Planning sustainable cities: Coordinating accessibility improvements with housing policies

Abstract

Emerging mobility services (such as mobility-on-demand and micromobility) have expanded the range of travel options available to individuals and offered ways to improve access to various opportunities. Unlike mass transit services, emerging mobilities can be implemented and experimented with rather rapidly. As a result, they are also likely to induce relatively rapid changes in travel behavior and location choices. Several cities across the world are experimenting with ‘car-lite’ policies that aim to reduce auto ownership and use (and emissions) with the help of emerging mobilities, transit improvements, and/or urban design. Therefore, it becomes important to understand the near-term effects of emerging mobilities on neighborhoods through the lenses of vehicle ownership and residential location choice over the first few years of change. This is especially important given the gentrification patterns we have observed in neighborhoods where transit improvements or extensions have been implemented (often referred to as ‘transit-induced gentrification’). Will we observe similar patterns of accessibility-induced gentrification with emerging mobilities as well? If so, how can we, as planners, seek to mitigate these undesirable but consequential side-effects of car-lite policies?

In my dissertation, I introduced necessary methodological extensions to a state-of-the-art land use-transport interaction (LUTI) model that can enable better modeling of the interdependencies between various choices and tradeoffs of housing and mobility. Applying this improved LUTI model to the city-state of Singapore, I conducted quasi-static analyses and agent-based microsimulations of `what-if' scenarios regarding how households react to accessibility changes. In addition to looking at neighborhood-level car-lite pilot programs that improve non-auto accessibility, I also explored vehicle restriction policies that seek to ban private vehicles.

I found that private vehicle restrictions alone without complementary non-auto accessibility improvements can reduce accessibility and social welfare, even in a transit-rich place like Singapore. Solely imposing a blanket ban on private automobiles to accelerate the transition to a sustainable mobility future will likely do more harm than good. Evidence of accessibility-induced gentrification, to varying degrees, was found in all of the Singaporean neighborhoods I explored. Lower-income and less auto-dependent neighborhoods seem to be more prone to accessibility-induced gentrification, thereby suggesting that non-accessibility improvements alone may not guarantee equitable outcomes. I then explored two housing policies – upzoning and parking restrictions – as possible strategies to mitigate the gentrification side-effects. Both policies appeared to have limited value by themselves because, at times, they could accelerate gentrification or reduce social welfare. However, they became much more effective policy instruments when combined with affordability constraints (such as income restrictions and price discounts), so that the accessibility and welfare benefits of car-lite policies could be equitably distributed across residents. I also tested the generalizability and transferability of my findings through various sensitivity analyses, robustness checks, and implementation in a more auto-dependent context separate from Singapore.

This dissertation is expected to contribute to our understanding of the effects of emerging mobilities on three fronts. From a conceptual perspective, this study can demonstrate how emerging mobilities can lead to inequitable urban development in the absence of carefully designed market regulations. From a policy perspective, we can learn about the effectiveness of some housing and mobility policies in mitigating these undesirable outcomes while enhancing targeted outcomes. From a methodological perspective, the study contributes to the creation of a state-of-the-art integrated urban model that can be used to explore near-term market dynamics in reaction to new transportation technologies.