Allocation problems are major issues in managing On-Demand Transport (ODT) systems. They have been studied for decades, and a variety of solutions were proposed. The approaches to these problems can be classified as centralized and decentralized. Each has its pros and cons in practice. In this work, we aim to provide a generic model for the problem of online on-demand transport (ODT) with autonomous vehicles and a multi-agent model dedicated to resource allocation and scheduling in vehicle fleets. This generic model supports the processing of different allocation mechanisms and considers autonomous vehicles that communicate via peer-to-peer radio channels to meet passenger requirements and satisfy trip requests in an online ODT system. We validate this model's genericity by applying several allocation mechanisms (mathematical programming, greedy heuristic, distributed constraint optimization, and auctions) and compare their performance on synthetic scenarios in a real-world city map.