167 citations · 502 across the 33 of their papers we have counts for
4 papers · 1 filter
Autonomous Driving using Safe Reinforcement Learning by Incorporating a Regret-based Human Lane-Changing Decision Model
Dong Chen, Longsheng Jiang, Yue Wang +1
It is expected that many human drivers will still prefer to drive themselves even if the self-driving technologies are ready. Therefore, human-driven vehicles and autonomous vehicl…
Robust Platoon Control in Mixed Traffic Flow Based on Tube Model Predictive Control
Shuo Feng, Ziyou Song, Zhaojian Li +2
The design of cooperative adaptive cruise control is critical in mixed traffic flow, where connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) coexist. Compare…
Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control
Tianshu Chu, Jie Wang, Lara Codecà +1
Reinforcement learning (RL) is a promising data-driven approach for adaptive traffic signal control (ATSC) in complex urban traffic networks, and deep neural networks further enhan…
A New Microscopic Traffic Model Using a Spring-Mass-Damper-Clutch System
Zhaojian Li, Firas Khasawneh, Xiang Yin +2
Microscopic traffic models describe how cars interact with their neighbors in an uninterrupted traffic flow and are frequently used for reference in advanced vehicle control design…