A taxonomy for autonomous vehicles considering ambient road infrastructure
To standardize definitions and guide the design, regulation, and policy related to automated
transportation, the Society of Automotive Engineers (SAE) has established a taxonomy …
transportation, the Society of Automotive Engineers (SAE) has established a taxonomy …
Graph neural network and reinforcement learning for multi‐agent cooperative control of connected autonomous vehicles
A connected autonomous vehicle (CAV) network can be defined as a set of connected
vehicles including CAVs that operate on a specific spatial scope that may be a road network …
vehicles including CAVs that operate on a specific spatial scope that may be a road network …
Space-weighted information fusion using deep reinforcement learning: The context of tactical control of lane-changing autonomous vehicles and connectivity range …
The connectivity aspect of connected autonomous vehicles (CAV) is beneficial because it
facilitates dissemination of traffic-related information to vehicles through Vehicle-to-External …
facilitates dissemination of traffic-related information to vehicles through Vehicle-to-External …
Dynamic urban traffic rerouting with fog‐cloud reinforcement learning
Dynamic rerouting has been touted as a solution for urban traffic congestion. However, its
implementation is stymied by the complexity of urban traffic. To address this, recent studies …
implementation is stymied by the complexity of urban traffic. To address this, recent studies …
[HTML][HTML] The deceitful connected and autonomous vehicle: defining the concept, contextualising its dimensions and proposing mitigation policies
Abstract The Connected and Autonomous Vehicle (CAV) is an emerging mobility technology
that may hold a paradigm-changing potential for the future of transport policy and planning …
that may hold a paradigm-changing potential for the future of transport policy and planning …
Leveraging the capabilities of connected and autonomous vehicles and multi-agent reinforcement learning to mitigate highway bottleneck congestion
Active Traffic Management strategies are often adopted in real-time to address such sudden
flow breakdowns. When queuing is imminent, Speed Harmonization (SH), which adjusts …
flow breakdowns. When queuing is imminent, Speed Harmonization (SH), which adjusts …
A DRL-based multiagent cooperative control framework for CAV networks: A graphic convolution Q network
Connected Autonomous Vehicle (CAV) Network can be defined as a collection of CAVs
operating at different locations on a multilane corridor, which provides a platform to facilitate …
operating at different locations on a multilane corridor, which provides a platform to facilitate …
[PDF][PDF] Development and testing of an image transformer for explainable autonomous driving systems
Purpose-Perception has been identified as the main cause underlying most autonomous
vehicle related accidents. As the key technology in perception, deep learning (DL) based …
vehicle related accidents. As the key technology in perception, deep learning (DL) based …
Trajectory control in roundabouts with a mixed fleet of automated and human‐driven vehicles
R Mohebifard, A Hajbabaie - Computer‐Aided Civil and …, 2022 - Wiley Online Library
This paper presents a methodology to control the trajectory of cooperative connected
automated vehicles (CAVs) at roundabouts with a mixed fleet of CAVs and human‐driven …
automated vehicles (CAVs) at roundabouts with a mixed fleet of CAVs and human‐driven …
Leveraging vehicle connectivity and autonomy for highway bottleneck congestion mitigation using reinforcement learning
Automation and connectivity based platforms have great potential for managing highway
traffic congestion including bottlenecks. Speed harmonisation (SH), one of such platforms, is …
traffic congestion including bottlenecks. Speed harmonisation (SH), one of such platforms, is …