Connected autonomous vehicle motion planning with video predictions from smart, self-supervised infrastructure
Connected autonomous vehicles (CAVs) promise to enhance safety, efficiency, and
sustainability in urban transportation. However, this is contingent upon a CAV correctly …
sustainability in urban transportation. However, this is contingent upon a CAV correctly …
Self-supervised traffic advisors: Distributed, multi-view traffic prediction for smart cities
Connected and Autonomous Vehicles (CAVs) are becoming more widely deployed, but it is
unclear how to best deploy smart infrastructure to maximize their capabilities. One key …
unclear how to best deploy smart infrastructure to maximize their capabilities. One key …
A Context-Aware Path Forecasting Method for Connected Autonomous Vehicles
MN Azadani, A Boukerche - ICC 2023-IEEE International …, 2023 - ieeexplore.ieee.org
Forecasting the future paths of surrounding vehicles of a Connected Autonomous Vehicle
(CAV) can enhance connectivity and efficiency of vehicular networks, and accurate motion …
(CAV) can enhance connectivity and efficiency of vehicular networks, and accurate motion …
Bringing diversity to autonomous vehicles: An interpretable multi-vehicle decision-making and planning framework
With the development of autonomous driving, it is becoming increasingly common for
autonomous vehicles (AVs) and human-driven vehicles (HVs) to travel on the same roads …
autonomous vehicles (AVs) and human-driven vehicles (HVs) to travel on the same roads …
An infrastructure-based cooperative driving framework for connected and automated vehicles
Z Yang - 2022 - deepblue.lib.umich.edu
Trajectory planning is a key component of the Connected and Automated Vehicle (CAV)
autonomy stack. It is a challenging task to plan a trajectory for a CAV that ensures safety …
autonomy stack. It is a challenging task to plan a trajectory for a CAV that ensures safety …
Safety-assured speculative planning with adaptive prediction
Recently significant progress has been made in vehicle prediction and planning algorithms
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …
STFP: Simultaneous traffic scene forecasting and planning for autonomous driving
Autonomous vehicles must be able to understand the surrounding traffic flows and predict
the future traffic conditions for planning a safe maneuver. During prediction, the action of …
the future traffic conditions for planning a safe maneuver. During prediction, the action of …
Implicit scene context-aware interactive trajectory prediction for autonomous driving
The accurate prediction of behaviors of surrounding traffic participants is critical for
autonomous vehicles (AV). How to fully encode both explicit (eg, map structure and road …
autonomous vehicles (AV). How to fully encode both explicit (eg, map structure and road …
Improving Efficiency and Generalisability of Motion Predictions With Deep Multi-Agent Learning and Multi-Head Attention
DE Benrachou, S Glaser, M Elhenawy… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Automated Vehicles (AVs) have been receiving increasing attention as a potential highly
mechanised, intelligent, self-regulating futuristic mode of transport. AVs are predicted to …
mechanised, intelligent, self-regulating futuristic mode of transport. AVs are predicted to …
Graph-based Prediction and Planning Policy Network (GP3Net) for scalable self-driving in dynamic environments using Deep Reinforcement Learning
Recent advancements in motion planning for Autonomous Vehicles (AVs) show great
promise in using expert driver behaviors in non-stationary driving environments. However …
promise in using expert driver behaviors in non-stationary driving environments. However …