Ziyi / An, Rui et al. | Elsevier | 2024
    Schlagwörter: Machine learning model

    What Lies behind Idle Connection Time in Fast-Charging Public Stations: Evidence from Changshu, China

    Zhou, Xizhen / Ding, Xueqi / Ji, Yanjie | ASCE | 2024
    Schlagwörter: Machine learning

    DeepAD: An integrated decision-making framework for intelligent autonomous driving

    Shi, Yunyang / Liu, Jinghan / Liu, Chengqi et al. | Elsevier | 2024
    Schlagwörter: Deep reinforcement learning

    Built environment influences commute mode choice in a global south megacity context: Insights from explainable machine learning approach

    Ashik, F.R. / Sreezon, A.I.Z. / Rahman, M.H. et al. | Elsevier | 2024
    Schlagwörter: Machine learning

    Urban network geofencing with dynamic speed limit policy via deep reinforcement learning

    Lu, Wenqi / Yi, Ziwei / Gidofalvi, Gyözö et al. | Elsevier | 2024
    Schlagwörter: Reinforcement learning technology

    Real-Time Optimization of Urban Rail Transit Train Scheduling via Advantage Actor–Critic Deep Reinforcement Learning

    Wen, Longhui / Zhou, Wei / Liu, Jiajun et al. | ASCE | 2024
    Schlagwörter: Deep reinforcement learning

    Application of machine learning models to predict driver left turn destination lane choice behavior at urban intersections

    Freier Zugriff
    Mohammed Moinuddin / Logan Proffer / Matthew Vechione et al. | DOAJ | 2024
    Schlagwörter: Applied Machine Learning

    Unsupervised Approach to Investigate Urban Traffic Crashes Based on Crash Unit, Crash Severity, and Manner of Collision

    Maniei, Farzin / Mattingly, Stephen P. | ASCE | 2024
    Schlagwörter: Unsupervised learning

    A state-of-the-art survey of deep learning models for automated pavement crack segmentation

    Freier Zugriff
    Hongren Gong / Liming Liu / Haimei Liang et al. | DOAJ | 2024
    Schlagwörter: Deep learning