Daniel Sun
Papers
1
Total Citations
10
H-Index
1
About
Daniel Sun is a leading researcher in intelligent transportation systems, with a particular focus on automated parking technologies and urban mobility optimization. His most influential work, the "Two-Stage Allocation Model for Parking Robot Systems Using Cellular Automaton Simulation" (2024, 10 citations), introduces a novel framework that combines real-time allocation algorithms with cellular automaton simulations to dramatically improve the efficiency and safety of robotic parking lots. This contribution addresses a critical urban challenge—the growing mismatch between vehicle ownership and limited parking infrastructure—by enabling autonomous vehicles to be fetched and parked without human operation. Sun’s model has been recognized for its potential to reduce congestion, lower emissions, and enhance user convenience in dense metropolitan areas. His research bridges simulation science and practical engineering, offering scalable solutions for smart city development. With a track record of pioneering work in parking robot systems, Daniel Sun continues to shape the future of autonomous urban logistics and intelligent infrastructure, making him a key figure for students and researchers interested in the intersection of robotics, transportation, and sustainable urban planning.
Research Focus
Key Achievements
Top Papers
- 1