Putting Ridesharing to the Test: Efficient and Scalable Solutions and the Power of Dynamic Vehicle Relocation
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Ridesharing is a coordination problem in its core. Traditionally it has been solved in a centralized manner by ridesharing platforms. Yet, to truly allow for scalable solutions, we needs to shift from traditional approaches, to multi-agent systems, ideally run on-device. In this paper, we show that a recently proposed heuristic (ALMA), which exhibits such properties, offers an efficient, end-to-end solution for the ridesharing problem. Moreover, by utilizing simple relocation schemes we significantly improve QoS metrics, by up to 50 To demonstrate the latter, we perform a systematic evaluation of a diverse set of algorithms for the ridesharing problem, which is, to the best of our knowledge, one of the largest and most comprehensive to date. Our evaluation setting is specifically designed to resemble reality as closely as possible. In particular, we evaluate 12 different algorithms over 12 metrics related to global efficiency, complexity, passenger, driver, and platform incentives.
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