Qiangqiang Guo
Control and Systems Engineering · 2019
A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Control and Systems Engineering — 24 citations into it
- Transportation — 21 citations into it
- Building and Construction — 16 citations into it
- Automotive Engineering — 7 citations into it
Whom Qiangqiang Guo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Pitu B. Mirchandani
- Marcello Montanino
- Paolo Massioni
- Raffaello D'Andrea
- Jianhua Guo
- Xiaolei Ma
- Yongcan Cao
- Jennie Lioris
- Yisheng Lv
- Fredrik K. Gustafsson
Papers from Qiangqiang Guo's perspective
Ordered by how strongly the researchers Qiangqiang Guo trusts endorse each paper. Same corpus, a different order for every researcher.
- Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory
- Traffic Flow Prediction With Big Data: A Deep Learning Approach (IEEE transactions on intelligent transportation systems (Print))
- Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings - eScholarship
- A REAL-TIME TRAFFIC SIGNAL CONTROL SYSTEM: ARCHITECTURE, ALGORITHMS, AND ANALYSIS
- Adaptive Kalman filter approach for stochastic short-term traffic flow rate prediction and uncertainty quantification
- An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination
- Virtual trip lines for distributed privacy-preserving traffic monitoring (ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services)
- Particle filters for positioning, navigation, and tracking (IEEE Transactions on Signal Processing)
- Parallel Control and Management for Intelligent Transportation Systems: Concepts, Architectures, and Applications (IEEE transactions on intelligent transportation systems (Print))
- Stochastic programming model for oversaturated intersection signal timing
Their papers
- Urban traffic signal control with connected and automated vehicles: A survey (2019) — 432 citations