Experience: Large-scale Cellular Localization for Pickup Position Recommendation at Black-hole
Conference
Zhu, S, Li, L, Wang, X et al. (2023). Experience: Large-scale Cellular Localization for Pickup Position Recommendation at Black-hole
. 1270-1284. 10.1145/3570361.3613298
Zhu, S, Li, L, Wang, X et al. (2023). Experience: Large-scale Cellular Localization for Pickup Position Recommendation at Black-hole
. 1270-1284. 10.1145/3570361.3613298
Location awareness is the basis for enabling pickup service at ride-hailing platforms. In contrast to the almost pervasive coverage outdoors, indoor localization availability is still sporadic in industry since it largely relies on RF signatures from certain IT infrastructure, e.g., WiFi access points. Based on our 2-year observations at DiDi ride-hailing platform in China, there are 68k orders everyday created at black-hole, i.e., where only cellular signals exist. In this paper, we present the design, development, and deployment of TransparentLoc, a large-scale cellular localization system for pickup position recommendation, and share our 2-year experience with 50 million orders across 13 million devices in 4541 cities to address practical challenges including sparse cell towers, unbalanced user fingerprints, and temporal variations. Our system outperforms the iOS built-in cellular localization system in terms of four major service metrics, regardless of environmental changes, smartphone brands/models, time, and cellular providers.
