Development of an efficient driving strategy for connected and automated vehicles at signalized intersections: A reinforcement learning approach
The concept of Connected and Automated Vehicles (CAVs) enables instant traffic
information to be shared among vehicle networks. With this newly proposed concept, a …
information to be shared among vehicle networks. With this newly proposed concept, a …
Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach
It has been well recognized that human driver's limits, heterogeneity, and selfishness
substantially compromise the performance of our urban transport systems. In recent years, in …
substantially compromise the performance of our urban transport systems. In recent years, in …
A joint service migration and mobility optimization approach for vehicular edge computing
The vehicular edge computing is considered an enabling technology for intelligent and
connected vehicles since the optimization of communication and computing on edge has a …
connected vehicles since the optimization of communication and computing on edge has a …
A bibliometric analysis and review on reinforcement learning for transportation applications
Transportation is the backbone of the economy and urban development. Improving the
efficiency, sustainability, resilience, and intelligence of transportation systems is critical and …
efficiency, sustainability, resilience, and intelligence of transportation systems is critical and …
SLAM algorithm analysis of mobile robot based on lidar
Z Xuexi, L Guokun, F Genping… - 2019 Chinese …, 2019 - ieeexplore.ieee.org
In this work, we tested Simultaneous localization and mapping (SLAM) about mobile robots
in indoor environment, where all experiments were conducted based on the Robot …
in indoor environment, where all experiments were conducted based on the Robot …
Context-aware road travel time estimation by coupled tensor decomposition based on trajectory data
Urban road travel time estimation and prediction on a citywide scale is a necessary and
important task for recommending optimal travel paths. However, this problem has not yet …
important task for recommending optimal travel paths. However, this problem has not yet …
Dynamic trajectory planning and tracking for autonomous vehicle with obstacle avoidance based on model predictive control
S Li, Z Li, Z Yu, B Zhang, N Zhang - Ieee Access, 2019 - ieeexplore.ieee.org
In this study, an obstacle avoidance controller based on nonlinear model predictive control
is designed in autonomous vehicle navigation. The reference trajectory is predefined using …
is designed in autonomous vehicle navigation. The reference trajectory is predefined using …
Learning physical human–robot interaction with coupled cooperative primitives for a lower exoskeleton
Human-powered lower exoskeletons have received considerable interests from both
academia and industry over the past decades, and encountered increasing applications in …
academia and industry over the past decades, and encountered increasing applications in …
A novel GRU-RNN network model for dynamic path planning of mobile robot
J Yuan, H Wang, C Lin, D Liu, D Yu - IEEE Access, 2019 - ieeexplore.ieee.org
A dynamic path planning method based on a gated recurrent unit-recurrent neural network
model is proposed for the problem of path planning of a mobile robot in an unknown space …
model is proposed for the problem of path planning of a mobile robot in an unknown space …
Using reinforcement learning to minimize the probability of delay occurrence in transportation
Reducing traffic delay is of crucial importance for the development of sustainable
transportation systems, which is a challenging task in the studies of stochastic shortest path …
transportation systems, which is a challenging task in the studies of stochastic shortest path …