SCRAM

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Open Access
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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.
Funding Information
  • Research Fund of Future Network of Jiangsu Province (BY2013095-2-04)
  • Rhône-Alpes Region, France
  • CIP program of Morgan Stanley
  • China National Science Foundation (61272438,61472253)
  • Research Funds of Science and Technology Commission of Shanghai Municipality (14511107702, 12511502704)