Human Driven Vehicle

Human-driven vehicle (HDV) behavior modeling and prediction are crucial for developing safe and efficient autonomous driving systems. Current research focuses on improving trajectory prediction using deep learning architectures like convolutional and recurrent neural networks, often combined with reinforcement learning algorithms (e.g., DDPG, TD3, PPO) to optimize autonomous vehicle (AV) decision-making in mixed traffic scenarios. This work aims to enhance AV safety and efficiency by accurately anticipating HDV actions, considering factors like driver cooperation, risk assessment, and communication between vehicles. The resulting advancements have implications for improving traffic flow, reducing accidents, and ultimately shaping the future of transportation systems.

Papers

February 17, 2023

Mixed Traffic Control and Coordination from Pixels
Michael Villarreal, Bibek Poudel, Jia Pan, Weizi Li
Mobile Robot Tetromino Pixel Human Driven Vehicle Traffic Management Prior Coordination Traffic Management System Mixed Traffic Control

February 14, 2023

Bringing Diversity to Autonomous Vehicles: An Interpretable Multi-vehicle Decision-making and Planning Framework
Licheng Wen, Pinlong Cai, Daocheng Fu, Song Mao, Yikang Li
Autonomous Driving Autonomous Vehicle Human Driven Vehicle Planning Algorithm Diversity Enhancement Explainable Decision GOFAI Based Planning Multi Robot Decision Making

January 30, 2023

Automatic Intersection Management in Mixed Traffic Using Reinforcement Learning and Graph Neural Networks
Marvin Klimke, Benjamin Völz, Michael Buchholz
Graph Neural Network Automated Driving Human Driven Vehicle Multi Agent Planning Mixed Traffic Intersection Management Mixed Traffic Control

January 12, 2023

Learning to Control and Coordinate Mixed Traffic Through Robot Vehicles at Complex and Unsignalized Intersections
Dawei Wang, Weizi Li, Lei Zhu, Jia Pan
LeArning Abstract Multi Agent Reinforcement Learning External Control Intersection Scenario Human Driven Vehicle Complexity Level Mixed Traffic Unsignalized Intersection

December 4, 2022

Connected Cruise and Traffic Control for Pairs of Connected Automated Vehicles
Sicong Guo, Gabor Orosz, Tamas G. Molnar
Human Driven Vehicle Traffic Management Adaptive Cruise Control Connected Autonomous Vehicle Mixed Traffic Similar Pair Ground Vehicle Vehicle to Everything

November 19, 2022

Prediction-aware and Reinforcement Learning based Altruistic Cooperative Driving
Rodolfo Valiente, Mahdi Razzaghpour, Behrad Toghi, Ghayoor Shah, Yaser P. Fallah
Reinforcement Learning Autonomous Vehicle Human Driven Vehicle Cooperative Driving Multiple Prediction Prediction Boosted Planning Framework

November 9, 2022

Improving safety in mixed traffic: A learning-based model predictive control for autonomous and human-driven vehicle platooning
Jie Wang, Zhihao Jiang, Yash Vardhan Pant
Autonomous Vehicle Predictive Control Learning Based Human SAFETY Human Driven Vehicle Platoon Control Mixed Traffic Car Following Gaussian Process Model Predictive Control

November 6, 2022

Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges
Qi Liu, Xueyuan Li, Zirui Li, Jingda Wu, Guodong Du, Xin Gao, Fan Yang, Shihua Yuan
Timely Survey Autonomous Driving Technical Challenge Human Driven Vehicle Graph Reinforcement Learning Multi Agent Decision Mixed Autonomy Traffic Collaborative Decision

November 3, 2022

Cooperative Maneuvers of Highly Automated Vehicles at Urban Intersections: A Game-theoretic Approach
Björn Koopmann, Stefan Puch, Günter Ehmen, Martin Fränzle
Automated Driving Game Theoretic Intersection Scenario Traffic Simulation Human Driven Vehicle Decentralized Control Cooperative Maneuver

November 2, 2022

Driver Digital Twin for Online Prediction of Personalized Lane Change Behavior
Xishun Liao, Xuanpeng Zhao, Ziran Wang, Zhouqiao Zhao, Kyungtae Han, Rohit Gupta, Matthew J. Barth, Guoyuan Wu
Human Driven Vehicle Driver Behavior Naturalistic Driving Online Prediction Vehicle Edge Computing

