Abstract
Baltimore's transportation system mainly relies on walking and buses, with researchers aiming to improve these by optimizing bus routes and sidewalk facilities. However, costs and traffic congestion remain concerns, especially after the collapse of the Francis Scott Key Bridge, which exacerbated congestion and affected travel time, freight costs, and supply chains. For Task1: To address these issues, researchers built a hypernetwork model for a multimodal transportation system considering transfer relationships. This model analyzes traveler behavior, defines feasible paths, and establishes cost functions, providing a comprehensive perspective for decision makers to identify bottlenecks, optimize resources, and promote sustainable development during bridge reconstruction, ensuring smoother transitions and minimizing disruptions. For Task2: The researchers conducted a cost analysis, studying travel time, emissions, and energy consumption for different modes of transportation. They employed a multimodal transportation network flow allocation model and sensitivity analysis to solve programming problems, aiding in quantifying the project's impact on stakeholders and providing a robust scientific basis for decision making. For Task3: Based on these analyses, the researchers proposed various measures to improve the transportation network, including setting up low-emission zones, promoting new travel modes, and reducing private car entry. They also suggested supportive measures such as strengthening parking facilities, implementing differentiated fees, optimizing traffic layout, and integrating public and shared travel options. Additionally, they proposed long-term development plans, policy guarantees, and encouraged public participation to create a green and efficient travel environment. Overall, this research report comprehensively evaluates the potential impact of optimizing bus routes and sidewalk facilities in Baltimore, proposing a range of measures and long-term plans to foster an efficient, environmentally friendly, and sustainable transportation system that caters to the city's current and future needs.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 9th International Conference on Cloud, Big Data and Communication Systems, ICCBDCS 2025 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 85-92 |
| Number of pages | 8 |
| ISBN (Electronic) | 9798331591748 |
| DOIs | |
| State | Published - 2025 |
| Externally published | Yes |
| Event | 9th International Conference on Cloud, Big Data and Communication Systems, ICCBDCS 2025 - Manchester, United Kingdom Duration: 14 Aug 2025 → 16 Aug 2025 |
Publication series
| Name | Proceedings - 9th International Conference on Cloud, Big Data and Communication Systems, ICCBDCS 2025 |
|---|
Conference
| Conference | 9th International Conference on Cloud, Big Data and Communication Systems, ICCBDCS 2025 |
|---|---|
| Country/Territory | United Kingdom |
| City | Manchester |
| Period | 14/08/25 → 16/08/25 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- bi-level programming model
- multimodal transportation system
- random user equilibrium allocation model
- system optimization
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