Deep learning for trajectory data management and mining: A survey and beyond
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …
mining, garnering widespread attention due to its crucial role in various practical …
Safelight: A reinforcement learning method toward collision-free traffic signal control
Traffic signal control is safety-critical for our daily life. Roughly one-quarter of road accidents
in the US happen at intersections due to problematic signal timing, urging the development …
in the US happen at intersections due to problematic signal timing, urging the development …
Prompt to Transfer: Sim-to-Real Transfer for Traffic Signal Control with Prompt Learning
Numerous methods are proposed for the Traffic Signal Control (TSC) tasks aiming to provide
efficient transportation and mitigate congestion waste. In recent, promising results have …
efficient transportation and mitigate congestion waste. In recent, promising results have …
eTraM: Event-based Traffic Monitoring Dataset
Event cameras with their high temporal and dynamic range and minimal memory usage
have found applications in various fields. However their potential in static traffic monitoring …
have found applications in various fields. However their potential in static traffic monitoring …
Llm powered sim-to-real transfer for traffic signal control
Numerous solutions are proposed for the Traffic Signal Control (TSC) tasks aiming to
provide efficient transportation and mitigate congestion waste. In recent, promising results …
provide efficient transportation and mitigate congestion waste. In recent, promising results …
Open-ti: Open traffic intelligence with augmented language model
Transportation has greatly benefited the cities' development in the modern civilization
process. Intelligent transportation, leveraging advanced computer algorithms, could further …
process. Intelligent transportation, leveraging advanced computer algorithms, could further …
Uncertainty-aware Grounded Action Transformation towards Sim-to-Real Transfer for Traffic Signal Control
Traffic signal control (TSC) is a complex and important task that affects the daily lives of
millions of people. Reinforcement Learning (RL) has shown promising results in optimizing …
millions of people. Reinforcement Learning (RL) has shown promising results in optimizing …
[HTML][HTML] HumanLight: Incentivizing ridesharing via human-centric deep reinforcement learning in traffic signal control
Single occupancy vehicles are the most attractive transportation alternative for many
commuters, leading to increased traffic congestion and air pollution. Advancements in …
commuters, leading to increased traffic congestion and air pollution. Advancements in …
MARLens: Understanding Multi-Agent Reinforcement Learning for Traffic Signal Control Via Visual Analytics
Y Zhang, G Zheng, Z Liu, Q Li… - IEEE transactions on …, 2024 - ieeexplore.ieee.org
The issue of traffic congestion poses a significant obstacle to the development of global
cities. One promising solution to tackle this problem is intelligent traffic signal control (TSC) …
cities. One promising solution to tackle this problem is intelligent traffic signal control (TSC) …
A Holistic Framework Towards Vision-based Traffic Signal Control with Microscopic Simulation
Traffic signal control (TSC) is crucial for reducing traffic congestion that leads to smoother
traffic flow, reduced idling time, and mitigated CO2 emissions. In this study, we explore the …
traffic flow, reduced idling time, and mitigated CO2 emissions. In this study, we explore the …