Cost-based analysis of autonomous mobility services

TLDR

Rapid advances in autonomous driving raise questions about operational models, with cost‑competitiveness being a key determinant of viability. The study accounts for higher cleaning costs and effort that could shift the cost balance. Public transport remains economically competitive in bundled‑demand settings, especially in dense urban areas, whereas shared and pooled vehicles are more efficient when bundling is limited, yet shared fleets may not be optimal and many vehicles may stay privately owned due to low variable costs and accepted high fixed costs.

Abstract

Fast advances in autonomous driving technology trigger the question of suitable operational models for future autonomous vehicles. A key determinant of such operational models' viability is the competitiveness of their cost structures. Using a comprehensive analysis of the respective cost structures, this research shows that public transportation (in its current form) will only remain economically competitive where demand can be bundled to larger units. In particular, this applies to dense urban areas, where public transportation can be offered at lower prices than autonomous taxis (even if pooled) and private cars. Wherever substantial bundling is not possible, shared and pooled vehicles serve travel demand more efficiently. Yet, in contrast to current wisdom, shared fleets may not be the most efficient alternative. Higher costs and more effort for vehicle cleaning could change the equation. Moreover, the results suggest that a substantial share of vehicles may remain in private possession and use due to their low variable costs. Even more than today, high fixed costs of private vehicles will continue to be accepted, given the various benefits of a private mobility robot.