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Forecasting Public Transport Ridership: Management of Information Systems using CNN and LSTM Architectures

Procedia Computer Science, 2021
This research paper provides a framework for the e ffi cient representation and analysis of both spatial and temporal dimensions of panel data. This is achieved by representing the data as spatio-temporal image-matrix, and applied to a case study on ...
Sergey Khalil, C. Amrit, Thomas Koch, E. Dugundji   +3 more
semanticscholar   +3 more sources

Smart Metro: Deep Learning Approaches to Forecasting the MRT Line 3 Ridership [PDF]

International Journal of Computing Sciences Research, 2023
Since its establishment in 1999, the Metro Rail Transit Line 3 (MRT3) has served as a transportation option for numerous passengers in Metro Manila, Philippines.
Jayrald Empino, Jean Allyson Junsay, Mary Grace Verzon, Mideth B. Abisado, Shekinah Lor B. Huyo-a, Gabriel Avelino R. Sampedro   +5 more
semanticscholar   +4 more sources

Forecasting bus ridership using a “Blended Approach” [PDF]

Transportation, 2019
As sources of “Big Data” continue to grow, transportation planners and researchers seek to utilize these new resources. Given the current dependency on traditional transportation data sources and conventional tools (e.g., spreadsheets and propriety ...
C. Lawson, A. Muro, E. Krans
semanticscholar   +3 more sources

Enhancing MRT purple line offset project through forecasting ridership using the direct demand ridership model

Journal of Infrastructure, Policy and Development
The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan.
Kamonchanok Wangvittaya, Dahye Yang, Hyemin Park   +2 more
semanticscholar   +2 more sources

Research on the Metro Ridership Forecasting based on ARIMA Model

Transactions on Computer Science and Intelligent Systems Research
With the increasing coverage of subways in cities, people travel more than just by bus or walking. Nowadays, subway stations have become sites with high population density in the city. Due to the increasing travel demand of residents.
ShiRu Lyu
semanticscholar   +2 more sources

A comparison of time series methods for post-COVID transit ridership forecasting

Journal of Public Transportation
Transit agencies conduct system-level ridership forecasting for planning, budgeting, and other administrative purposes. However, the COVID-19 pandemic introduced substantial changes in transit ridership levels and seasonal patterns, which has impacted the performance of ridership forecasting.
Ashley Hightower, A. Ziedan, Jing Guo, Xiaojuan Zhu, C. Brakewood   +4 more
semanticscholar   +3 more sources

Forecasting of Short-Term Metro Ridership with Support Vector Machine Online Model

Journal of Advanced Transportation, 2018
Forecasting for short-term ridership is the foundation of metro operation and management. A prediction model is necessary to seize the weekly periodicity and nonlinearity characteristics of short-term ridership in real-time. First, this research captures
Xuemei Wang, Ning Zhang, Yunlong Zhang, Zhuangbin Shi   +3 more
semanticscholar   +3 more sources

Medium-term public transit route ridership forecasting: What, how and why? A case study in Lyon

, 2021
Demand forecasting is an essential task in many industries and the transportation sector is no exception. In fact, accurate prediction of future demand is an essential components of intelligent transportation systems [Vlahogianni et al., 2014 ...
Oscar Egu, P. Bonnel
semanticscholar   +1 more source

Mass Rapid Transit Ridership Forecast Based on Direct Ridership Models: A Case Study in Wuhan, China

Journal of Advanced Transportation, 2020
Many large cities rely on Mass Rapid Transit (MRT) to increase passenger mobility. For efficiency, MRT stations should be arranged to attract maximal number of travelers. It is therefore important to develop methods for estimating MRT ridership forecasting models, which are important for policies on land use development or new MRT lines.
Ruili Guo, Zhengdong Huang
openaire   +2 more sources

Integrating geographic information systems into transit ridership forecast models

Journal of Advanced Transportation, 1995
AbstractResearchers have produced sophisticated modal split and transit demand models, including forecasts that are sensitive to the level of service. However, little effort has been made to integrate these models into corridor studies and route alignment analyses since (a) re‐routing is itself an extremely complex modeling task, and (b) the results of
Kamal T. Azar, Joseph Ferreira
openaire   +1 more source