With the increase in the number of all megacities and large cities, urban traffic has become an important issue in urban life. Urban traffic accidents are occurring more and more frequently, which has a negative impact on the economy and safety. The existing research shows that sunlight intensity or rainy days can increase the probability of accidents in urban traffic. This paper proposes multiple machine learning methods to compare the accuracy of different machine learning algorithms for New York traffic accident prediction on weather data from 2015 to 2020. The experimental results show that both OVR and OVO methods have high accuracy except for the lower accuracy in 2020.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Urban traffic accident prediction research based on meteorological data


    Contributors:


    Publication date :

    2022-02-01


    Size :

    1222530 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Urban expressway traffic accident meteorological factor sensitivity analysis method

    WANG JIANJUN / LU XIAOJUAN / WANG SAI et al. | European Patent Office | 2021

    Free access

    Traffic accident rate prediction method based on space-time meteorological grid

    CHEN YUNQIANG / LU JUN / YANG HONG et al. | European Patent Office | 2021

    Free access

    Research on Traffic Safety Accident Prediction Based on ARIMA

    Wei, Ziyi / Wang, Kefeng / Gao, Jinhai | Springer Verlag | 2024

    Free access

    Research Progress on Road Traffic Accident Prediction Based on Big Data Methods

    Zhao, Zhenzhong / Zhou, Dan / Wang, Wenyu et al. | Springer Verlag | 2024


    Prediction system for traffic accident

    BACK JU YONG | European Patent Office | 2019

    Free access