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Ride and Hide: A Study on the Privacy of Ride Hailing Services
2019 IEEE Vehicular Networking Conference (VNC), 2019The rise of ride-hailing services (RHSs) is transforming our mobility. More and more people rely on such services on daily basis. In such services, users reveal their precise locations of origin and destination of desired trips to the service providers (SPs). Often, these locations are considered personally identifiable and further represent (sensitive)
Ala'a Al-Momani +2 more
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Blockchain-Enabled Ride-Hailing Services
2019Ride-hailing services (RHSs) have been developing in the past decade, given the proliferation of sharing economy and the increasing connectivity. RHSs are now serving users (including riders and drivers) worldwide every day. RHSs enable users to upload their ride requests and responses to an RHS platform, and then establish rides through mobile ...
Liehuang Zhu, Keke Gai, Meng Li
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The strategic analysis of service mode selection for a ride‐hailing platform
International Transactions in Operational Research, 2023AbstractThis paper examines the service mode selection strategy of a ride‐hailing platform and analyzes the impact of the strategy on consumers and drivers. The platform has three service modes to select from, including Mode L (only low‐quality services), Mode H (only high‐quality services), and Mode HL (high‐ and low‐quality services).
Dongliang Guo +2 more
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How long will the Service Time in a Ride-Hailing Service?
2020 The 3rd International Conference on Machine Learning and Machine Intelligence, 2020With the rapid development of mobile applications, the ride-hailing services such as Uber in America and Didi-taxi in China have been very popular all over the world as they provide convenience to the users. A key factor that makes the ride-hailing service successful is the user experience, which is highly related to the passenger service time.
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Digitalization of Ride-Hailing Services
What measures should be taken to effectively address the negative effects of the digitalization of ride-hailing services? Let's ponder some thoughts!! Findings validate that the digitalization of ride-hailing services remains a threat to environmental sustainability.Meenakshi Bose, Swarnendu Mazumder
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Intent-Aware Audience Targeting for Ride-Hailing Service
2019As the market for ride-hailing service is increasing dramatically, an efficient audience targeting system (which aims to identify a group of recipients for a particular message) for ride-hailing services is demanding for marketing campaigns. In this paper, we describe the details of our deployed system for intent-aware audience targeting on Baidu Maps ...
Yuan Xia +7 more
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A Privacy-Preserving Order Dispatch Scheme for Ride-Hailing Services
2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), 2019The ride-hailing system has become popular around the world. The Service Providers (SPs) such as Uber and Didi dispatch passenger orders based on their location information. However, one concern from the public is whether the SPs could protect the location privacy of passengers. In this paper, we propose an order dispatch scheme that could preserve the
Yubin Duan +3 more
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Predicting Ride-Hailing Service Demand via RPA-LSTM
IEEE Transactions on Vehicular Technology, 2019Ride hailing is a representative practice of rapidly developing sharing economy, which not only brings people convenience on mobility, but also benefits the utilization of vehicular resources. For ride-hailing service providers, it is necessary to supervise the demands of customers so that they could carry out reasonable dispatches.
Kun Niu +3 more
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A Consumer Compensation System in Ride-hailing Service
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023Zhe Yu 0001 +4 more
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Hotspots Recommender: Spatio-Temporal Prediction of Ride-Hailing and Taxicab Services
2022The complexity of predicting hotspot areas for taxicab services has recently increased with the popularity of ride-hailing services such as Uber and Lyft. In this paper, we first reveal that passengers in certain areas prefer ride-hailing services over taxicab services at certain times, and propose an enhanced LSTM model for predicting the hotspots ...
Huan Huang, Basem Suleiman, Waheeb Yaqub
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