Autonomous vehicles and residential location choice: a scoping review and analytical framework

A prominent transportation technology that may impact residential relocation patterns in the long-term is autonomous vehicle (AV), also commonly known as driverless car. AVs are expected to impact residential location choice by inducing, for example, changes in accessibility, road capacity, parking demand and travel behaviour. AVs may positively affect accessibility by reducing travel costs, parking costs, and the disutility of travel time compared to conventional human-driven cars. However, reductions in the value of travel time and monetary travel costs may eventually lead to urban sprawl. The impacts of AVs on residential location choice may also vary with the type of AV. The results of modelling studies have shown that the average housing distance to city centre may vary from -4% to 14% for shared autonomous vehicles (SAV), and from 12% to 14% for private autonomous vehicles (PAV). In other words, both AV types may induce urban sprawl in similar magnitudes, however, SAVs have also shown potential to attract residents towards city centres. Research has also shown that parking may be an important mechanism to drive residential relocation in the AV era. For example, housing supply in dense areas may increase by replacing obsolete parking slots, what may reduce housing costs and also attract new residents. In addition, the possibility of empty-cruising may allow higher flexibility for parking outside high-density areas, what may eventually reduce parking costs, and attract new residents to city centres. In other words, the assumption of parking as a fixed cost may no longer be valid with AVs. Thus, it is important to consider changes in parking costs, empty-cruising costs and accessibility in the development of RLC models with AVs. In light of that, this study contributes to the field by (1) undertaking the first review of the literature on residential location choice modelling approaches with AVs; (2) proposing the first analytical framework to guide the assessment and development of state-of-the-art residential location choice models with AVs.

• Record URL:
  https://australasiantransportresearchforum.org.au/papers/2023
• Authors:
  • Pimenta, A
  • Kamruzzaman, M
  • Currie, G
• Conference:
  • Australasian Transport Research Forum (ATRF), 44th, 2023, Perth, Western Australia, Australia
• Publication Date: 2023-11

Media Info

• Pagination: 9p
• Monograph Title: Australasian Transport Research Forum, 2023, 29 November-1 December, Perth, Western Australia

Subject/Index Terms

• TRT Terms: Automated vehicle control; Autonomous vehicles; Land use; Land use planning; Literature reviews; Mathematical models; Parking; Population; Population density; Residential location; Urban areas; Urban development
• ATRI Terms: Autonomous vehicle; Land use; Literature review; Modelling; Parking; Place of residence; Population density; Urban form
• Subject Areas: I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01914543
• Record Type: Publication
• Source Agency: ARRB Group Limited
• Files: ITRD, ATRI
• Created Date: Apr 15 2024 2:19PM