This paper proposes a fuzzy logic model for assessing the mobility of road transport networks from a network perspective. Two mobility attributes are introduced to account for the physical connectivity and road transport network level of service. The relative importance of the two mobility attributes has been established through the fuzzy inference reasoning procedure that was implemented to estimate a single mobility indicator. The advantage of quantifying two mobility attributes is that it improves the ability of the mobility indicator developed to assess the level of mobility under different types of disruptive events.
A case study of real traffic data from seven British cities shows a strong correlation between the proposed mobility indicator and the Geo distance per minute, demonstrating the applicability of the proposed fuzzy logic model. The second case study of a synthetic road transport network for Delft city illustrates the ability of the proposed network mobility indicator to reflect variation in the demand side (i.e. departure rate) and supply side (i.e. network capacity and link closure). Overall, the proposed mobility indicator offers a new tool for decision makers in understanding the dynamic nature of mobility under various disruptive events.
|Number of pages||13|
|Journal||Expert Systems with Applications|
|Publication status||Published - 1 Jun 2015|
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Rawia El Rashidy
- Department of Engineering and Technology - Senior Research Fellow
- School of Computing and Engineering
- Institute of Railway Research - Member