Unraveling the Complex Barriers to and Policies for Shared Autonomous Vehicles: A Strategic Analysis for Sustainable Urban Mobility

Abstract

Integrating shared autonomous vehicles (SAVs) in urban transportation systems holds transformative potential but is accompanied by notable challenges. This study, conducted in Saudi Arabia (KSA), aims to address these challenges by identifying and prioritizing the key barriers and policies that are necessary if we are to successfully adopt SAVs. A comprehensive analysis was performed through a literature review and expert consultations, revealing 24 critical barriers and 10 policies for solving them. The research employed a three-phase methodology to evaluate and rank the policies proposed to overcome these barriers. Initially, the study assessed the specific barriers and policies related to SAVs. Subsequently, the Fuzzy Analytic Hierarchy Process (FAHP) was employed to evaluate the relative importance of these barriers. Finally, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS) was applied to rank the policies; the process identified government-backed investment, urban planning integration, and funding for research and development in sensor and hardware technologies as the most effective policies. The study underscores the importance of targeted policies in addressing technical and infrastructural challenges. Emphasizing system reliability, cybersecurity, and effective integration of SAVs into urban planning, the findings advocate for robust government support and continued technological innovation. These insights offer a roadmap for policymakers and industry leaders in the KSA to foster a more sustainable and resilient urban transportation future.

Keywords

• shared autonomous vehicles (SAVs)
• barriers
• sensors
• policies
• FAHP
• F-TOPSIS