Space-weighted information fusion using deep reinforcement learning: The context of tactical control of lane-changing autonomous vehicles and connectivity range assessment

Graph neural network and reinforcement learning for multi‐agent cooperative control of connected autonomous vehicles

(2021) Sikai Chen et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Predicting lane-changing risk level based on vehicles’ space-series features: A pre-emptive learning approach

(2020) Tianyi Chen et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Advanced planning for autonomous vehicles using reinforcement learning and deep inverse reinforcement learning

(2019) Changxi You et al.   ROBOTICS AND AUTONOMOUS SYSTEMS

Deep reinforcement learning enabled self-learning control for energy efficient driving

(2019) Xuewei Qi et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Corridor level cooperative trajectory optimization with connected and automated vehicles

(2019) Chunhui Yu et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

A data-driven lane-changing model based on deep learning

(2019) Dong-Fan Xie et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Stochastic Model-Predictive Control for Lane Change Decision of Automated Driving Vehicles

(2018) Jongsang Suh et al.   IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY

Spatiotemporal intersection control in a connected and automated vehicle environment

(2018) Yiheng Feng et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Connectivity’s impact on mandatory lane-changing behaviour: Evidences from a driving simulator study

(2018) Yasir Ali et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Network Scale Travel Time Prediction using Deep Learning

(2018) Yi Hou et al.   TRANSPORTATION RESEARCH RECORD

A dynamic lane-changing trajectory planning model for automated vehicles

(2018) Da Yang et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Overview of Environment Perception for Intelligent Vehicles

(2017) Hao Zhu et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Platoons of connected vehicles can double throughput in urban roads

(2017) Jennie Lioris et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Deep learning for short-term traffic flow prediction

(2017) Nicholas G. Polson et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Situation assessment and decision making for lane change assistance using ensemble learning methods

(2015) Yi Hou et al.   EXPERT SYSTEMS WITH APPLICATIONS

Recent developments and research needs in modeling lane changing

(2013) Zuduo Zheng   TRANSPORTATION RESEARCH PART B-METHODOLOGICAL

Research and Implementation of Lane-Changing Model Based on Driver Behavior

(2010) Daniel (Jian) Sun et al.   TRANSPORTATION RESEARCH RECORD