IntroductionHigh-density housing is heralded as a foremost smart-growth instrument apt to reduce land consumption and automobile dependence (American Planning Association, 1998;Holtzclaw, 1994; Local Government Commission, 2003). But on its own it has little effect on journey patterns. To modify travel behaviour, density must be associated with a walking-conducive layout, proximity to quality public-transit services, nearby concentrations of diversified activities, and attitudes and socioeconomic attributes which are conducive to public-transit use and walking.In this paper we have two objectives. First, we evaluate the impact of highresidential-density distribution on modal shares, bearing in mind that many of the policies guiding this distribution in the metropolitan region under investigation were intended to raise public-transit use and walking levels. Our second objective is to draw lessons from past density-distribution policies, which can be conducive to an elevated reliance on public transit and walking. In this paper we adhere to the smart-growth perspective. The work is part of efforts to find ways of reducing dependence on the car and thus lessen traffic congestion, improving air quality, lowering households' transportation expenditures, and providing nonautomobile-oriented lifestyle options. In this paper we explore the feasibility of a car-use reduction strategy that entails minimal infringement of individuals' freedom of choiceöthe juxtaposition of high residential density and high-quality public-transit services.The empirical focus is on policies related to residential density adopted over the last five decades in the Toronto metropolitan region, an urban area long known for its public-transit orientation and metropolitan-wide planning capacity. Toronto is well suited for an examination of obstacles hampering a coordination of high residential density and high-quality public-transit services. Over the last fifty years, density-related policies have not elevated modal shares of walking and public-transit use as much as
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