Two-sided mobility platforms, such as Uber and Lyft, widely emerged in the urban mobility landscape, bringing disruptive changes to transportation systems worldwide. This calls for a simulation framework where researchers from various and across disciplines may introduce models aimed at representing the dynamics of platform-driven urban mobility systems. In this work, we present MaaSSim, an agent-based simulator reproducing the transport system used by two kind of agents: (i) travellers, requesting to travel from their origin to destination at a given time, and (ii) drivers supplying their travel needs by offering them rides. An intermediate agent, the platform, allows demand to be matched with supply. Agents are decision makers, specifically, travellers may decide which mode they use or reject an incoming offer. Similarly, drivers may opt-out from the system or reject incoming requests. All of the above behaviours are modelled through user-defined modules, representing agents' taste variations (heterogeneity), their previous experiences (learning) and available information (system control). MaaSSim is an open-source library available at a public repository github.com/RafalKucharskiPK/MaaSSim, along with a set of tutorials and reproducible use-case scenarios.

中文翻译：

---

MaaSSim-基于代理的双向移动平台模拟器

双向出行平台，例如Uber和Lyft，在城市出行领域中广泛出现，给全世界的交通运输系统带来了颠覆性的变化。这需要一个模拟框架，来自各个领域的研究人员可以引入旨在表示平台驱动的城市出行系统动态的模型。在这项工作中，我们介绍MaaSSim，这是一种基于代理的模拟器，可重现两种代理所使用的运输系统：（i）旅行者，要求在给定时间从其出发地到达目的地，以及（ii）提供他们的旅行的驾驶员通过为他们提供游乐设施的需求。中间代理平台可以使需求与供应相匹配。代理商是决策者，具体地说，旅行者可以决定他们使用或拒绝收到的报价的方式。同样，驱动程序可能会选择退出系统或拒绝传入的请求。所有上述行为都是通过用户定义的模块进行建模的，这些模块代表代理商的口味变化（异质性），他们以前的经历（学习）和可用信息（系统控制）。MaaSSim是一个开放源代码库，可在公共资源库github.com/RafalKucharskiPK/MaaSSim上获得，以及一组教程和可复制的用例场景。