24 citations · 62 across the 4 of their papers we have counts for
5 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…
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…