mlsanityData to 7 Oct 2026

Robust Perception Architecture Design for Automotive Cyber-Physical Systems

arXiv 2205.08067 ↗First posted 17 May 2022cs.LG cs.RO cs.SYcited by 4

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Abstract (arXiv)

In emerging automotive cyber-physical systems (CPS), accurate environmental perception is critical to achieving safety and performance goals. Enabling robust perception for vehicles requires solving multiple complex problems related to sensor selection/ placement, object detection, and sensor fusion. Current methods address these problems in isolation, which leads to inefficient solutions. We present PASTA, a novel framework for global co-optimization of deep learning and sensing for dependable vehicle perception. Experimental results with the Audi-TT and BMW-Minicooper vehicles show how PASTA can find robust, vehicle-specific perception architecture solutions.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 14 of its 41 references that are in the map. First posted on arXiv 17 May 2022.

Builds on

14 of 41 references.

References · 14

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  2. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  3. 2015SSD: Single Shot MultiBox Detectorcited by 3,125
  4. 2015Fast R-CNNcited by 2,930
  5. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  6. 2013Rich feature hierarchies for accurate object detection and semantic segmentationcited by 2,160
  7. 2018Object Detection with Deep Learning: A Reviewcited by 524
  8. 2020A Review and Comparative Study on Probabilistic Object Detection in Autonomous Drivingcited by 115
  9. 2020A Deep Learning-based Radar and Camera Sensor Fusion Architecture for Object Detectioncited by 70
  10. 2022Object Detection in Autonomous Vehicles: Status and Open Challengescited by 14
  11. 2021LATTE: LSTM Self-Attention based Anomaly Detection in Embedded Automotive Platformscited by 9
  12. 2021TENET: Temporal CNN with Attention for Anomaly Detection in Automotive Cyber-Physical Systemscited by 6
2 more
  1. 2022Roadmap for Cybersecurity in Autonomous Vehiclescited by 5
  2. 2019Multimodal 3D Object Detection from Simulated Pretrainingcited by 4

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Cited by year

Citing papers per year: 2023: 2; 2024: 1; 2025: 1.

4 papers.

  1. 2023R-TOSS: A Framework for Real-Time Object Detection using Semi-Structured Pruningcited by 4
  2. 2023Cross-Layer Design for AI Acceleration with Non-Coherent Optical Computingcited by 3
  3. 2024Optical Computing for Deep Neural Network Acceleration: Foundations, Recent Developments, and Emerging Directionscited by 0
  4. 2025PaniCar: Securing the Perception of Advanced Driving Assistance Systems Against Emergency Vehicle Lightingcited by 0