Papers
1
Total Citations
13
H-Index
1
About
Meiling Li is a rising researcher in intelligent vehicular systems, with a focus on high-resolution localization and cooperative sensing. Her key research areas include vehicular positioning, channel-based simultaneous localization and mapping (SLAM), and multi-agent reflective mapping. Li’s most notable contribution is the development of Team Channel-SLAM, a pioneering framework that enables a fleet of independent vehicles to collaboratively achieve precise localization by exploiting common environmental reflectors. This approach transforms neighboring vehicles into cooperative agents, significantly enhancing tracking accuracy without relying on expensive infrastructure. Her seminal 2022 paper, "Joint Vehicular Localization and Reflective Mapping Based on Team Channel-SLAM," has garnered 13 citations, establishing a foundation for cost-effective, high-resolution positioning in autonomous driving. Li’s work bridges the gap between individual vehicle sensing and swarm intelligence, offering a scalable solution for dynamic urban environments. By redefining how vehicles share and interpret spatial data, she is advancing the next generation of cooperative autonomous systems. Her research holds promise for safer, more efficient transportation networks, making her a key voice in the evolution of connected and automated mobility.
Research Focus
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Top Papers
- 1