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Found 9 papers, 1 papers with code
Driving Towards Stability and Efficiency: A Variable Time Gap Strategy for Adaptive Cruise Control
This study introduces a novel variable time gap feedback control policy aimed at striking a balance between maintaining a minimum time gap setting under equilibrium car-following conditions, thereby improving traffic capacity, while ensuring string stability to mitigate disturbances away from the equilibrium flow.
Antifragile Perimeter Control: Anticipating and Gaining from Disruptions with Reinforcement Learning
While previous research works have dedicated efforts to improving the robustness or resilience of transportation systems against disruptions, this paper applies the cutting-edge concept of antifragility to better design a traffic control strategy for urban road networks.
The Fragile Nature of Road Transportation Systems
The continuous increase in traffic demand presents a substantial challenge to the optimal operation of urban road networks and the efficiency of traffic control strategies.
Platoon Fundamental Diagram estimation can be Markovian: evidence from human- and self-driven vehicle trajectories
We propose a simple and effective method to derive the Fundamental Diagram (FD) from platoon vehicle trajectories.
A Time-varying Shockwave Speed Model for Trajectory Reconstruction using Lagrangian and Eulerian Observations
The calibrated shockwave speed of the CV is then utilized for trajectory reconstruction of other non-connected vehicles based on shockwave theory.
Energy-based Assessment and Driving Behavior of ACC Systems and Humans Inside Platoons
Evidence in the literature shows that automated and human driving modes demonstrate different driving characteristics, i. e., headway policy, spacing policy, reaction time, comfortable acceleration, and others.
Two-layer adaptive signal control framework for large-scale dynamically-congested networks: Combining efficient Max Pressure with Perimeter Control
However, its effectiveness under saturated conditions is questionable, while network-wide application is limited due to high instrumentation cost.
Time-to-Green predictions for fully-actuated signal control systems with supervised learning
Recently, efforts have been made to standardize signal phase and timing (SPaT) messages.
An Experimental Urban Case Study with Various Data Sources and a Model for Traffic Estimation
However, the problem of traffic state estimation from various sensors within an urban environment is very complex for several different reasons, such as availability of sensors, different noise levels, different output quantities, sensor accuracy, heterogeneous data fusion, and many more.
