Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning
Inefficient traffic control may cause numerous problems such as traffic congestion and
energy waste. This paper proposes a novel multi-agent reinforcement learning method …
energy waste. This paper proposes a novel multi-agent reinforcement learning method …
[HTML][HTML] CCGN: Centralized collaborative graphical transformer multi-agent reinforcement learning for multi-intersection signal free-corridor
Tackling traffic signal control through multi-agent reinforcement learning is a widely-
employed approach. However, current state-of-the-art models have drawbacks: intersections …
employed approach. However, current state-of-the-art models have drawbacks: intersections …
Fuzzy logic and genetic-based algorithm for a servo control system
H Torres-Salinas, J Rodríguez-Reséndiz… - Micromachines, 2022 - mdpi.com
Performing control is necessary for processes where a variable needs to be regulated. Even
though conventional techniques are widely preferred for their implementation, they present …
though conventional techniques are widely preferred for their implementation, they present …
Three novel fuzzy logic concepts applied to reshoring decision-making
This paper investigates the possibility of increasing the interpretability of fuzzy rules and
reducing the complexity when designing fuzzy rules. To achieve this, three novel fuzzy logic …
reducing the complexity when designing fuzzy rules. To achieve this, three novel fuzzy logic …
Intelligent traffic light design and control in smart cities: a survey on techniques and methodologies
Increased traffic in metropolitan territories has led to significant concerns, such as road
blockage, transportation delays, pollution level, fuel consumption, etc. Traffic light signals at …
blockage, transportation delays, pollution level, fuel consumption, etc. Traffic light signals at …
Congestion adaptive traffic light control and notification architecture using google maps APIs
Traffic jams can be avoided by controlling traffic signals according to quickly building
congestion with steep gradients on short temporal and small spatial scales. With the rising …
congestion with steep gradients on short temporal and small spatial scales. With the rising …
Fuzzy Control Under Time-Varying Universe and Phase Optimization in Traffic Lights (ICSSE 2020)
C Zhou, H Mo, X Chen, H Wen - International Journal of Fuzzy Systems, 2021 - Springer
As the pace of life accelerates, people are troubled by spending too much time on
commuting, and people's waiting time for travel can be reduced by reasonable strategy of …
commuting, and people's waiting time for travel can be reduced by reasonable strategy of …
Fitness landscapes analysis and adaptive algorithms design for traffic lights optimization on SIALAC benchmark
Finding optimal traffic light timings at road intersections is a mandatory step for urban
planners wishing to achieve a sustainable mobility in modern cities. Increasing congestion …
planners wishing to achieve a sustainable mobility in modern cities. Increasing congestion …
Optimizing of phase plan, sequence and signal timing based on flower pollination algorithm for signalized intersections
The purpose of this study is to develop a control system that optimizes the phase plan,
sequence and signal timing using the flower pollination algorithm (FPA). At the same time, it …
sequence and signal timing using the flower pollination algorithm (FPA). At the same time, it …
Distributed Multi-Intersection Traffic Flow Prediction using Deep Learning
Efficient traffic flow prediction is paramount in modern urban transportation management,
contributing significantly to energy efficiency and overall sustainability. Traditional traffic …
contributing significantly to energy efficiency and overall sustainability. Traditional traffic …