47 citations · 126 across the 9 of their papers we have counts for
9 papers
Tactical Decision Making for Emergency Vehicles Based on A Combinational Learning Method
Haoyi Niu, Jianming Hu, Zheyu Cui +1
Increasing the response time of emergency vehicles(EVs) could lead to an immeasurable loss of property and life. On this account, tactical decision making for EVs' microscopic cont…
Tensor-based Cooperative Control for Large Scale Multi-intersection Traffic Signal Using Deep Reinforcement Learning and Imitation Learning
Yusen Huo, Qinghua Tao, Jianming Hu
Traffic signal control has long been considered as a critical topic in intelligent transportation systems. Most existing learning methods mainly focus on isolated intersections and…
Cooperative Lane Changing via Deep Reinforcement Learning
Guan Wang, Jianming Hu, Zhiheng Li +1
In this paper, we study how to learn an appropriate lane changing strategy for autonomous vehicles by using deep reinforcement learning. We show that the reward of the system shoul…
Person Re-Identification by Unsupervised Video Matching
Xiaolong Ma, Xiatian Zhu, Shaogang Gong +4
Most existing person re-identification (ReID) methods rely only on the spatial appearance information from either one or multiple person images, whilst ignore the space-time cues r…
Global optimization framework for real-time route guidance via variable message sign
Bai Liu, Ke Han, Jianming Hu
Variable message sign (VMS) is an effective traffic management tool for congestion mitigation. The VMS is primarily used as a means of providing factual travel information or genui…
A New Car-Following Model Inspired by Galton Board
Fa Wang, Li Li, Xuexiang Jin +3
Different from previous models based on scatter theory and random matrix theory, a new interpretation of the observed log-normal type time-headway distribution of vehicles is prese…
Fluctuations and Pseudo Long Range Dependence in Network Flows: A Non-Stationary Poisson Process Model
Yudong Chen, Li Li, Yi Zhang +1
In the study of complex networks (systems), the scaling phenomenon of flow fluctuations refers to a certain power-law between the mean flux (activity) of the th node and…
A Markov Process Inspired Cellular Automata Model of Road Traffic
Fa Wang, Li Li, Jianming Hu +6
To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of…
Response to Comments on PCA Based Hurst Exponent Estimator for fBm Signals Under Disturbances
Li Li
In this response, we try to give a repair to our previous proof for PCA Based Hurst Exponent Estimator for fBm Signals by using orthogonal projection. Moreover, we answer the quest…