C
Cheng-Jie Jin
Researcher at Southeast University
Publications - 32
Citations - 425
Cheng-Jie Jin is an academic researcher from Southeast University. The author has contributed to research in topics: Traffic flow & Flow (mathematics). The author has an hindex of 10, co-authored 26 publications receiving 298 citations. Previous affiliations of Cheng-Jie Jin include Delft University of Technology.
Papers
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Journal ArticleDOI
Experimental and empirical investigations of traffic flow instability
Rui Jiang,Rui Jiang,Cheng-Jie Jin,H.M. Zhang,H.M. Zhang,Yong-Xian Huang,Junfang Tian,Wei Wang,Mao-Bin Hu,Hao Wang,Bin Jia +10 more
TL;DR: In this paper, the authors have carried out a large scale experiment to study the car-following behavior in a 51-car platoon and found that there exists a critical speed between 30 and 40 km/h, above which the standard deviation of car velocity is almost saturated (flat) along the platoon.
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The influence of nonmonotonic synchronized flow branch in a cellular automaton traffic flow model
Cheng-Jie Jin,Wei Wang +1 more
TL;DR: The congested patterns upstream of an isolated on-ramp in a cellular automaton traffic flow model, proposed in the previous paper, are studied to help understand more about the outflow of wide moving jams or bottlenecks.
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Understanding the structure of hyper-congested traffic from empirical and experimental evidences
TL;DR: It is found that traffic states inside hypercongestion are not homogeneous, which contradicts the existence of a “Homogeneous Congested Traffic” state claimed in two-phase traffic theory.
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Observational characteristics of pedestrian flows under high-density conditions based on controlled experiments
TL;DR: In this paper, a 1.5m-wide ring corridor and a single-file circular track were used to study pedestrian flow dynamics under high-density conditions, where the authors examined global densities as high as 9 ped/m2 and found that the unidirectional and bidirectional flow rates were nearly the same.
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Discretionary lane-changing behavior: empirical validation for one realistic rule-based model
TL;DR: It is found that the classical lane-changing rules of rule-based model cannot explain many cases in the empirical dataset, so one new decision rule is proposed, comparing the position after a time horizon of several seconds without a lane-change.