SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations
SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations
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DOI：
10.1145/2783258.2783261
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发表时间：
2015-08
期刊：
影响因子：
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通讯作者：
Shiyou Qian;Jian Cao;Frédéric Le Mouël;Issam Sahel;Minglu Li
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文献类型：
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作者：
Shiyou Qian;Jian Cao;Frédéric Le Mouël;Issam Sahel;Minglu Li
在大多数的路线推荐系统中，为一组相互竞争的出租车司机推荐路线几乎是不受影响的。对于这类问题，推荐公平性和驱动效率是两个基本方面。在本文中，我们提出了SCRAM，一个共享考虑公平出租车路线建议的路线分配机制。SCRAM旨在为一组竞争的出租车司机提供推荐公平性，而不牺牲驾驶效率。通过设计一个简洁的路径分配机制，SCRAM实现了更好的推荐公平竞争的出租车。通过考虑共享路段以避免不必要的竞争，SCRAM在每客户驾驶成本（DCC）方面更有效。我们基于大量的历史出租车轨迹测试SCRAM，并通过广泛的评估来验证SCRAM的推荐公平性和驾驶效率。实验结果表明，SCRAM比三种方法具有更好的推荐公平性和更高的驱动效率。
Recommending routes for a group of competing taxi drivers is almost untouched in most route recommender systems. For this kind of problem, recommendation fairness and driving efficiency are two fundamental aspects. In the paper, we propose SCRAM, a sharing considered route assignment mechanism for fair taxi route recommendations. SCRAM aims to provide recommendation fairness for a group of competing taxi drivers, without sacrificing driving efficiency. By designing a concise route assignment mechanism, SCRAM achieves better recommendation fairness for competing taxis. By considering the sharing of road sections to avoid unnecessary competition, SCRAM is more efficient in terms of driving cost per customer (DCC). We test SCRAM based on a large number of historical taxi trajectories and validate the recommendation fairness and driving efficiency of SCRAM with extensive evaluations. Experimental results show that SCRAM achieves better recommendation fairness and higher driving efficiency than three compared approaches.