Safety in Traffic Management Systems: A Comprehensive Survey
Traffic management systems play a vital role in ensuring safe and efficient transportation on
roads. However, the use of advanced technologies in traffic management systems has …
roads. However, the use of advanced technologies in traffic management systems has …
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 …
Digital Twin-Assisted Data-Driven Optimization for Reliable Edge Caching in Wireless Networks
Optimizing edge caching is crucial for the advancement of next-generation (nextG) wireless
networks, ensuring high-speed and low-latency services for mobile users. Existing data …
networks, ensuring high-speed and low-latency services for mobile users. Existing data …
Coslight: Co-optimizing collaborator selection and decision-making to enhance traffic signal control
Effective multi-intersection collaboration is pivotal for reinforcement-learning-based traffic
signal control to alleviate congestion. Existing work mainly chooses neighboring …
signal control to alleviate congestion. Existing work mainly chooses neighboring …
π-light: Programmatic interpretable reinforcement learning for resource-limited traffic signal control
The recent advancements in Deep Reinforcement Learning (DRL) have significantly
enhanced the performance of adaptive Traffic Signal Control (TSC). However, DRL policies …
enhanced the performance of adaptive Traffic Signal Control (TSC). However, DRL policies …
Safety Assessment and Risk Management of Urban Arterial Traffic Flow Based on Artificial Driving and Intelligent Network Connection: An Overview
Y Pei, L Hou - Archives of Computational Methods in Engineering, 2024 - Springer
As the problems with managing traffic in cities get worse, this paper looks at a way to make it
easier to judge safety and handle risks in the flow of traffic on major roads in cities. By …
easier to judge safety and handle risks in the flow of traffic on major roads in cities. By …
Cooperative Traffic Signal Control Using a Distributed Agent-Based Deep Reinforcement Learning With Incentive Communication
Deep Reinforcement Learning has shown some promise in dynamic traffic signal control by
adapting to real-time traffic conditions. However, multi-intersection control presents …
adapting to real-time traffic conditions. However, multi-intersection control presents …
[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 …
Constrained Reinforcement Learning for Fair and Environmentally Efficient Traffic Signal Controllers
Traffic signal controller (TSC) has a crucial role in managing traffic flow in urban areas.
Recently, reinforcement learning (RL) models have received a great attention for TSC with …
Recently, reinforcement learning (RL) models have received a great attention for TSC with …