Αποτελέσματα Αναζήτησης
27 Μαρ 2023 · This research introduces an innovative, AI-based, data-driven methodology for predicting bus arrival times at various transit points (stations), offering a collective prediction for all bus lines within large metropolitan areas.
4 Μαρ 2024 · This research introduces an innovative, AI-based, data-driven methodology for predicting bus arrival times at various transit points (stations), offering a collective prediction for all bus lines within large metropolitan areas.
12 Απρ 2023 · Xu and Ying developed a data-driven prediction method for bus arrival time using real-time bus trajectories created by 1000 vehicles for two months. The required data, i.e., traffic flows, are collected from GPS equipment.
28 Ιουν 2017 · We build a bus arrival time prediction system by using real-world trajectory dataset generated by 1000 buses in a period of 2 months. Experiments show that our method can predict more accurate arrival time with less online computation than competing methods.
In this paper, we compare and evaluate a realtime bus arrival prediction system for short-distance (< 1km) bus stops using real time and publicly available online information, including bus location, weather, traffic status and passenger flow.
3 Σεπ 2020 · In this paper, we seek to predict the occurrence of arrival time irregularities by mining GPS coordinates of transit buses provided by the Toronto Transit Commission (TTC) along with hourly weather data and using this data in machine learning models that we have developed.
12 Μαρ 2021 · Thus, this study used an RNN to predict the arrival time of a bus. A route of a bus has 30–40 bus stations in general. Arrival time prediction includes the time prediction of each station along the way from the starting to the finishing stop, the arrival times at subsequent stations, and the arrival time of the nearest vehicle to a station.
