4.6 Article

Fuzzy modelling of static system optimum traffic assignment problem having multi origin-destination pair

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SOCIO-ECONOMIC PLANNING SCIENCES
卷 77, 期 -, 页码 -

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.seps.2021.101024

关键词

SOTAP; BPR function; Triangular fuzzy numbers; Fuzzy QPP

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Traffic congestion is an unavoidable issue in transportation networks, leading to negative impacts on traffic safety, time wastage, traffic delays, and costs. Traffic assignment plays a crucial role in improving traffic management, safety, time efficiency, and cost effectiveness. The System Optimum Traffic Assignment Problem (SOTAP) aims to minimize total system travel time and adhere to flow conservation constraints, with the possibility of using fuzzy parameters for a more realistic model.
Traffic congestion is an unpreventable problem to avoid in a transportation network and it has negative effects on traffic accident, time wasting, traffic delay and safety problem. Besides, in transportation networks, drivers do not want to deal with traffic jam while traversing between specified origin-destination pair. Therefore, traffic assignment (TA) is imperative to improve traffic management, transportation safety, time, and cost savings. System Optimum Traffic Assignment Problem (SOTAP) is a kind of TA model which aims to minimize the total system travel time on the network, and satisfies the flow conservation constraints. To model the SOTAP more realistically, the imprecise parameters can be taken as fuzzy. Therefore, in this paper, we focus on converting the conventional SOTAP to a fuzzy quadratic programming problem (QPP) which is named System Optimum Fuzzy Traffic Assignment Problem (SOFTAP). Here, link travel time is expressed with BPR function as generally used in the literature by converting to fuzzy except link-dependent parameters. Thus, the nonlinear objective function of SOFTAP is expressed in terms of fuzzy link flows and fuzzy link travel times. A solution approach from the literature is modified to the reconstructed SOFTAP.

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