SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations

Abstract : 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.
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Shiyou Qian, Jian Cao, Frédéric Le Mouël, Issam Sahel, Minglu Li. SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations. Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2015), Aug 2015, Sydney, Australia. ⟨10.1145/2783258.2783261⟩. ⟨hal-01180500⟩

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