Car-following models for human-driven vehicles and autonomous vehicles: A systematic review
The focus of car-following models is to analyze the microscopic characteristics of traffic
flows, with particular attention given to the interaction between adjacent vehicles. This paper …
flows, with particular attention given to the interaction between adjacent vehicles. This paper …
A deep reinforcement learning based distributed control strategy for connected automated vehicles in mixed traffic platoon
This paper proposes an innovative distributed longitudinal control strategy for connected
automated vehicles (CAVs) in the mixed traffic environment of CAV and human-driven …
automated vehicles (CAVs) in the mixed traffic environment of CAV and human-driven …
Physics-informed deep reinforcement learning-based integrated two-dimensional car-following control strategy for connected automated vehicles
Connected automated vehicles (CAVs) are broadly recognized as next-generation
transformative transportation technologies having great potential to improve traffic safety …
transformative transportation technologies having great potential to improve traffic safety …
A deep reinforcement learning‐based distributed connected automated vehicle control under communication failure
This paper proposes a deep reinforcement learning (DRL)‐based distributed longitudinal
control strategy for connected and automated vehicles (CAVs) under communication failure …
control strategy for connected and automated vehicles (CAVs) under communication failure …
An integrated car-following and lane changing vehicle trajectory prediction algorithm based on a deep neural network
Vehicle trajectory prediction is essential for the operation safety and control efficiency of
automated driving. Prevailing studies predict car following and lane change processes in a …
automated driving. Prevailing studies predict car following and lane change processes in a …
Multi-agent reinforcement learning for connected and automated vehicles control: Recent advancements and future prospects
Connected and automated vehicles (CAVs) have emerged as a potential solution to the
future challenges of developing safe, efficient, and eco-friendly transportation systems …
future challenges of developing safe, efficient, and eco-friendly transportation systems …
Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems
User trust has been identified as a critical issue that is pivotal to the success of autonomous
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …
vehicle (AV) operations where artificial intelligence (AI) is widely adopted. For such …
Car-following behavior of human-driven vehicles in mixed-flow traffic: A driving simulator study
Connected and autonomous vehicles (CAVs) and human-driven vehicles (HDVs) will
inevitably coexist on roads in the future, creating mixed-flow traffic. The heterogeneous car …
inevitably coexist on roads in the future, creating mixed-flow traffic. The heterogeneous car …
Cooperative control of a platoon of connected autonomous vehicles and unconnected human‐driven vehicles
By using kinematic state information obtained through vehicle‐to‐vehicle communications,
connected autonomous vehicles (CAVs) can drive cooperatively to alleviate shockwave …
connected autonomous vehicles (CAVs) can drive cooperatively to alleviate shockwave …
Study on mixed traffic of autonomous vehicles and human-driven vehicles with different cyber interaction approaches
XY Guo, G Zhang, AF Jia - Vehicular Communications, 2023 - Elsevier
The emergence of autonomous vehicles will significantly improve traffic efficiency and
safety. Before the fully autonomous driving of traffic system, the mixed traffic with …
safety. Before the fully autonomous driving of traffic system, the mixed traffic with …