- An interpretable decision|making model for autonomous driving🔍
- Interpretable Decision|Making for Autonomous Vehicles with ...🔍
- Driving with Regulation🔍
- An Interpretable Decision|Making for Virtual Driver🔍
- An interpretation framework for autonomous vehicles decision ...🔍
- An Interpretable Deep Reinforcement Learning Approach to ...🔍
- An Overview of Decision|Making in Autonomous Vehicles🔍
- An Interpretable Multi|vehicle Decision|making and Planning ...🔍
An interpretable decision|making model for autonomous driving
An interpretable decision-making model for autonomous driving
We propose a decision-making model explicitly tailored for autonomous vehicles, comprising three distinct modules: needs assessment, motivation generation, and ...
Interpretable Decision-Making for Autonomous Vehicles with ... - arXiv
Abstract:This work presents an interpretable decision-making framework for autonomous vehicles that integrates traffic regulations, norms, ...
Driving with Regulation: Interpretable Decision-Making for ... - arXiv
This work presents an interpretable decision-making framework for autonomous vehicles that integrates traffic regulations, norms, and safety guidelines ...
An Interpretable Decision-Making for Virtual Driver - IEEE Xplore
Abstract: The interpretability of decision-making in autonomous driving is crucial for the building of virtual driver, promoting the trust ...
Interpretable Decision-Making for Autonomous Vehicles with ...
This work presents an interpretable decision-making framework for autonomous vehicles that integrates traffic regulations, norms, ...
An Interpretable Decision-Making for Virtual Driver - ResearchGate
The new method involves cognitive modeling, reinforcement learning and reasoning path extraction. Experiments on the virtual driving environment ...
An interpretation framework for autonomous vehicles decision ...
Abstract: Decision-making for autonomous vehicles is critical to achieving safe and efficient autonomous driving. In recent years, deep reinforcement ...
Driving with Regulation: Interpretable Decision-Making for ...
The paper presents a novel framework for interpretable decision-making in autonomous vehicles, using a combination of large language models (LLMs) and ...
InAction: Interpretable Action Decision Making for Autonomous Driving
A novel Interpretable Action decision making model to provide an enriched explanation from both explicit human annotation and implicit visual semantics, ...
An Interpretable Deep Reinforcement Learning Approach to ...
As a proof of concept, we demonstrate the feasibility of our approach on two classical decision-making scenarios in autonomous driving: lane changing and ...
An Overview of Decision-Making in Autonomous Vehicles
In this review we have surveyed the literature on the autonomous vehicle focusing on the decision-making architecture.
InAction: Interpretable Action Decision Making for Autonomous Driving
Autonomous driving has attracted interest for interpretable action decision models that mimic human cognition. Existing interpretable autonomous driving models ...
DriveGPT4: Interpretable End-to-end Autonomous Driving via Large ...
Multimodal large language models (MLLMs) have emerged as a prominent area of interest within the research community, given their profi- ciency in handling and ...
An Interpretable Multi-vehicle Decision-making and Planning ...
This work proposes a hierarchical multi-vehicle decision-making and planning framework that jointly makes decisions for all vehicles within the flow and ...
Why did the AI make that decision? Towards an explainable artificial ...
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 ...
InAction: Interpretable Action Decision Making for Autonomous Driving
Existing interpretable autonomous driving models explore static human explanations, which ig- nore the implicit visual semantics that are not explicitly ...
Learning Interpretable, High-Performing Policies for Autonomous ...
insight into the model's decision-making, similar to [55, 45]. Our ... An environment for autonomous driving decision-making. https://github.com ...
A Review of Decision-Making and Planning for Autonomous ... - MDPI
[21] proposed a Conv-LSTM model for predicting the position of a left-turning vehicle at an intersection during a turn, which employs CNNs to extract behavioral ...
DriveGPT4: Interpretable End-to-end Autonomous Driving via Large...
To the best of our knowledge, DriveGPT4 is the first work focusing on interpretable end-to-end autonomous driving. When evaluated on multiple tasks alongside ...
Decision-Making Model for Dynamic Scenario Vehicles in ... - MDPI
This addressed the interpretability challenge present in current scenario vehicle behaviors for autonomous driving simulations. Moreover, it ...