Search Results for author:
Found 5 papers, 0 papers with code
Impact of Acceleration/deceleration Limits on the String Stability of Adaptive Cruise Control
This paper demonstrates that the acceleration/deceleration limits in ACC systems can make a string stable ACC amplify the speed perturbation in natural driving.
Significance of Low-level Controller for String Stability under Adaptive Cruise Control
Current commercial adaptive cruise control (ACC) systems consist of an upper-level planner controller that decides the optimal trajectory that should be followed, and a low-level controller in charge of sending the gas/brake signals to the mechanical system to actually move the vehicle.
Incentive-based Decentralized Routing for Connected and Autonomous Vehicles using Information Propagation
The first stage incorporates a decentralized local route switching dynamical system to approximate the system optimal route flow in a local area based on vehicles' knowledge of local traffic information.
Autonomous Vehicles
Physics and Society
Computer Science and Game Theory
Systems and Control
Systems and Control
Review of Learning-based Longitudinal Motion Planning for Autonomous Vehicles: Research Gaps between Self-driving and Traffic Congestion
Some suggestions towards congestion mitigation for future mMP studies are proposed: i) enrich data collection to facilitate the congestion learning, ii) incorporate non-imitation learning methods to combine traffic efficiency into a safety-oriented technical route, and iii) integrate domain knowledge from the traditional car following (CF) theory to improve the string stability of mMP.
Predicting Station-level Hourly Demands in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approach
Two architectures of the GCNN-DDGF model are explored; GCNNreg-DDGF is a regular GCNN-DDGF model which contains the convolution and feedforward blocks, and GCNNrec-DDGF additionally contains a recurrent block from the Long Short-term Memory neural network architecture to capture temporal dependencies in the bike-sharing demand series.
