We study the optimization of large-scale, real-time ridesharing systems and propose a modular design methodology, Component Algorithms for Ridesharing (CAR). We evaluate a diverse set of CARs (14 in total), focusing on the key algorithmic components of ridesharing. We take a multi-objective approach, evaluating 12 metrics related to global efficiency, complexity, passenger, driver, and platform incentives, in settings designed to closely resemble reality in every aspect, focusing on vehicles of capacity two. To the best of our knowledge, this is the largest and most comprehensive evaluation to date. We (i) identify CARs that perform well on global, passenger, driver or platform metrics, (ii) demonstrate that lightweight relocation schemes can significantly improve the Quality of Service by up to $50\%$, and (iii) highlight a practical, scalable, on-device CAR that works well across all metrics.
翻译：我们研究如何优化大规模、实时搭车共享系统,并提议模块设计方法,即“乘车共享的构件算法 ” ( CAR) 。我们评估了一组不同的CAR(共14个,共14个),重点是搭车共享的关键算法组成部分。我们采取了多目标方法,在设计上与每个方面都非常相似的环境下,对12个与全球效率、复杂性、乘客、驾驶员、驾驶员和平台奖励有关的衡量标准进行评估,重点是能力车辆2。据我们所知,这是迄今为止规模最大、最全面的评估。 我们(一) 确定在全球、乘客、驾驶员或平台衡量标准方面表现良好的CAR(共14个), 表明轻重搬迁计划可以显著提高服务的质量,高达50美元。 (三) 突出一个实用、可扩展、跨度的、跨度的CAR(CAR) 。
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