Exploring the effectiveness of bus rapid transit a prototype agent-based model of commuting behavior

2011 ◽  
Vol 18 (6) ◽  
pp. 825-835 ◽  
Author(s):  
Simon McDonnell ◽  
Moira Zellner
Keyword(s):  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Agent Based Model ◽  
Agent Based

Using agent based modeling to assess the effect of increased Bus Rapid Transit system infrastructure on walking for transportation

2016 ◽  
Vol 88 ◽  
pp. 39-45 ◽  
Author(s):  
Pablo D. Lemoine ◽  
Juan Manuel Cordovez ◽  
Juan Manuel Zambrano ◽  
Olga L. Sarmiento ◽  
Jose D. Meisel ◽  
...  
Keyword(s):  
Agent Based Modeling ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Transit System ◽  
Agent Based ◽  
Walking For Transportation

A data-driven agent-based model of congestion and scaling dynamics of rapid transit systems

2015 ◽  
Vol 10 ◽  
pp. 338-350 ◽  
Author(s):  
Nasri Bin Othman ◽  
Erika Fille Legara ◽  
Vicknesh Selvam ◽  
Christopher Monterola
Keyword(s):  
Data Driven ◽  
Rapid Transit ◽  
Agent Based Model ◽  
Transit Systems ◽  
Agent Based

Simulations of an Agent-Based Model that Consists of a Large Number of Agents Moving Stochastically in a Wide Bounded Domain

2001 ◽  
Author(s):  
Minoru Tabata ◽  
Akira Ide ◽  
Nobuoki Eshima ◽  
Kyushu Takagi ◽  
Yasuhiro Takei ◽  
...  
Keyword(s):  
Bounded Domain ◽  
Agent Based Model ◽  
Agent Based

Game Model of the Route Selection for Bus Rapid Transit

CICTP 2017 ◽  
2018 ◽  
Author(s):  
Hua-Wei Gong ◽  
Wen-Zhou Jin ◽  
Xiao-Dong Zang ◽  
Qiang Luo
Keyword(s):  
Bus Rapid Transit ◽  
Game Model ◽  
Route Selection ◽  
Rapid Transit ◽  
Selection For

Modeling Interstation Travel Speed of Hybrid Bus Rapid Transit within A Bayesian Framework

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Ji-hua Hu ◽  
Jia-xian Liang
Keyword(s):  
Road Traffic ◽  
Travel Speed ◽  
Bayesian Framework ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Important Indicator ◽  
Main Road ◽  
Traffic Lights ◽  
Speed Distribution ◽  
Hybrid Bus

Interstation travel speed is an important indicator of the running state of hybrid Bus Rapid Transit and passenger experience. Due to the influence of road traffic, traffic lights and other factors, the interstation travel speeds are often some kind of multi-peak and it is difficult to use a single distribution to model them. In this paper, a Gaussian mixture model charactizing the interstation travel speed of hybrid BRT under a Bayesian framework is established. The parameters of the model are inferred using the Reversible-Jump Markov Chain Monte Carlo approach (RJMCMC), including the number of model components and the weight, mean and variance of each component. Then the model is applied to Guangzhou BRT, a kind of hybrid BRT. From the results, it can be observed that the model can very effectively describe the heterogeneous speed data among different inter-stations, and provide richer information usually not available from the traditional models, and the model also produces an excellent fit to each multimodal speed distribution curve of the inter-stations. The causes of different speed distribution can be identified through investigating the Internet map of GBRT, they are big road traffic and long traffic lights respectively, which always contribute to a main road crossing. So, the BRT lane should be elevated through the main road to decrease the complexity of the running state.

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