A Survey on integration of network communication into vehicle real-time motion control
B Deng, J Nan, W Cao, W Wang - … Communications Surveys & …, 2023 - ieeexplore.ieee.org
In the initial period of automobile development, the vast majority of researchers would never
have guessed network communications would be applied to vehicles one day. After the …
have guessed network communications would be applied to vehicles one day. After the …
Safe intersection management with cooperative perception for mixed traffic of human-driven and autonomous vehicles
S Aoki, R Rajkumar - IEEE Open Journal of Vehicular …, 2022 - ieeexplore.ieee.org
Autonomous driving systems are highly expected to be used on public roads to improve
traffic throughput and road safety, but it will likely take a long transition period before all …
traffic throughput and road safety, but it will likely take a long transition period before all …
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 …
Learning representation for anomaly detection of vehicle trajectories
Predicting the future trajectories of surrounding vehicles based on their history trajectories is
a critical task in autonomous driving. However, when small crafted perturbations are …
a critical task in autonomous driving. However, when small crafted perturbations are …
Waving the double-edged sword: Building resilient cavs with edge and cloud computing
The rapid advancement of edge and cloud computing platforms, vehicular ad-hoc networks,
and machine learning techniques have brought both opportunities and challenges for next …
and machine learning techniques have brought both opportunities and challenges for next …
Know the unknowns: Addressing disturbances and uncertainties in autonomous systems
Future autonomous systems will employ complex sensing, computation, and communication
components for their perception, planning, control, and coordination, and could operate in …
components for their perception, planning, control, and coordination, and could operate in …
Intelligent traffic signal control based on reinforcement learning with state reduction for smart cities
Efficient signal control at isolated intersections is vital for relieving congestion, accidents,
and environmental pollution caused by increasing numbers of vehicles. However, most of …
and environmental pollution caused by increasing numbers of vehicles. However, most of …
Safety-assured design and adaptation of learning-enabled autonomous systems
Future autonomous systems will employ sophisticated machine learning techniques for the
sensing and perception of the surroundings and the making corresponding decisions for …
sensing and perception of the surroundings and the making corresponding decisions for …
Cyber traffic light: Safe cooperation for autonomous vehicles at dynamic intersections
S Aoki, R Rajkumar - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
Autonomous driving systems are becoming increasingly feasible and highly expected to be
the heart of intelligent transportation systems. To deploy the autonomous driving vehicles on …
the heart of intelligent transportation systems. To deploy the autonomous driving vehicles on …
Semi-supervised semantics-guided adversarial training for robust trajectory prediction
Predicting the trajectories of surrounding objects is a critical task for self-driving vehicles and
many other autonomous systems. Recent works demonstrate that adversarial attacks on …
many other autonomous systems. Recent works demonstrate that adversarial attacks on …