When mobility on demand meets vehicle electrification: a longitudinal study on evolution of city-scale ridesharing
Author:
Funder
National Science Foundation
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction
Link
https://link.springer.com/content/pdf/10.1007/s42486-023-00125-w.pdf
Reference44 articles.
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3. Bokányi, E., Hannák, A.: Ride-share matching algorithms generate income inequality. arXiv preprint arXiv:1905.12535 (2019)
4. Chaudhari, H.A., Byers, J.W., Terzi, E.: Putting data in the driver’s seat: optimizing earnings for on-demand ride-hailing. In: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining. ACM, pp. 90–98 (2018)
5. Du, B., Tong, Y., Zhou, Z., Tao, Q., Zhou, W.: Demand-aware charger planning for electric vehicle sharing. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. ACM, pp. 1330–1338 (2018)
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