System papers for connected and autonomous vehicle research
Target venues:
- robotics conferences (IROS/ICRA);
- real-time system conferences (RTSS/RTAS);
- computing system conferences (ATC/EuroSys/NSDI/OSDI/ASPLOS/MICRO/HPCA/ISCA/MobiCom/MobiSys/SEC/ICDCS);
- robotics journals (Nature/Science Robotics/T-RO/TITS/SoRo/RA-L);
- computer security conferences (USENIX Security/IEEE S&P/CCS).
[ICRA'23] An Open Approach to Energy-Efficient Autonomous Mobile Robots
[IROS'22] MMFN: Multi-Modal-Fusion-Net for End-to-End Driving
[EuroSys'22] D3: A Dynamic Deadline-Driven Approach for Building Autonomous Vehicles
[MICRO'21] Building the Computing System for Autonomous Micromobility Vehicles: Design Constraints and Architectural Optimizations
[ISCA'21] RoboX: An End-to-End Solution to Accelerate Autonomous Control in Robotics
[IoTJ'21] Computing Systems for Autonomous Driving: State-of-the-Art and Challenges
[PIEEE'19] Edge Computing for Autonomous Driving: Opportunities and Challenges
[IEEE-Micro'15] An Open Approach to Autonomous Vehicles
[ICRA'22] VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles
[ASPLOS'21] Quantifying the design-space tradeoffs in autonomous drones
[ICRA'21] Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehicles
[RTAS'20] Timing of Autonomous Driving Software: Problem Analysis and Prospects for Future Solutions
[IISWC'20] Demystifying Power and Performance Bottlenecks in Autonomous Driving Systems
[ASPLOS'18] The Architectural Implications of Autonomous Driving: Constraints and Acceleration
[RTAS'17] An Evaluation of the NVIDIA TX1 for Supporting Real-time Computer-Vision Workloads
[PIEEE'11] Vehicular Channel Characterization and Its Implications for Wireless System Design and Performance
[Nature'23] Dense reinforcement learning for safety validation of autonomous vehicles
[TITS'23] Fuel Rate Prediction for Heavy-Duty Trucks
[IROS'22] From Timing Variations to Performance Degradation: Understanding and Mitigating the Impact of Software Execution Timing in SLAM
[ICRA'22] Real-time Full-stack Traffic Scene Perception for Autonomous Driving with Roadside Cameras
[RTSS'22] Prophet: Realizing a Predictable Real-time Perception Pipeline for Autonomous Vehicles
[RTAS'22] DNN-SAM: Split-and-Merge DNN Execution for Real-Time Object Detection
[NSDI'22] SwarmMap: Scaling Up Real-time Collaborative Visual SLAM at the Edge
[MobiSys'22] Sunflower: Locating Underwater Robots From the Air
[MobiSys'22] AutoCast: Scalable Infrastructure-less Cooperative Perception for Distributed Collaborative Driving
[MobiSys'22] Motion Inspires Notion: Self-supervised Visual-LiDAR Fusion for Environment Depth Estimation
[RTAS'22] Brief Industry Paper: Enabling Level-4 Autonomous Driving on a Single $1k Off-the-Shelf Card
[RTAS'22] Brief Industry Paper: The Necessity of Adaptive Data Fusion in Infrastructure-Augmented Autonomous Driving System
[ICDCS'22] To Turn or Not To Turn, SafeCross is the Answer
[RTAS'21] Budget RNNs: Multi-Capacity Neural Networks to Improve In-Sensor Inference Under Energy Budgets
[MobiCom'21] VI-eye: semantic-based 3D point cloud registration for infrastructure-assisted autonomous driving
[MICRO'21] Archytas: A Framework for Synthesizing and Dynamically Optimizing Accelerators for Robotic Localization
[HPCA'21] Eudoxus: Characterizing and Accelerating Localization in Autonomous Machines
[CVPR'20] Towards Streaming Perception
