Z
Zhe Zeng
Researcher at China University of Petroleum
Publications - 14
Citations - 326
Zhe Zeng is an academic researcher from China University of Petroleum. The author has contributed to research in topics: Computer science & Hierarchical database model. The author has an hindex of 7, co-authored 10 publications receiving 247 citations. Previous affiliations of Zhe Zeng include Wuhan University & Chinese Ministry of Education.
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Journal ArticleDOI
Dynamic accessibility mapping using floating car data: a network-constrained density estimation approach
Qingquan Li,Qingquan Li,Tong Zhang,Tong Zhang,Handong Wang,Handong Wang,Zhe Zeng,Zhe Zeng,Zhe Zeng +8 more
TL;DR: A novel integrated access measure to compute accessibility to Points of Interest (POIs) constrained by road networks based on real-time travel speeds that are derived from floating car data (FCD) is introduced.
Journal ArticleDOI
Path-finding through flexible hierarchical road networks: An experiential approach using taxi trajectory data
TL;DR: A new experiential approach that computes optimal paths based on the experience of taxi drivers by mining a huge number of floating car trajectories is presented, demonstrating that experientially optimal paths can be flexibly obtained in different time intervals, particularly during peak hours.
Proceedings ArticleDOI
Hierarchical route planning based on taxi GPS-trajectories
TL;DR: Hierarchical travel experience information of road network is given by statistical analysis on a large amount of taxi GPS trajectories and shows that the route results according to the experiential information approach to optimal results more than that according to static information ofRoad network.
Journal ArticleDOI
Quantifying multi-modal public transit accessibility for large metropolitan areas: a time-dependent reliability modeling approach
TL;DR: A multi-modal transit accessibility modeling approach is proposed to account for realistic variations in travel time and service reliability in Shenzhen (China), where transit services exhibit significant travel time variations over space and time.
Journal ArticleDOI
Curvedness feature constrained map matching for low-frequency probe vehicle data
TL;DR: Using real-world probe vehicles data, it is shown that the curvedness feature (CURF) constrained map matching method outperforms two classical methods for accuracy and stability under complicated road environments.