Middle Class Urbanism: The Socio-Spatial Transformation of Tehran, 1921–41

Most of the available literature on Tehran between the two world wars deals with the morphological transformation of the city and the role of the Pahlavi state in accomplishing massive urban projects. In contrast, this article focuses on the reciprocal relationship between the sociality and spatiality of the city. It demonstrates how the consolidation of the discourse of modernity resulted in the development of social and political desires for the production of new forms of social life and spaces. The article argues that the formation of the modern middle class and its alignment with the Pahlavi state’s reform projects contributed to a twofold process: first, the decline of the traditional forms of social life and spaces and, second, the production and prevalence of alternative forms. This process resulted in the establishment of social dichotomies with vast spatial manifestations and polarized the city both socially and spatially.     

Modeling Bikeability of Urban Systems

There are characteristics of urban transportation infrastructure that are thought to influence use by bicyclists given their perceived effect on safety, comfort, and efficiency. Prior research has primarily focused on assessing the qualities of individual road segments and analysis of one or a few routes connecting pairs of origins and destinations (ODs). To address these limitations, a multicriterion shortest path framework is proposed for evaluating the characteristics of alternative routes and measuring their tradeoffs with respect to three routing objectives. A label correcting algorithm is described for identifying the complete set of routes optimizing the three objectives and metrics are developed to summarize variations in bikeability within an urban environment. The proposed methods are applied to a case study involving 27,722 urban ODs, yielding 329,931 paths optimal with respect to some combination of the three routing objectives. In particular, 77,418 paths (23.5%) were found to optimize one or more of the three individual routing objectives while 252,513 paths (76.5%) were found to optimize some tradeoff among the three routing objectives. This large number of Pareto‐optimal tradeoff paths underscores the importance of not limiting analysis of routing alternatives to one or two individual objectives.