Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems
出版年份 2023 全文链接
标题
Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems
作者
关键词
-
出版物
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
Volume 156, Issue -, Pages 104358
出版商
Elsevier BV
发表日期
2023-09-30
DOI
10.1016/j.trc.2023.104358
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Explainability of Deep Vision-Based Autonomous Driving Systems: Review and Challenges
- (2022) Éloi Zablocki et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Attention for Vision-Based Assistive and Automated Driving: A Review of Algorithms and Datasets
- (2022) Iuliia Kotseruba et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- COOR-PLT: A hierarchical control model for coordinating adaptive platoons of connected and autonomous vehicles at signal-free intersections based on deep reinforcement learning
- (2022) Duowei Li et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning
- (2021) Xuan Di et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Graph neural network and reinforcement learning for multi‐agent cooperative control of connected autonomous vehicles
- (2021) Sikai Chen et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Multi-scale driver behavior modeling based on deep spatial-temporal representation for intelligent vehicles
- (2021) Yang Xing et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Space-weighted information fusion using deep reinforcement learning: The context of tactical control of lane-changing autonomous vehicles and connectivity range assessment
- (2021) Jiqian Dong et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment
- (2021) Haotian Shi et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Comfortable and energy-efficient speed control of autonomous vehicles on rough pavements using deep reinforcement learning
- (2021) Yuchuan Du et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness
- (2021) Guofa Li et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Driving behavior explanation with multi-level fusion
- (2021) Hédi Ben-Younes et al. PATTERN RECOGNITION
- Explanations in Autonomous Driving: A Survey
- (2021) Daniel Omeiza et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Cyber-physical system architecture for automating the mapping of truck loads to bridge behavior using computer vision in connected highway corridors
- (2020) Rui Hou et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Forecasting road traffic speeds by considering area-wide spatio-temporal dependencies based on a graph convolutional neural network (GCN)
- (2020) Byeonghyeop Yu et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Multi-vehicle routing problems with soft time windows: A multi-agent reinforcement learning approach
- (2020) Ke Zhang et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Urban flow prediction with spatial–temporal neural ODEs
- (2020) Fan Zhou et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- DeepPF: A deep learning based architecture for metro passenger flow prediction
- (2019) Yang Liu et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- A deep learning algorithm for simulating autonomous driving considering prior knowledge and temporal information
- (2019) Sikai Chen et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- An effective spatial-temporal attention based neural network for traffic flow prediction
- (2019) Loan N.N. Do et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- Predicting the Driver's Focus of Attention: the DR(eye)VE Project
- (2018) Andrea Palazzi et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Perceptions of autonomous vehicles: Relationships with road users, risk, gender and age
- (2018) Lynn M. Hulse et al. SAFETY SCIENCE
- Automated vision inspection of rail surface cracks: A double-layer data-driven framework
- (2018) Li Zhuang et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- A Survey of Methods for Explaining Black Box Models
- (2018) Riccardo Guidotti et al. ACM COMPUTING SURVEYS
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