Short-term passenger volume forecast and model analysis of Beijing public transport

2021 ◽  
Author(s):  
Xiangyu Li ◽  
Manman Xie
Keyword(s):  
Public Transport ◽  
Model Analysis ◽  
Short Term ◽  
Passenger Volume

scholarly journals Analysis of Approaches to Short Term Passenger Volume Prediction in Public Transport

2015 ◽  
Vol 131 (10) ◽  
pp. 34-38
Author(s):  
Abhijeet Shingade ◽  
Adesh Atole ◽  
Piyush Galphat ◽  
Shashank Dharmadhikari ◽  
Bhushan Thakare
Keyword(s):  
Public Transport ◽  
Short Term ◽  
Passenger Volume

scholarly journals Characterization of COVID-19’s Impact on Mobility and Short-Term Prediction of Public Transport Demand in a Mid-Size City in Spain

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6574
Author(s):  
Ana Belén Rodríguez González ◽  
Mark R. Wilby ◽  
Juan José Vinagre Díaz ◽  
Rubén Fernández Pozo
Keyword(s):  
Public Transport ◽  
High Performance ◽  
Monitoring Network ◽  
Traffic Monitoring ◽  
Health Economy ◽  
Accurate Information ◽  
Short Term ◽  
Public And Private ◽  
The Impact

COVID-19 has dramatically struck each section of our society: health, economy, employment, and mobility. This work presents a data-driven characterization of the impact of COVID-19 pandemic on public and private mobility in a mid-size city in Spain (Fuenlabrada). Our analysis used real data collected from the public transport smart card system and a Bluetooth traffic monitoring network, from February to September 2020, thus covering relevant phases of the pandemic. Our results show that, at the peak of the pandemic, public and private mobility dramatically decreased to 95% and 86% of their pre-COVID-19 values, after which the latter experienced a faster recovery. In addition, our analysis of daily patterns evidenced a clear change in the behavior of users towards mobility during the different phases of the pandemic. Based on these findings, we developed short-term predictors of future public transport demand to provide operators and mobility managers with accurate information to optimize their service and avoid crowded areas. Our prediction model achieved a high performance for pre- and post-state-of-alarm phases. Consequently, this work contributes to enlarging the knowledge about the impact of pandemic on mobility, providing a deep analysis about how it affected each transport mode in a mid-size city.

scholarly journals Short-Term Forecasting of Off-Street Parking Occupancy

2021 ◽  
pp. 036119812110363
Author(s):  
Elisabeth S. Fokker ◽  
Thomas Koch ◽  
Marco van Leeuwen ◽  
Elenna R. Dugundji
Keyword(s):  
Information And Communication Technologies ◽  
Public Transport ◽  
Short Term Memory ◽  
Sunshine Duration ◽  
Influential Factors ◽  
Time Variability ◽  
Weather Variables ◽  
Short Term ◽  
Average Wind Speed ◽  
The Impact

Information and communication technologies have opened the way to guide recent developments in the field of parking. In this paper these technologies are applied to model a decision support system that gives insight into 6-months ahead parking occupancy forecasts for 57 off-street parking locations in Amsterdam. An effect analysis was conducted into the influence of weather-, event-, parking tariff-, and public transport attributes on parking occupancy. The most influential factors on the parking occupancy were the scheduling of artistic and sports events, the addition of a public transport line, and the weather variables thunderstorm, average wind speed, temperature, precipitation, and sunshine duration. Parking tariffs did not significantly contribute to model performance, which could have been because of the lack of data and time variability in the parking tariffs of the examined parking locations. The forecasting algorithms compared were the seasonal naive model as a benchmark approach, the Box–Jenkins seasonal autoregressive integrated moving average with and without exogenous regressors (SARIMAX and SARIMA, respectively), exponential smoothing models, and the long short-term memory neural network. The SARIMAX model outperformed the other algorithms for the 6-months ahead forecasts according to the lowest root mean square error (RMSE). By including the event factor, the model improved by 24% based on the RMSE. Weather variables improved the predictive performance by 8%. Future studies could focus on the addition of more event variables, extension into an online model, and the impact of spatial–temporal features on parking occupancy.

Investigating the development and interaction of bus-metro based on Lotka–Volterra models: Evidence from seven central cities in China

2021 ◽  
pp. 2150207
Author(s):  
Xinyu Liang ◽  
Xianghai Meng
Keyword(s):  
Public Transport ◽  
Logistic Model ◽  
Volterra Model ◽  
Volume Data ◽  
Central Cities ◽  
Guangzhou City ◽  
Nanjing City ◽  
Passenger Volume ◽  
Shanghai City ◽  
Transport Modes

Bus and metro are the two most important public transport modes in many metropolises in China, and they both have experienced rapid growth and meanwhile coexisted for decades. However, little is known on how the metro and bus interacted with each other during their rapid growths. This study was proposed to investigate the growth and interaction of bus-metro from the macro perspective. The passenger volume data for metro and bus were collected from seven central cities to represent the development of the two public transport modes, and the Logistic model and Lotka–Volterra model were employed to model the growth as well as the interaction of bus-metro, respectively. The modeling results show that the development of bus conforms to the Logistic model (i.e. S-shaped curve), while the bus-metro interaction conforms to the Lotka–Volterra model with interaction modes of competition (Shanghai city from 2000–2009, Shanghai city from 2009–2018, Guangzhou city from 2009–2017, Nanjing city from 2008–2018), and mutualism (Guangzhou city from 2000–2009). The further analysis indicates that urban characteristics and policies determine the interaction, and the parameters of the Lotka–Volterra model could be used to judge the bus-metro interaction type.

Research on the Public Transport Integration of Major Western Region Cities – A Case Study on Bus Connection with Subway Line 6 in Chonqing

2012 ◽  
Vol 610-613 ◽  
pp. 3809-3813
Author(s):  
Ling Hong Wei ◽  
Hong Yang Wu ◽  
Huan Li
Keyword(s):  
Public Transport ◽  
Network Optimization ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Theoretical Foundation ◽  
Optimization Theory ◽  
The Public ◽  
Urban Public Transport ◽  
Passenger Volume

The major western cities of China are beginning to suffer the growing traffic congestion problems, which eastern cities of China has experienced. Learn lessons from eastern cities on traffic issues as soon as possible, dealing with the diversified modes of public transportation problem of convergence effectively, providing condition for integration development of urban public transport in the west is the main goal in this paper. This paper takes Subway transit Line 6 in Chongqing as a bus connection example. On the basis of passenger volume forecast, integrated public transport optimization theory and method are used to study Chongqing subway transit Line 6 along the feeder site optimization program , it can provide the theoretical foundation and technical support for the public transport network optimization of Chongqing.

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