65 citations · 125 across the 9 of their papers we have counts for
10 papers
Probe-and-Release Coordination of Platoons at Highway Bottlenecks with Unknown Parameters
Yi Gao, Xi Xiong, Karl H. Johansson +1
This paper considers coordination of platoons of connected and autonomous vehicles (CAVs) at mixed-autonomy bottlenecks in the face of three practically important factors, viz. tim…
Dyna-Style Learning with A Macroscopic Model for Vehicle Platooning in Mixed-Autonomy Traffic
Yichuan Zou, Li Jin, Xi Xiong
Platooning of connected and autonomous vehicles (CAVs) plays a vital role in modernizing highways, ushering in enhanced efficiency and safety. This paper explores the significance…
An Approximate Dynamic Programming Approach to Vehicle Platooning Coordination in Networks
Xi Xiong, Maonan Wang, Dengfeng Sun +1
Platooning connected and autonomous vehicles (CAVs) provide significant benefits in terms of traffic efficiency and fuel economy. However, most existing platooning systems assume t…
ADLight: A Universal Approach of Traffic Signal Control with Augmented Data Using Reinforcement Learning
Maonan Wang, Yutong Xu, Xi Xiong +3
Traffic signal control has the potential to reduce congestion in dynamic networks. Recent studies show that traffic signal control with reinforcement learning (RL) methods can sign…
Optimizing Coordinated Vehicle Platooning: An Analytical Approach Based on Stochastic Dynamic Programming
Xi Xiong, Junyi Sha, Li Jin
Platooning connected and autonomous vehicles (CAVs) can improve traffic and fuel efficiency. However, scalable platooning operations require junction-level coordination, which has…
Evaluation of Headway Threshold-based Coordinated Platooning over a Cascade of Highway Junctions
Xi Xiong, Teze Wang, Li Jin
Platooning of vehicles with coordinated adaptive cruise control (CACC) capabilities is a promising technology with a strong potential for fuel savings and congestion mitigation. Al…
Coordinating Vehicle Platoons for Highway Bottleneck Decongestion and Throughput Improvement
Mladen Čičić, Li Jin, Karl Henrik Johansson
Truck platooning is a technology that is expected to become widespread in the coming years. Apart from the numerous benefits that it brings, its potential effects on the overall tr…
Dynamic Origin-Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter
Xi Xiong, Kaan Ozbay, Li Jin +1
Modern intelligent transportation systems provide data that allow real-time dynamic demand prediction, which is essential for planning and operations. The main challenge of predict…
Analysis of a Stochastic Model for Coordinated Platooning of Heavy-duty Vehicles
Xi Xiong, Erdong Xiao, Li Jin
Platooning of heavy-duty vehicles (HDVs) is a key component of smart and connected highways and is expected to bring remarkable fuel savings and emission reduction. In this paper,…
Combining Deep Reinforcement Learning and Safety Based Control for Autonomous Driving
Xi Xiong, Jianqiang Wang, Fang Zhang +1
With the development of state-of-art deep reinforcement learning, we can efficiently tackle continuous control problems. But the deep reinforcement learning method for continuous c…