The increasing interest in sustainable development has underlined the importance of accessibility as a key indicator to assess transport investments, urban policy, and urban form. From both the environmental and the equity component of sustainability, a comparison of accessibility by car versus public transport is of utmost importance. However, most studies in this direction have used rather rough estimates of travel time, especially by public transport. In this paper, we present Urban.Access, an ArcGIS extension for estimating car-based and transit-based accessibility to employment and other land uses. Urban.Access enables a detailed representation of travel times by transit and car and thus makes it possible to adequately compare accessibility levels by transport mode. The application of Urban.Access to the Tel Aviv metropolitan area shows that the gaps between car-based and transit-based accessibility are larger than those found in other studies. We argue that this is not the result of a poorer transit system, but rather of a more detailed description of travel by transit in the Urban.Access application. The larger gaps point to a greater need for adequate policy responses, both for reducing car dependence as well as for creating a more equitable

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Transportation planning is changing. What used to be a concern with motorized vehicles only is evolving into a discipline dealing with multimodal systems where priority is given to transit and nonmotorized means of transport, chief among them being walking. The city of Bat Yam in Israel has chosen to pioneer planning for pedestrians as an integral component of its transportation master plan. This article presents a novel use of pedestrian movement modeling within urban transportation planning, by means of pedestrian movement volume prediction maps for the city, both at its current state today and at its future state planned for the year 2030. The study shows that a pedestrian movement distribution can be explained mainly by the spatial variables that represent properties of a street network. Changes to this network structure are relatively rare, and, therefore, pedestrian movement will not change in a fundamental way in the future. Furthermore, by overlaying the models for pedestrian movement and motorized traffic, as well as the underlying public transit and bicycle networks, focus can be on those streets and places where conflicts among the various road users (i.e., pedestrians, bicycles, transit vehicles, and private cars) are expected.

Most pedestrian movement volume models were constructed for urban areas that developed on the basis of pre-modern planning. In this paper, we confront neighborhoods that were built upon modern planning doctrines, combining the functional hierarchy of streets with the neighborhood unit concept, with neighborhoods that developed from pre-modem non-hierarchical street-based planning. We use space syntax analysis to investigate how their street network's structural attributes interact with pedestrian movement distribution. The investigation was conducted in 14 neighborhoods from 4 cities in Israel by examining the correlation of observed pedestrian volume with models using different axial-and segment-based topological, angular, and metric syntactic attributes across different radii (scales). The results indicate that the street network and the distribution of pedestrian movement interact differently in the two neighborhood types. In pre-modern neighborhoods: (i) there is significantly more walking; (ii) the street network's syntactic attributes tend to be much more consistent in their correlation with pedestrian volume across all scales; (iii) the correlation of pedestrian volume with these attributes and with commerce is relatively high; and (iv) pedestrian movement distribution is more predictable. We relate these differences to the absence of a self-organized circular causality between street network structure, commerce, and movement in modern planned neighborhoods.