[NSDI'20] CarMap: Fast 3D Feature Map Updates for Automobiles
[RTSS'20] R-TOD: Real-Time Object Detector with Minimized End-to-End Delay for Autonomous Driving
[RTAS'20] Real-Time Object Detection System with Multi-Path Neural Networks
[ICCV'19] A Delay Metric for Video Object Detection: What Average Precision Fails to Tell
[RTAS'19] Re-Thinking CNN Frameworks for Time-Sensitive Autonomous-Driving Applications: Addressing an Industrial Challenge
[RTSS'18] ApNet: Approximation-Aware Real-Time Neural Network
[RTSS'18] PredJoule: A Timing-Predictable Energy Optimization Framework for Deep Neural Networks
[SenSys'11] Adversarial Attacks against LiDAR Semantic Segmentation in Autonomous Driving
[Arxiv'22] SoK: On the Semantic AI Security in Autonomous Driving
[USENIX Security'21] Too Good to Be Safe: Tricking Lane Detection in Autonomous Driving with Crafted Perturbations
[IEEE S&P'21] Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
[USENIX Security'20] Drift with Devil: Security of Multi-Sensor Fusion based Localization in High-Level Autonomous Driving under GPS Spoofing
[USENIX Security'20] Towards Robust LiDAR-based Perception in Autonomous Driving: General Black-box Adversarial Sensor Attack and Countermeasures
[RA-L'21] Oops! It’s Too Late. Your Autonomous Driving System Needs a Faster Middleware
[ATC'21] DART: A Scalable and Adaptive Edge Stream Processing Engine
[RTSS'21] A Middleware Protocol for Time-Critical Wireless Communication of Large Data Samples
[ECRTS'19] Response-Time Analysis of ROS 2 Processing Chains Under Reservation-Based Scheduling
[SEC'19] E2M: An Energy-Efficient Middleware for Computer Vision Applications on Autonomous Mobile Robots
[ICDCS'18] OpenVDAP: An Open Vehicular Data Analytics Platform for CAVs
[OSDI'22] Microsecond-scale Preemption for Concurrent GPU-accelerated DNN Inferences
[ATC'20] NeuOS: A Latency-Predictable Multi-Dimensional Optimization Framework for DNN-driven Autonomous Systems
[ATC'20] ALERT: Accurate Learning for Energy and Timeliness
[RTSS'20] On Removing Algorithmic Priority Inversion from Mission-critical Machine Inference Pipelines
[RTSS'19] Pipelined Data-Parallel CPU/GPU Scheduling for Multi-DNN Real-Time Inference
[ATX'16] MEANTIME: Achieving Both Minimal Energy and Timeliness with Approximate Computing
[ATC'11] TimeGraph: GPU Scheduling for Real-Time Multi-Tasking Environments
[RTAS'04] Feedback-based real-time scheduling in autonomous vehicle systems
[ATC'22] SOTER: Guarding Black-box Inference for General Neural Networks at the Edge
[ASPLOS'21] Quantifying the design-space tradeoffs in autonomous drones
[ISCA'21] RoboX: An End-to-End Solution to Accelerate Autonomous Control in Robotics
[MICRO'21] Archytas: A Framework for Synthesizing and Dynamically Optimizing Accelerators for Robotic Localization
[HPCA'21] Eudoxus: Characterizing and Accelerating Localization in Autonomous Machines
[RTAS'20] Co-Optimizing Performance and Memory Footprint Via Integrated CPU/GPU Memory Management, an Implementation on Autonomous Driving Platform
[ASPLOS'18] The Architectural Implications of Autonomous Driving: Constraints and Acceleration
[RTAS'17] An Evaluation of the NVIDIA TX1 for Supporting Real-time Computer-Vision Workloads
[Apollo by Baidu] website Related Doc 1 Related Doc 2
[Autoware] website
[Comma3] openpilot
Another awesome Awesome Autonomous Driving