July 1, 2022

Comprehensive Reactive Safety: No Need For A Trajectory If You Have A Strategy
Fang Da
Autonomous Driving Autonomous Vehicle Motion Planning Community Need Strategy Logic Human Driven Vehicle Temporal Trajectory

June 24, 2022

May 19, 2022

Centralized Model-Predictive Control with Human-Driver Interaction for Platooning
Justin M. Kennedy, Julian Heinovski, Daniel E. Quevedo, Falko Dressler
Vehicle Interaction Human Driven Vehicle Platoon Control Cooperative Adaptive Cruise Control

April 28, 2022

Interaction of Autonomous and Manually-Controlled Vehicles:Implementation of a Road User Communication Service
Nikita Smirnov, Sebastian Tschernuth, Walter Morales-Alvarez, Cristina Olaverri-Monreal
Practical Implementation Legal Autonomy Decomposed Automation Correction Interaction Generation Human Driven Vehicle Autonomous Ground Vehicle

April 17, 2022

ParkPredict+: Multimodal Intent and Motion Prediction for Vehicles in Parking Lots with CNN and Transformer
Xu Shen, Matthew Lacayo, Nidhir Guggilla, Francesco Borrelli
Transformer Based Trajectory Prediction Motion Prediction Traffic Scenario Future Trajectory Human Driven Vehicle Parking Lot Parking Availability Prediction Multimodal Intent

April 11, 2022

A-DRIVE: Autonomous Deadlock Detection and Recovery at Road Intersections for Connected and Automated Vehicles
Shunsuke Aoki, Ragunathan, Rajkumar
Automated Driving Intersection Scenario Human Driven Vehicle Prompt Recovery Connected Behavior Sparsity Pruning Heterogeneous Traffic Deadlock Free

February 2, 2022

Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic
Rodolfo Valiente, Behrad Toghi, Ramtin Pedarsani, Yaser P. Fallah
Reinforcement Learning Native Robustness Autonomous Vehicle Multi Agent Reinforcement Learning Adaptive Importance Human Driven Vehicle Mixed Autonomy Mixed Autonomy Traffic Cooperative Autonomous Driving

November 27, 2021

Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning
Huayi Li, Nan Li, Ilya Kolmanovsky, Anouck Girard
Reinforcement Learning Autonomous Vehicle Autonomous Driving Technology Human Driven Vehicle Driver Behavior Human Driving Behavior Energy Efficient Autonomous Driving

Human Driven Vehicle

Papers

Mixed Traffic Control and Coordination from Pixels

Bringing Diversity to Autonomous Vehicles: An Interpretable Multi-vehicle Decision-making and Planning Framework

Automatic Intersection Management in Mixed Traffic Using Reinforcement Learning and Graph Neural Networks

Learning to Control and Coordinate Mixed Traffic Through Robot Vehicles at Complex and Unsignalized Intersections

Connected Cruise and Traffic Control for Pairs of Connected Automated Vehicles

Prediction-aware and Reinforcement Learning based Altruistic Cooperative Driving

Improving safety in mixed traffic: A learning-based model predictive control for autonomous and human-driven vehicle platooning

Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges

Cooperative Maneuvers of Highly Automated Vehicles at Urban Intersections: A Game-theoretic Approach

Driver Digital Twin for Online Prediction of Personalized Lane Change Behavior

Comprehensive Reactive Safety: No Need For A Trajectory If You Have A Strategy

Eco-driving for Electric Connected Vehicles at Signalized Intersections: A Parameterized Reinforcement Learning approach

Learning the policy for mixed electric platoon control of automated and human-driven vehicles at signalized intersection: a random search approach

Centralized Model-Predictive Control with Human-Driver Interaction for Platooning

Interaction of Autonomous and Manually-Controlled Vehicles:Implementation of a Road User Communication Service

ParkPredict+: Multimodal Intent and Motion Prediction for Vehicles in Parking Lots with CNN and Transformer

A-DRIVE: Autonomous Deadlock Detection and Recovery at Road Intersections for Connected and Automated Vehicles

Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic

Energy-Efficient Autonomous Driving Using Cognitive Driver Behavioral Models and Reinforcement Learning