Rethinking Mobility: AI-Based Pricing Systems To Promote Fair Mobility Participation In Cities
(A2025-125944)

AUTHORS

Madeleine Neumann, EBS University; Sarah Selinka, Baden-Wuerttemberg Cooperative State University Stuttgart; Vanessa Reit, Cooperative State University Baden-Württemberg (DHBW Stuttgart); Sinu Thirukketheeswaran, Toulouse School of Management; Marc Kuhn, Baden-Wuerttemberg Cooperative State University Stuttgart

ABSTRACT

The study examines AI's role in pricing shared mobility services and its potential to promote fair mobility in urban areas. Urbanization exacerbates social inequalities, limiting mobility access for disadvantaged groups. AI-driven systems, such as shared autonomous vehicles (SAVs), are seen as solutions for enhancing accessibility and sustainability. This study explores how socio-demographic factors and social constructs like inclusion and participation influence AI pricing. Survey data from 89 German respondents reveals income, number of children, caregiver status, age, and travel purpose significantly impact pricing, while inclusion and participation have no effect. Higher income and age increase prices, while caregiving and more children reduce fares. These findings indicate AI prioritizes demographic data over nuanced social equity measures. Future research will use simulations to refine AI models and assess public acceptance of socially oriented pricing systems.