Optimizing Dallas-Fort Worth Bus Transportation System Using Any Logic

The bus transportation system, modeled using the AnyLogic simulation software, aims to optimize the flow of buses and manage key operational challenges such as bus bunching and delays. The simulation incorporates various elements, including bus agents, bus stops, and passenger behaviors, with a focus on how buses interact with each other and with passengers at different stops. The system is designed to simulate real-world bus routes, taking into account factors like bus speed, intervals, dwell times, and passenger load. By adjusting bus schedules and frequencies, the simulation tests different scenarios to identify strategies that minimize wait times, reduce delays, and improve service efficiency. This paper explores the optimization of bus transportation systems in the Dallas-Fort Worth area, focusing on addressing the challenge of bus bunching and improving overall service efficiency. Using the AnyLogic simulation tool, the study models the dynamics of bus operations, including factors such as bus intervals, dwell times, and passenger load variations during rush and normal hours. By adjusting bus schedules and service frequencies, the paper evaluates multiple optimization scenarios to identify strategies that reduce passenger wait times, minimize delays, and enhance system efficiency. The results demonstrate that strategically reducing bus intervals during peak hours and extending them during non peak hours can significantly improve operational performance, with service efficiency increasing from 75% to 88% under optimal conditions. The findings highlight the importance of tailoring bus schedules to passenger demand and time-of-day factors to mitigate issues like bus bunching and ensure more reliable public transportation services.

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Publication Details

Journal
Journal of Sensors, IoT & Health Sciences (JSIHS).
Published
2024-12-31
DOI
https://doi.org/10.69996/jsihs.2024020
Citations
5
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
3.42
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article

Optimizing Dallas-Fort Worth Bus Transportation System Using Any Logic

Srinivasa Sai Abhijit Challapalli
5 citations
Journal of Sensors, IoT & Health Sciences (JSIHS).
Transportation Planning and Optimization
3.42
article

Optimizing Dallas-Fort Worth Bus Transportation System Using Any Logic

Srinivasa Sai Abhijit Challapalli
article en
5 citations

Abstract

The bus transportation system, modeled using the AnyLogic simulation software, aims to optimize the flow of buses and manage key operational challenges such as bus bunching and delays. The simulation incorporates various elements, including bus agents, bus stops, and passenger behaviors, with a focus on how buses interact with each other and with passengers at different stops. The system is designed to simulate real-world bus routes, taking into account factors like bus speed, intervals, dwell times, and passenger load. By adjusting bus schedules and frequencies, the simulation tests different scenarios to identify strategies that minimize wait times, reduce delays, and improve service efficiency. This paper explores the optimization of bus transportation systems in the Dallas-Fort Worth area, focusing on addressing the challenge of bus bunching and improving overall service efficiency. Using the AnyLogic simulation tool, the study models the dynamics of bus operations, including factors such as bus intervals, dwell times, and passenger load variations during rush and normal hours. By adjusting bus schedules and service frequencies, the paper evaluates multiple optimization scenarios to identify strategies that reduce passenger wait times, minimize delays, and enhance system efficiency. The results demonstrate that strategically reducing bus intervals during peak hours and extending them during non peak hours can significantly improve operational performance, with service efficiency increasing from 75% to 88% under optimal conditions. The findings highlight the importance of tailoring bus schedules to passenger demand and time-of-day factors to mitigate issues like bus bunching and ensure more reliable public transportation services.

Journal of Sensors, IoT & Health Sciences (JSIHS).Vol. 2(4)
The University of Texas at Arlington (US)
Openalex Percentile: Top 8%
Transportation Planning and Optimization
3.42
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Optimizing Dallas-Fort Worth Bus Transportation System Using Any Logic — Srinivasa Sai Abhijit Challapalli · Journal of Sensors, IoT & Health Sciences (JSIHS). (2024) | TGRS Research Map | TGRS