Mode Choice Effect on the Number of En-route Travelers and Arrival Rates in an Urban Transport Network | ||||
SVU-International Journal of Engineering Sciences and Applications | ||||
Volume 5, Issue 2, December 2024, Page 100-108 PDF (401.95 K) | ||||
Document Type: Original research articles | ||||
DOI: 10.21608/svusrc.2024.268541.1185 | ||||
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Authors | ||||
Seham Hemdan1; Elsayed A. A. Abulela ![]() | ||||
1Civil Engineering Department Faculty of Engineering, Aswan University, Aswan 81542, Egypt. | ||||
2Civil Engineering Department Faculty of Engineering, South Valley University, Qena 83523, Egypt. | ||||
Abstract | ||||
Traffic congestion is a challenge facing urban network users and traffic managers worldwide. Although there have been several previous studies conducted to investigate the association between travelers’ choices and congestion levels in multimodal transport networks, the effect of mode choice on the number of en-route travelers and the travelers’ arrival rates is still largely unknown. Increasing numbers of en-route travelers indicates traffic congestion existence in the network and the efficiency of transportation systems improves as more travelers arrive at their destination. The objective of this paper is to analyze the effects of various mode choice scenarios on the number of travelers staying en-route and arriving at their destination throughout the day in the Sweden national network. To achieve this objective, the multi-agent transport simulation (MATSim) is used as a simulation framework. Specifically, three mode choice scenarios were simulated including a base case to serve as a reference group and 10%, and 30% of agents allowed to change their travel mode. Overall, results revealed that the mode choice flexibility reduced the number of en-route travelers by 44.3% and 37.1%, and the number of travelers reached their destinations has increased by 12.6% and 36.4% for the morning and evening peaks, respectively. The reduced number of travelers still en-route and the increased arrival rates indicate a significant reduction in congestion levels at the network level. | ||||
Keywords | ||||
Agent-based Modeling; MATSim; Mode Share Ratio; Traffic Congestion; Travel Choices | ||||
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