Adaptive Occupant Experience and Concurrency Management in Fully Autonomous Robotaxi Services

Authors

Ronak Indrasinh Kosamia

Abstract

Recent progress in fully autonomous vehicles—often referred to as robotaxis—has spurred the deployment of ride-hailing services without human drivers. This shift, while revolutionizing mobility, raises new questions about occupant experience, concurrency in multi-passenger scenarios, and ensuring safety in the absence of a dedicated driver. This paper presents a framework for adaptive occupant experience and concurrency management, emphasizing occupant detection, seat assignment, resource allocation, and automated conflict resolution. By merging onboard inference with microservice-based aggregator modules, our approach handles occupant classification, occupant-based personalization, and environment-aware route planning in real time. We adopt ephemeral occupant data storage to safeguard privacy, discarding raw sensor inputs immediately after local inference. Preliminary evaluations suggest that occupant-based concurrency can reduce disputes and enhance passenger comfort in multi-rider robotaxis, while maintaining minimal overhead on embedded hardware. By offering occupant seat assignment, dynamic UI modules, and remote operator escalation for rare conflicts, the system paves a path toward occupant-centric, globally scalable driverless fleets. We conclude that occupant concurrency logic, integrated with environment triggers and aggregator synergy, can transform fully autonomous ride-hailing from a purely technological achievement to a safe, user-friendly experience accessible worldwide.

Keywords

Adaptive Occupant Experience and Concurrency Management in Fully Autonomous Robotaxi Services. Ronak Indrasinh Kosamia. 2021. IJIRCT, Volume 7, Issue 5. Pages 1-31. https://www.ijirct.org/viewPaper.php?paperId=2503059