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Title: BTE-Sim: Fast Simulation Environment For Public Transportation
The public commute is essential to all urban centers and is an efficient and environment-friendly way to travel. Transit systems must become more accessible and user-friendly. Since public transit is majorly designed statically, with very few improvements coming over time, it can get stagnated, unable to update itself with changing population trends. To better understand transportation demands and make them more usable, efficient, and demographic-focused, we propose a fast, multi-layered transit simulation that primarily focuses on public transit simulation (BTE-Sim). BTE-Sim is designed based on the population demand, existing traffic conditions, and the road networks that exist in a region. The system is versatile, with the ability to run different configurations of the existing transit routes, or inculcate any new changes that may seem necessary, or even in extreme cases, new transit network design as well. In all situations, it can compare multiple transit networks and provide evaluation metrics for them. It provides detailed data on each transit vehicle, the trips it performs, its on-time performance and other necessary factors. Its highlighting feature is the considerably low computation time it requires to perform all these tasks and provide consistently reliable results.  more » « less
Award ID(s):
1952011
PAR ID:
10466149
Author(s) / Creator(s):
; ; ; ; ; ;
Date Published:
Journal Name:
2022 IEEE International Conference on Big Data (Big Data)
Page Range / eLocation ID:
2886 to 2894
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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