Analysis and Modeling the impact of Road Network Typology on the Macroscopic Fundamental Diagram
| dc.contributor.advisor | Yonas Minalu (PhD) | |
| dc.contributor.author | Tilaneh Tesfahun | |
| dc.date.accessioned | 2024-08-27T11:59:00Z | |
| dc.date.available | 2024-08-27T11:59:00Z | |
| dc.date.issued | 2024-06 | |
| dc.description.abstract | The population and traffic in cities increased consistently due to the increase in urbanization, economic growth, and increased welfare. This trend necessitates changes in city road network structure in order to satisfy the growing travel demand. This research investigates the relationship between road network typology and the macroscopic fundamental diagram (MFD) in Addis Ababa city road network. The macroscopic fundamental diagram (MFD) refers to the relationship between density, flow, and speed at the network level. The macroscopic fundamental diagram is important in the field of transportation and urban planning. By illustrating the relationship between travel speeds, traffic flow rates, and vehicle density in an urban setting, it gives a macro-level understanding of how urban transportation networks work. The objective of the study is to understand how different road network typologies affect the overall traffic flow and the macroscopic fundamental diagram. Sixty-one 2km by 2km road networks extracted from OpenStreetMap were analyzed using simulation of urban mobility (SUMO) with consistent Origin-Destination (OD) data. The study used geographic information system (GIS) software to gather road network typological data (i.e. road network connectivity indexes, network density, primary road proportion, and trafficable area). Whereas, the maximum flow data were extracted from a simulation of urban mobility output. An exponential regression model was developed to assess the impact of network typological factors on the MFD. The regression model yielded significant results, with an adjusted R square value close to one, indicating a strong correlation between network characteristics and macroscopic traffic flow dynamics. Factors such as alpha, degree centrality, primary length proportion, and network density were found to be statistically significant in influencing the aggregated maximum flow. The study aims to provide insights into how road network characteristics influence macroscopic traffic flow dynamics, aiding in the optimization of transportation systems and urban planning strategies. The findings will offer valuable information for urban planners and decision-makers to enhance transportation efficiency and network design in Addis Ababa City. The research highlights the importance of understanding MFD for optimizing transportation systems and suggests a shift towards holistic urban traffic management strategies based on macroscopic variables for sustainable urban development. | |
| dc.identifier.uri | https://etd.aau.edu.et/handle/123456789/3401 | |
| dc.language.iso | en_US | |
| dc.publisher | Addis Ababa University | |
| dc.subject | Aggregated maximum flow | |
| dc.subject | GIS | |
| dc.subject | City structure | |
| dc.subject | Road network typology | |
| dc.subject | Macroscopic fundamental diagram | |
| dc.subject | Simulation of urban mobility | |
| dc.subject | Transportation efficiency | |
| dc.subject | Urban planners. | |
| dc.title | Analysis and Modeling the impact of Road Network Typology on the Macroscopic Fundamental Diagram | |
| dc.type | Thesis |