Recent advances in reinforcement learning for traffic signal control: A survey of models and evaluation
Traffic signal control is an important and challenging real-world problem that has recently
received a large amount of interest from both transportation and computer science …
received a large amount of interest from both transportation and computer science …
[HTML][HTML] Leveraging reinforcement learning for dynamic traffic control: A survey and challenges for field implementation
In recent years, the advancement of artificial intelligence techniques has led to significant
interest in reinforcement learning (RL) within the traffic and transportation community …
interest in reinforcement learning (RL) within the traffic and transportation community …
Transfer learning in deep reinforcement learning: A survey
Reinforcement learning is a learning paradigm for solving sequential decision-making
problems. Recent years have witnessed remarkable progress in reinforcement learning …
problems. Recent years have witnessed remarkable progress in reinforcement learning …
Deep reinforcement learning for intelligent transportation systems: A survey
Latest technological improvements increased the quality of transportation. New data-driven
approaches bring out a new research direction for all control-based systems, eg, in …
approaches bring out a new research direction for all control-based systems, eg, in …
An introduction to deep reinforcement learning
Deep reinforcement learning is the combination of reinforcement learning (RL) and deep
learning. This field of research has been able to solve a wide range of complex …
learning. This field of research has been able to solve a wide range of complex …
Big data analytics in intelligent transportation systems: A survey
Big data is becoming a research focus in intelligent transportation systems (ITS), which can
be seen in many projects around the world. Intelligent transportation systems will produce a …
be seen in many projects around the world. Intelligent transportation systems will produce a …
Intellilight: A reinforcement learning approach for intelligent traffic light control
The intelligent traffic light control is critical for an efficient transportation system. While
existing traffic lights are mostly operated by hand-crafted rules, an intelligent traffic light …
existing traffic lights are mostly operated by hand-crafted rules, an intelligent traffic light …
A deep reinforcement learning network for traffic light cycle control
Existing inefficient traffic light cycle control causes numerous problems, such as long delay
and waste of energy. To improve efficiency, taking real-time traffic information as an input …
and waste of energy. To improve efficiency, taking real-time traffic information as an input …
Presslight: Learning max pressure control to coordinate traffic signals in arterial network
Traffic signal control is essential for transportation efficiency in road networks. It has been a
challenging problem because of the complexity in traffic dynamics. Conventional …
challenging problem because of the complexity in traffic dynamics. Conventional …
Internet of things connected wireless sensor networks for smart cities
Abstract The Smart City is the most complete and covered framework that meets the need of
different project facets related to the smart city. It allows the cities to use the urban network …
different project facets related to the smart city. It allows the cities to use the urban network …