[PDF][PDF] Alleviating Road Traffic Congestion with Artificial Intelligence.
G Sharon - IJCAI, 2021 - people.engr.tamu.edu
This paper reviews current AI solutions towards road traffic congestion alleviation. Three
specific AI technologies are discussed,(1) intersection management protocols for …
specific AI technologies are discussed,(1) intersection management protocols for …
[HTML][HTML] Dynamic optimal congestion pricing in multi-region urban networks by application of a Multi-Layer-Neural network
A Genser, A Kouvelas - Transportation Research Part C: Emerging …, 2022 - Elsevier
Traffic management by applying congestion pricing is a measure for mitigating congestion in
protected city corridors. As a promising tool, pricing improves the level of service in a …
protected city corridors. As a promising tool, pricing improves the level of service in a …
Reinforcement learning for cyber-physical systems
Cyber-Physical Systems (CPS), including smart industrial manufacturing, smart
transportation, and smart grids, among others, are envisioned to convert traditionally …
transportation, and smart grids, among others, are envisioned to convert traditionally …
Ctrl: Cooperative traffic tolling via reinforcement learning
Y Wang, H Jin, G Zheng - Proceedings of the 31st ACM International …, 2022 - dl.acm.org
People have been working long to tackle the traffic congestion problem. Among the different
measures, traffic tolling has been recognized as an effective way to mitigate citywide …
measures, traffic tolling has been recognized as an effective way to mitigate citywide …
Cblab: Supporting the training of large-scale traffic control policies with scalable traffic simulation
Traffic simulation provides interactive data for the optimization of traffic control policies.
However, existing traffic simulators are limited by their lack of scalability and shortage in …
However, existing traffic simulators are limited by their lack of scalability and shortage in …
Cblab: Scalable traffic simulation with enriched data supporting
Traffic simulation provides interactive data for the optimization of traffic policies. However,
existing traffic simulators are limited by their lack of scalability and shortage in input data …
existing traffic simulators are limited by their lack of scalability and shortage in input data …
Learning and managing stochastic network traffic dynamics: an iterative and interactive approach
This study examines the potential of an iterative and interactive approach to learn network
traffic dynamics and optimise tolling strategies considering time-varying stochastic traffic. A …
traffic dynamics and optimise tolling strategies considering time-varying stochastic traffic. A …
Dynamic Tolling in Arc-based Traffic Assignment Models
Tolling in traffic networks offers a popular measure to minimize overall congestion. Existing
toll designs primarily focus on congestion in route-based traffic assignment models (TAMs) …
toll designs primarily focus on congestion in route-based traffic assignment models (TAMs) …
A reinforcement learning-based dynamic congestion pricing method for the morning commute problems
K Sato, T Seo, T Fuse - Transportation Research Procedia, 2021 - Elsevier
A reinforcement learning-based dynamic congestion pricing method for morning commute
problems is proposed. In this method, tolls are iteratively updated day by day based on …
problems is proposed. In this method, tolls are iteratively updated day by day based on …
Dynamic resource allocation during natural disasters using multi-agent environment
A Vereshchaka, W Dong - Social, Cultural, and Behavioral Modeling: 12th …, 2019 - Springer
Natural disasters are devastating for a country and effective allocation of critical resources
can mitigate the impact. While traditional approaches usually have difficulties in making …
can mitigate the impact. While traditional approaches usually have difficulties in making …