Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey
H Cao, W Zou, Y Wang, T Song, M Liu - arXiv preprint arXiv:2210.11237, 2022 - arxiv.org
Since the 2004 DARPA Grand Challenge, the autonomous driving technology has
witnessed nearly two decades of rapid development. Particularly, in recent years, with the …
witnessed nearly two decades of rapid development. Particularly, in recent years, with the …
Development methodologies for safety critical machine learning applications in the automotive domain: A survey
Enabled by recent advances in the field of machine learning, the automotive industry pushes
towards automated driving. The development of traditional safety-critical automotive …
towards automated driving. The development of traditional safety-critical automotive …
An improved dueling deep double-q network based on prioritized experience replay for path planning of unmanned surface vehicles
Unmanned Surface Vehicle (USV) has a broad application prospect and autonomous path
planning as its crucial technology has developed into a hot research direction in the field of …
planning as its crucial technology has developed into a hot research direction in the field of …
Adversarial deep reinforcement learning for improving the robustness of multi-agent autonomous driving policies
Autonomous cars are well known for being vulnerable to adversarial attacks that can
compromise the safety of the car and pose danger to other road users. To effectively defend …
compromise the safety of the car and pose danger to other road users. To effectively defend …
An empirical study of ddpg and ppo-based reinforcement learning algorithms for autonomous driving
S Siboo, A Bhattacharyya, RN Raj, SH Ashwin - IEEE Access, 2023 - ieeexplore.ieee.org
Autonomous vehicles mitigate road accidents and provide safe transportation with a smooth
traffic flow. They are expected to greatly improve the quality of the elderly or people with …
traffic flow. They are expected to greatly improve the quality of the elderly or people with …
Artificial intelligence methods for security and cyber security systems
RN Rudd-Orthner - 2022 - etheses.whiterose.ac.uk
This research is in threat analysis and countermeasures employing Artificial Intelligence (AI)
methods within the civilian domain, where safety and mission-critical aspects are essential …
methods within the civilian domain, where safety and mission-critical aspects are essential …
Enhancing Stability and Performance in Mobile Robot Path Planning with PMR-Dueling DQN Algorithm
DA Deguale, L Yu, ML Sinishaw, K Li - Sensors, 2024 - mdpi.com
Path planning for mobile robots in complex circumstances is still a challenging issue. This
work introduces an improved deep reinforcement learning strategy for robot navigation that …
work introduces an improved deep reinforcement learning strategy for robot navigation that …
Evaluating the robustness of deep reinforcement learning for autonomous policies in a multi-agent urban driving environment
Background: Deep reinforcement learning is actively used for training autonomous car
policies in a simulated driving environment. Due to the large availability of various …
policies in a simulated driving environment. Due to the large availability of various …
Deep ConvNet: Non-random weight initialization for repeatable determinism, examined with FSGM
RNM Rudd-Orthner, L Mihaylova - Sensors, 2021 - mdpi.com
A repeatable and deterministic non-random weight initialization method in convolutional
layers of neural networks examined with the Fast Gradient Sign Method (FSGM). Using the …
layers of neural networks examined with the Fast Gradient Sign Method (FSGM). Using the …
Learning to drive fast on a DuckieTown highway
TPA Wiggers, A Visser - International Conference on Intelligent …, 2021 - Springer
We train a small Nvidia AI JetRacer to follow the road on a small DuckieTown highway. In
the real-world, roads do not always have the same appearance, so the system should not be …
the real-world, roads do not always have the same appearance, so the system should not be …