R
Renxin Zhong
Researcher at Sun Yat-sen University
Publications - 66
Citations - 1405
Renxin Zhong is an academic researcher from Sun Yat-sen University. The author has contributed to research in topics: Cell Transmission Model & Computer science. The author has an hindex of 16, co-authored 56 publications receiving 1026 citations. Previous affiliations of Renxin Zhong include Hong Kong Polytechnic University & The Chinese University of Hong Kong.
Papers
More filters
Journal ArticleDOI
Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment
TL;DR: Both the numerical simulation results and the empirical results confirm that the SCTM is capable of accurately estimating the means and SDs of the freeway densities as compared to the MCS.
Journal ArticleDOI
Short-Term Traffic State Prediction Based on Temporal–Spatial Correlation
TL;DR: The SCTM framework is extended to consider the spatial-temporal correlation of traffic flow and to support short-term traffic state prediction and the covariance structure calibrated from the spatial correlation analysis for probabilistic traffic state evaluation is incorporated.
Journal ArticleDOI
Delay-dependent robust control of descriptor systems with time delay
Renxin Zhong,Zhi Yang +1 more
TL;DR: In this paper, the problem of stability and robust control for both certain and uncertain continuous-time singular systems with state delay is considered, and robust delay-dependent stability criteria and linear memoryless state feedback controllers based on linear matrix inequality are obtained.
Journal ArticleDOI
Multi-objective optimal control formulations for bus service reliability with traffic signals
TL;DR: The optimality conditions of multi-objective control formulations are derived and an open loop solution algorithm is presented and found that the model is capable of regulating bus service reliability through utilising traffic signals while managing delays induced to surrounding traffic.
Journal ArticleDOI
Modeling the impacts of mandatory and discretionary lane-changing maneuvers
TL;DR: In this article, a mesoscopic multilane model is proposed to enable simultaneous simulation of mandatory and discretionary lane-changing behaviors to realistically capture multi-lane traffic dynamics, and the model considers lane specific fundamental diagrams to simulate dynamic heterogeneous lane flow distributions on expressways.